diff --git a/adapter/.gitattributes b/adapter/.gitattributes
new file mode 100644
index 0000000000000000000000000000000000000000..21b6e824e60ceef1b569bccac55aaf462568000c
--- /dev/null
+++ b/adapter/.gitattributes
@@ -0,0 +1 @@
+adapter_model.bin filter=lfs diff=lfs merge=lfs -text
diff --git a/adapter/README.md b/adapter/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..2e9b14f43b35766402c6c1edc8c01859ee3b0050
--- /dev/null
+++ b/adapter/README.md
@@ -0,0 +1,202 @@
+---
+base_model: Willow123/LVP_R560_IHD24_S3_1024_N24_CAT
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.8.2
diff --git a/adapter/adapter_config.json b/adapter/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..79b4f02379f910531baf0454ae31bb4ad0dc78e5
--- /dev/null
+++ b/adapter/adapter_config.json
@@ -0,0 +1,32 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/mnt/hwfile/mllm/zhangpan/share/from/xiaoyi/LVP_R560_IHD24_S3_1024_N24_CAT/LVP_R560_IHD24_S3_0726_N24",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 128,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": [
+    "video_mem_proj"
+  ],
+  "peft_type": "LORA",
+  "r": 128,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "feed_forward.w2",
+    "attention.wo",
+    "feed_forward.w3",
+    "feed_forward.w1",
+    "attention.wqkv"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_rslora": false
+}
diff --git a/adapter/adapter_model.bin b/adapter/adapter_model.bin
new file mode 100644
index 0000000000000000000000000000000000000000..64d3599083dc5464b098d20b4daa26cf3ee66767
--- /dev/null
+++ b/adapter/adapter_model.bin
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bc9d0e035f664fbf923ef2c5f1b792d06e9d354aaac940764d6344f206275985
+size 650245533
diff --git a/adapter/added_tokens.json b/adapter/added_tokens.json
new file mode 100644
index 0000000000000000000000000000000000000000..39090265148ac44e5d5ce46e69594ac3ad34b1e5
--- /dev/null
+++ b/adapter/added_tokens.json
@@ -0,0 +1,8 @@
+{
+  "<|action_end|>": 92547,
+  "<|action_start|>": 92546,
+  "<|im_end|>": 92545,
+  "<|im_start|>": 92544,
+  "<|interpreter|>": 92548,
+  "<|plugin|>": 92549
+}
diff --git a/adapter/special_tokens_map.json b/adapter/special_tokens_map.json
new file mode 100644
index 0000000000000000000000000000000000000000..1023d3510a8f6a72f071f934b9319d2b3dba616e
--- /dev/null
+++ b/adapter/special_tokens_map.json
@@ -0,0 +1,38 @@
+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|action_start|>",
+    "<|action_end|>",
+    "<|interpreter|>",
+    "<|plugin|>"
+  ],
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}
diff --git a/adapter/tokenization_internlm2.py b/adapter/tokenization_internlm2.py
new file mode 100644
index 0000000000000000000000000000000000000000..ff53eba214b313c86ef489a823167a7ef2b52c09
--- /dev/null
+++ b/adapter/tokenization_internlm2.py
@@ -0,0 +1,236 @@
+# coding=utf-8
+# Copyright (c) The InternLM team and The HuggingFace Inc. team. All rights reserved.
+#
+# This code is based on transformers/src/transformers/models/llama/tokenization_llama.py
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Tokenization classes for InternLM."""
+import os
+from shutil import copyfile
+from typing import Any, Dict, List, Optional, Tuple
+
+import sentencepiece as spm
+from transformers.tokenization_utils import PreTrainedTokenizer
+from transformers.utils import logging
+
+logger = logging.get_logger(__name__)
+
+VOCAB_FILES_NAMES = {"vocab_file": "./tokenizer.model"}
+
+PRETRAINED_VOCAB_FILES_MAP = {}
+
+
+# Modified from transformers.model.llama.tokenization_llama.LlamaTokenizer
+class InternLM2Tokenizer(PreTrainedTokenizer):
+    """
+    Construct a InternLM2 tokenizer. Based on byte-level Byte-Pair-Encoding.
+
+    Args:
+        vocab_file (`str`):
+            Path to the vocabulary file.
+    """
+
+    vocab_files_names = VOCAB_FILES_NAMES
+    pretrained_vocab_files_map = PRETRAINED_VOCAB_FILES_MAP
+    model_input_names = ["input_ids", "attention_mask"]
+    _auto_class = "AutoTokenizer"
+
+    def __init__(
+        self,
+        vocab_file,
+        unk_token="<unk>",
+        bos_token="<s>",
+        eos_token="</s>",
+        pad_token="</s>",
+        sp_model_kwargs: Optional[Dict[str, Any]] = None,
+        add_bos_token=True,
+        add_eos_token=False,
+        decode_with_prefix_space=False,
+        clean_up_tokenization_spaces=False,
+        **kwargs,
+    ):
+        self.sp_model_kwargs = {} if sp_model_kwargs is None else sp_model_kwargs
+        self.vocab_file = vocab_file
+        self.add_bos_token = add_bos_token
+        self.add_eos_token = add_eos_token
+        self.decode_with_prefix_space = decode_with_prefix_space
+        self.sp_model = spm.SentencePieceProcessor(**self.sp_model_kwargs)
+        self.sp_model.Load(vocab_file)
+        self._no_prefix_space_tokens = None
+        super().__init__(
+            bos_token=bos_token,
+            eos_token=eos_token,
+            unk_token=unk_token,
+            pad_token=pad_token,
+            clean_up_tokenization_spaces=clean_up_tokenization_spaces,
+            **kwargs,
+        )
+
+    @property
+    def no_prefix_space_tokens(self):
+        if self._no_prefix_space_tokens is None:
+            vocab = self.convert_ids_to_tokens(list(range(self.vocab_size)))
+            self._no_prefix_space_tokens = {i for i, tok in enumerate(vocab) if not tok.startswith("▁")}
+        return self._no_prefix_space_tokens
+
+    @property
+    def vocab_size(self):
+        """Returns vocab size"""
+        return self.sp_model.get_piece_size()
+
+    @property
+    def bos_token_id(self) -> Optional[int]:
+        return self.sp_model.bos_id()
+
+    @property
+    def eos_token_id(self) -> Optional[int]:
+        return self.sp_model.eos_id()
+
+    def get_vocab(self):
+        """Returns vocab as a dict"""
+        vocab = {self.convert_ids_to_tokens(i): i for i in range(self.vocab_size)}
+        vocab.update(self.added_tokens_encoder)
+        return vocab
+
+    def _tokenize(self, text):
+        """Returns a tokenized string."""
+        return self.sp_model.encode(text, out_type=str)
+
+    def _convert_token_to_id(self, token):
+        """Converts a token (str) in an id using the vocab."""
+        return self.sp_model.piece_to_id(token)
+
+    def _convert_id_to_token(self, index):
+        """Converts an index (integer) in a token (str) using the vocab."""
+        token = self.sp_model.IdToPiece(index)
+        return token
+
+    def _maybe_add_prefix_space(self, tokens, decoded):
+        if tokens and tokens[0] not in self.no_prefix_space_tokens:
+            return " " + decoded
+        else:
+            return decoded
+
+    def convert_tokens_to_string(self, tokens):
+        """Converts a sequence of tokens (string) in a single string."""
+        current_sub_tokens = []
+        out_string = ""
+        prev_is_special = False
+        for token in tokens:
+            # make sure that special tokens are not decoded using sentencepiece model
+            if token in self.all_special_tokens:
+                if not prev_is_special:
+                    out_string += " "
+                out_string += self.sp_model.decode(current_sub_tokens) + token
+                prev_is_special = True
+                current_sub_tokens = []
+            else:
+                current_sub_tokens.append(token)
+                prev_is_special = False
+        out_string += self.sp_model.decode(current_sub_tokens)
+        out_string = self.clean_up_tokenization(out_string)
+        out_string = self._maybe_add_prefix_space(tokens=tokens, decoded=out_string)
+        return out_string[1:]
+
+    def save_vocabulary(self, save_directory, filename_prefix: Optional[str] = None) -> Tuple[str]:
+        """
+        Save the vocabulary and special tokens file to a directory.
+
+        Args:
+            save_directory (`str`):
+                The directory in which to save the vocabulary.
+
+        Returns:
+            `Tuple(str)`: Paths to the files saved.
+        """
+        if not os.path.isdir(save_directory):
+            logger.error(f"Vocabulary path ({save_directory}) should be a directory")
+            return
+        out_vocab_file = os.path.join(
+            save_directory, (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]
+        )
+
+        if os.path.abspath(self.vocab_file) != os.path.abspath(out_vocab_file) and os.path.isfile(self.vocab_file):
+            copyfile(self.vocab_file, out_vocab_file)
+        elif not os.path.isfile(self.vocab_file):
+            with open(out_vocab_file, "wb") as fi:
+                content_spiece_model = self.sp_model.serialized_model_proto()
+                fi.write(content_spiece_model)
+
+        return (out_vocab_file,)
+
+    def build_inputs_with_special_tokens(self, token_ids_0, token_ids_1=None):
+        if self.add_bos_token:
+            bos_token_ids = [self.bos_token_id]
+        else:
+            bos_token_ids = []
+
+        output = bos_token_ids + token_ids_0
+
+        if token_ids_1 is not None:
+            output = output + token_ids_1
+
+        if self.add_eos_token:
+            output = output + [self.eos_token_id]
+
+        return output
+
+    def get_special_tokens_mask(
+        self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None, already_has_special_tokens: bool = False
+    ) -> List[int]:
+        """
+        Retrieve sequence ids from a token list that has no special tokens added. This method is called when adding
+        special tokens using the tokenizer `prepare_for_model` method.
+
+        Args:
+            token_ids_0 (`List[int]`):
+                List of IDs.
+            token_ids_1 (`List[int]`, *optional*):
+                Optional second list of IDs for sequence pairs.
+            already_has_special_tokens (`bool`, *optional*, defaults to `False`):
+                Whether or not the token list is already formatted with special tokens for the model.
+
+        Returns:
+            `List[int]`: A list of integers in the range [0, 1]: 1 for a special token, 0 for a sequence token.
+        """
+        if already_has_special_tokens:
+            return super().get_special_tokens_mask(
+                token_ids_0=token_ids_0, token_ids_1=token_ids_1, already_has_special_tokens=True
+            )
+
+        if token_ids_1 is None:
+            return [1] + ([0] * len(token_ids_0)) + [1]
+        return [1] + ([0] * len(token_ids_0)) + [1, 1] + ([0] * len(token_ids_1)) + [1]
+
+    def create_token_type_ids_from_sequences(
+        self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None
+    ) -> List[int]:
+        """
+        Create a mask from the two sequences passed to be used in a sequence-pair classification task. T5 does not make
+        use of token type ids, therefore a list of zeros is returned.
+
+        Args:
+            token_ids_0 (`List[int]`):
+                List of IDs.
+            token_ids_1 (`List[int]`, *optional*):
+                Optional second list of IDs for sequence pairs.
+
+        Returns:
+            `List[int]`: List of zeros.
+        """
+        eos = [self.eos_token_id]
+
+        if token_ids_1 is None:
+            return len(token_ids_0 + eos) * [0]
+        return len(token_ids_0 + eos + token_ids_1 + eos) * [0]
diff --git a/adapter/tokenizer.model b/adapter/tokenizer.model
new file mode 100644
index 0000000000000000000000000000000000000000..6600712949ca9c4ffb50f25275993a21fba0b408
--- /dev/null
+++ b/adapter/tokenizer.model
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f868398fc4e05ee1e8aeba95ddf18ddcc45b8bce55d5093bead5bbf80429b48b
+size 1477754
diff --git a/adapter/tokenizer_config.json b/adapter/tokenizer_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c09328e63848220f5be589fd72e139f38ecbf5fb
--- /dev/null
+++ b/adapter/tokenizer_config.json
@@ -0,0 +1,99 @@
+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "92538": {
+      "content": "<|plugin|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "92539": {
+      "content": "<|interpreter|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "92540": {
+      "content": "<|action_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "92541": {
+      "content": "<|action_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "92542": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "92543": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|action_start|>",
+    "<|action_end|>",
+    "<|interpreter|>",
+    "<|plugin|>"
+  ],
+  "auto_map": {
+    "AutoTokenizer": [
+      "tokenization_internlm2.InternLM2Tokenizer",
+      null
+    ]
+  },
+  "bos_token": "<s>",
+  "chat_template": "{{ bos_token }}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "</s>",
+  "padding_side": "right",
+  "tokenizer_class": "InternLM2Tokenizer",
+  "unk_token": "<unk>"
+}
diff --git a/adapter/zero_to_fp32.py b/adapter/zero_to_fp32.py
new file mode 100755
index 0000000000000000000000000000000000000000..c98caae31534368be22b67fc4ae906836c992a8d
--- /dev/null
+++ b/adapter/zero_to_fp32.py
@@ -0,0 +1,587 @@
+#!/usr/bin/env python
+
+# Copyright (c) Microsoft Corporation.
+# SPDX-License-Identifier: Apache-2.0
+
+# DeepSpeed Team
+
+# This script extracts fp32 consolidated weights from a zero 1, 2 and 3 DeepSpeed checkpoints. It gets
+# copied into the top level checkpoint dir, so the user can easily do the conversion at any point in
+# the future. Once extracted, the weights don't require DeepSpeed and can be used in any
+# application.
+#
+# example: python zero_to_fp32.py . pytorch_model.bin
+
+import argparse
+import torch
+import glob
+import math
+import os
+import re
+from collections import OrderedDict
+from dataclasses import dataclass
+
+# while this script doesn't use deepspeed to recover data, since the checkpoints are pickled with
+# DeepSpeed data structures it has to be available in the current python environment.
+from deepspeed.utils import logger
+from deepspeed.checkpoint.constants import (DS_VERSION, OPTIMIZER_STATE_DICT, SINGLE_PARTITION_OF_FP32_GROUPS,
+                                            FP32_FLAT_GROUPS, ZERO_STAGE, PARTITION_COUNT, PARAM_SHAPES, BUFFER_NAMES,
+                                            FROZEN_PARAM_SHAPES, FROZEN_PARAM_FRAGMENTS)
+
+
+@dataclass
+class zero_model_state:
+    buffers: dict()
+    param_shapes: dict()
+    shared_params: list
+    ds_version: int
+    frozen_param_shapes: dict()
+    frozen_param_fragments: dict()
+
+
+debug = 0
+
+# load to cpu
+device = torch.device('cpu')
+
+
+def atoi(text):
+    return int(text) if text.isdigit() else text
+
+
+def natural_keys(text):
+    '''
+    alist.sort(key=natural_keys) sorts in human order
+    http://nedbatchelder.com/blog/200712/human_sorting.html
+    (See Toothy's implementation in the comments)
+    '''
+    return [atoi(c) for c in re.split(r'(\d+)', text)]
+
+
+def get_model_state_file(checkpoint_dir, zero_stage):
+    if not os.path.isdir(checkpoint_dir):
+        raise FileNotFoundError(f"Directory '{checkpoint_dir}' doesn't exist")
+
+    # there should be only one file
+    if zero_stage <= 2:
+        file = os.path.join(checkpoint_dir, "mp_rank_00_model_states.pt")
+    elif zero_stage == 3:
+        file = os.path.join(checkpoint_dir, "zero_pp_rank_0_mp_rank_00_model_states.pt")
+
+    if not os.path.exists(file):
+        raise FileNotFoundError(f"can't find model states file at '{file}'")
+
+    return file
+
+
+def get_checkpoint_files(checkpoint_dir, glob_pattern):
+    # XXX: need to test that this simple glob rule works for multi-node setup too
+    ckpt_files = sorted(glob.glob(os.path.join(checkpoint_dir, glob_pattern)), key=natural_keys)
+
+    if len(ckpt_files) == 0:
+        raise FileNotFoundError(f"can't find {glob_pattern} files in directory '{checkpoint_dir}'")
+
+    return ckpt_files
+
+
+def get_optim_files(checkpoint_dir):
+    return get_checkpoint_files(checkpoint_dir, "*_optim_states.pt")
+
+
+def get_model_state_files(checkpoint_dir):
+    return get_checkpoint_files(checkpoint_dir, "*_model_states.pt")
+
+
+def parse_model_states(files):
+    zero_model_states = []
+    for file in files:
+        state_dict = torch.load(file, map_location=device)
+
+        if BUFFER_NAMES not in state_dict:
+            raise ValueError(f"{file} is not a model state checkpoint")
+        buffer_names = state_dict[BUFFER_NAMES]
+        if debug:
+            print("Found buffers:", buffer_names)
+
+        # recover just the buffers while restoring them to fp32 if they were saved in fp16
+        buffers = {k: v.float() for k, v in state_dict["module"].items() if k in buffer_names}
+        param_shapes = state_dict[PARAM_SHAPES]
+
+        # collect parameters that are included in param_shapes
+        param_names = []
+        for s in param_shapes:
+            for name in s.keys():
+                param_names.append(name)
+
+        # update with frozen parameters
+        frozen_param_shapes = state_dict.get(FROZEN_PARAM_SHAPES, None)
+        if frozen_param_shapes is not None:
+            if debug:
+                print(f"Found frozen_param_shapes: {frozen_param_shapes}")
+            param_names += list(frozen_param_shapes.keys())
+
+        # handle shared params
+        shared_params = [[k, v] for k, v in state_dict["shared_params"].items()]
+
+        ds_version = state_dict.get(DS_VERSION, None)
+
+        frozen_param_fragments = state_dict.get(FROZEN_PARAM_FRAGMENTS, None)
+
+        z_model_state = zero_model_state(buffers=buffers,
+                                         param_shapes=param_shapes,
+                                         shared_params=shared_params,
+                                         ds_version=ds_version,
+                                         frozen_param_shapes=frozen_param_shapes,
+                                         frozen_param_fragments=frozen_param_fragments)
+        zero_model_states.append(z_model_state)
+
+    return zero_model_states
+
+
+def parse_optim_states(files, ds_checkpoint_dir):
+
+    total_files = len(files)
+    state_dicts = []
+    for f in files:
+        state_dict = torch.load(f, map_location=device)
+        # immediately discard the potentially huge 2 optimizer states as we only care for fp32 master weights
+        # and also handle the case where it was already removed by another helper script
+        state_dict["optimizer_state_dict"].pop("optimizer_state_dict", None)
+        state_dicts.append(state_dict)
+
+    if not ZERO_STAGE in state_dicts[0][OPTIMIZER_STATE_DICT]:
+        raise ValueError(f"{files[0]} is not a zero checkpoint")
+    zero_stage = state_dicts[0][OPTIMIZER_STATE_DICT][ZERO_STAGE]
+    world_size = state_dicts[0][OPTIMIZER_STATE_DICT][PARTITION_COUNT]
+
+    # For ZeRO-2 each param group can have different partition_count as data parallelism for expert
+    # parameters can be different from data parallelism for non-expert parameters. So we can just
+    # use the max of the partition_count to get the dp world_size.
+
+    if type(world_size) is list:
+        world_size = max(world_size)
+
+    if world_size != total_files:
+        raise ValueError(
+            f"Expected {world_size} of '*_optim_states.pt' under '{ds_checkpoint_dir}' but found {total_files} files. "
+            "Possibly due to an overwrite of an old checkpoint, or a checkpoint didn't get saved by one or more processes."
+        )
+
+    # the groups are named differently in each stage
+    if zero_stage <= 2:
+        fp32_groups_key = SINGLE_PARTITION_OF_FP32_GROUPS
+    elif zero_stage == 3:
+        fp32_groups_key = FP32_FLAT_GROUPS
+    else:
+        raise ValueError(f"unknown zero stage {zero_stage}")
+
+    if zero_stage <= 2:
+        fp32_flat_groups = [state_dicts[i][OPTIMIZER_STATE_DICT][fp32_groups_key] for i in range(len(state_dicts))]
+    elif zero_stage == 3:
+        # if there is more than one param group, there will be multiple flattened tensors - one
+        # flattened tensor per group - for simplicity merge them into a single tensor
+        #
+        # XXX: could make the script more memory efficient for when there are multiple groups - it
+        # will require matching the sub-lists of param_shapes for each param group flattened tensor
+
+        fp32_flat_groups = [
+            torch.cat(state_dicts[i][OPTIMIZER_STATE_DICT][fp32_groups_key], 0) for i in range(len(state_dicts))
+        ]
+
+    return zero_stage, world_size, fp32_flat_groups
+
+
+def _get_fp32_state_dict_from_zero_checkpoint(ds_checkpoint_dir):
+    """
+    Returns fp32 state_dict reconstructed from ds checkpoint
+
+    Args:
+        - ``ds_checkpoint_dir``: path to the deepspeed checkpoint folder (where the optimizer files are)
+
+    """
+    print(f"Processing zero checkpoint '{ds_checkpoint_dir}'")
+
+    optim_files = get_optim_files(ds_checkpoint_dir)
+    zero_stage, world_size, fp32_flat_groups = parse_optim_states(optim_files, ds_checkpoint_dir)
+    print(f"Detected checkpoint of type zero stage {zero_stage}, world_size: {world_size}")
+
+    model_files = get_model_state_files(ds_checkpoint_dir)
+
+    zero_model_states = parse_model_states(model_files)
+    print(f'Parsing checkpoint created by deepspeed=={zero_model_states[0].ds_version}')
+
+    if zero_stage <= 2:
+        return _get_fp32_state_dict_from_zero2_checkpoint(world_size, fp32_flat_groups, zero_model_states)
+    elif zero_stage == 3:
+        return _get_fp32_state_dict_from_zero3_checkpoint(world_size, fp32_flat_groups, zero_model_states)
+
+
+def _zero2_merge_frozen_params(state_dict, zero_model_states):
+    if zero_model_states[0].frozen_param_shapes is None or len(zero_model_states[0].frozen_param_shapes) == 0:
+        return
+
+    frozen_param_shapes = zero_model_states[0].frozen_param_shapes
+    frozen_param_fragments = zero_model_states[0].frozen_param_fragments
+
+    if debug:
+        num_elem = sum(s.numel() for s in frozen_param_shapes.values())
+        print(f'rank 0: {FROZEN_PARAM_SHAPES}.numel = {num_elem}')
+
+        wanted_params = len(frozen_param_shapes)
+        wanted_numel = sum(s.numel() for s in frozen_param_shapes.values())
+        avail_numel = sum([p.numel() for p in frozen_param_fragments.values()])
+        print(f'Frozen params: Have {avail_numel} numels to process.')
+        print(f'Frozen params: Need {wanted_numel} numels in {wanted_params} params')
+
+    total_params = 0
+    total_numel = 0
+    for name, shape in frozen_param_shapes.items():
+        total_params += 1
+        unpartitioned_numel = shape.numel()
+        total_numel += unpartitioned_numel
+
+        state_dict[name] = frozen_param_fragments[name]
+
+        if debug:
+            print(f"{name} full shape: {shape} unpartitioned numel {unpartitioned_numel} ")
+
+    print(f"Reconstructed Frozen fp32 state dict with {total_params} params {total_numel} elements")
+
+
+def _zero2_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states):
+    param_shapes = zero_model_states[0].param_shapes
+
+    # Reconstruction protocol:
+    #
+    # XXX: document this
+
+    if debug:
+        for i in range(world_size):
+            for j in range(len(fp32_flat_groups[0])):
+                print(f"{FP32_FLAT_GROUPS}[{i}][{j}].shape={fp32_flat_groups[i][j].shape}")
+
+    # XXX: memory usage doubles here (zero2)
+    num_param_groups = len(fp32_flat_groups[0])
+    merged_single_partition_of_fp32_groups = []
+    for i in range(num_param_groups):
+        merged_partitions = [sd[i] for sd in fp32_flat_groups]
+        full_single_fp32_vector = torch.cat(merged_partitions, 0)
+        merged_single_partition_of_fp32_groups.append(full_single_fp32_vector)
+    avail_numel = sum(
+        [full_single_fp32_vector.numel() for full_single_fp32_vector in merged_single_partition_of_fp32_groups])
+
+    if debug:
+        wanted_params = sum([len(shapes) for shapes in param_shapes])
+        wanted_numel = sum([sum(shape.numel() for shape in shapes.values()) for shapes in param_shapes])
+        # not asserting if there is a mismatch due to possible padding
+        print(f"Have {avail_numel} numels to process.")
+        print(f"Need {wanted_numel} numels in {wanted_params} params.")
+
+    # params
+    # XXX: for huge models that can't fit into the host's RAM we will have to recode this to support
+    # out-of-core computing solution
+    total_numel = 0
+    total_params = 0
+    for shapes, full_single_fp32_vector in zip(param_shapes, merged_single_partition_of_fp32_groups):
+        offset = 0
+        avail_numel = full_single_fp32_vector.numel()
+        for name, shape in shapes.items():
+
+            unpartitioned_numel = shape.numel()
+            total_numel += unpartitioned_numel
+            total_params += 1
+
+            if debug:
+                print(f"{name} full shape: {shape} unpartitioned numel {unpartitioned_numel} ")
+            state_dict[name] = full_single_fp32_vector.narrow(0, offset, unpartitioned_numel).view(shape)
+            offset += unpartitioned_numel
+
+        # Z2 started to align to 2*world_size to improve nccl performance. Therefore both offset and
+        # avail_numel can differ by anywhere between 0..2*world_size. Due to two unrelated complex
+        # paddings performed in the code it's almost impossible to predict the exact numbers w/o the
+        # live optimizer object, so we are checking that the numbers are within the right range
+        align_to = 2 * world_size
+
+        def zero2_align(x):
+            return align_to * math.ceil(x / align_to)
+
+        if debug:
+            print(f"original offset={offset}, avail_numel={avail_numel}")
+
+        offset = zero2_align(offset)
+        avail_numel = zero2_align(avail_numel)
+
+        if debug:
+            print(f"aligned  offset={offset}, avail_numel={avail_numel}")
+
+        # Sanity check
+        if offset != avail_numel:
+            raise ValueError(f"consumed {offset} numels out of {avail_numel} - something is wrong")
+
+    print(f"Reconstructed fp32 state dict with {total_params} params {total_numel} elements")
+
+
+def _get_fp32_state_dict_from_zero2_checkpoint(world_size, fp32_flat_groups, zero_model_states):
+    state_dict = OrderedDict()
+
+    # buffers
+    buffers = zero_model_states[0].buffers
+    state_dict.update(buffers)
+    if debug:
+        print(f"added {len(buffers)} buffers")
+
+    _zero2_merge_frozen_params(state_dict, zero_model_states)
+
+    _zero2_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states)
+
+    # recover shared parameters
+    for pair in zero_model_states[0].shared_params:
+        if pair[1] in state_dict:
+            state_dict[pair[0]] = state_dict[pair[1]]
+
+    return state_dict
+
+
+def zero3_partitioned_param_info(unpartitioned_numel, world_size):
+    remainder = unpartitioned_numel % world_size
+    padding_numel = (world_size - remainder) if remainder else 0
+    partitioned_numel = math.ceil(unpartitioned_numel / world_size)
+    return partitioned_numel, padding_numel
+
+
+def _zero3_merge_frozen_params(state_dict, world_size, zero_model_states):
+    if zero_model_states[0].frozen_param_shapes is None or len(zero_model_states[0].frozen_param_shapes) == 0:
+        return
+
+    if debug:
+        for i in range(world_size):
+            num_elem = sum(s.numel() for s in zero_model_states[i].frozen_param_fragments.values())
+            print(f'rank {i}: {FROZEN_PARAM_SHAPES}.numel = {num_elem}')
+
+        frozen_param_shapes = zero_model_states[0].frozen_param_shapes
+        wanted_params = len(frozen_param_shapes)
+        wanted_numel = sum(s.numel() for s in frozen_param_shapes.values())
+        avail_numel = sum([p.numel() for p in zero_model_states[0].frozen_param_fragments.values()]) * world_size
+        print(f'Frozen params: Have {avail_numel} numels to process.')
+        print(f'Frozen params: Need {wanted_numel} numels in {wanted_params} params')
+
+    total_params = 0
+    total_numel = 0
+    for name, shape in zero_model_states[0].frozen_param_shapes.items():
+        total_params += 1
+        unpartitioned_numel = shape.numel()
+        total_numel += unpartitioned_numel
+
+        param_frags = tuple(model_state.frozen_param_fragments[name] for model_state in zero_model_states)
+        state_dict[name] = torch.cat(param_frags, 0).narrow(0, 0, unpartitioned_numel).view(shape)
+
+        partitioned_numel, partitioned_padding_numel = zero3_partitioned_param_info(unpartitioned_numel, world_size)
+
+        if debug:
+            print(
+                f"Frozen params: {total_params} {name} full shape: {shape} partition0 numel={partitioned_numel} partitioned_padding_numel={partitioned_padding_numel}"
+            )
+
+    print(f"Reconstructed Frozen fp32 state dict with {total_params} params {total_numel} elements")
+
+
+def _zero3_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states):
+    param_shapes = zero_model_states[0].param_shapes
+    avail_numel = fp32_flat_groups[0].numel() * world_size
+    # Reconstruction protocol: For zero3 we need to zip the partitions together at boundary of each
+    # param, re-consolidating each param, while dealing with padding if any
+
+    # merge list of dicts, preserving order
+    param_shapes = {k: v for d in param_shapes for k, v in d.items()}
+
+    if debug:
+        for i in range(world_size):
+            print(f"{FP32_FLAT_GROUPS}[{i}].shape={fp32_flat_groups[i].shape}")
+
+        wanted_params = len(param_shapes)
+        wanted_numel = sum(shape.numel() for shape in param_shapes.values())
+        # not asserting if there is a mismatch due to possible padding
+        avail_numel = fp32_flat_groups[0].numel() * world_size
+        print(f"Trainable params: Have {avail_numel} numels to process.")
+        print(f"Trainable params: Need {wanted_numel} numels in {wanted_params} params.")
+
+    # params
+    # XXX: for huge models that can't fit into the host's RAM we will have to recode this to support
+    # out-of-core computing solution
+    offset = 0
+    total_numel = 0
+    total_params = 0
+    for name, shape in param_shapes.items():
+
+        unpartitioned_numel = shape.numel()
+        total_numel += unpartitioned_numel
+        total_params += 1
+
+        partitioned_numel, partitioned_padding_numel = zero3_partitioned_param_info(unpartitioned_numel, world_size)
+
+        if debug:
+            print(
+                f"Trainable params: {total_params} {name} full shape: {shape} partition0 numel={partitioned_numel} partitioned_padding_numel={partitioned_padding_numel}"
+            )
+
+        # XXX: memory usage doubles here
+        state_dict[name] = torch.cat(
+            tuple(fp32_flat_groups[i].narrow(0, offset, partitioned_numel) for i in range(world_size)),
+            0).narrow(0, 0, unpartitioned_numel).view(shape)
+        offset += partitioned_numel
+
+    offset *= world_size
+
+    # Sanity check
+    if offset != avail_numel:
+        raise ValueError(f"consumed {offset} numels out of {avail_numel} - something is wrong")
+
+    print(f"Reconstructed Trainable fp32 state dict with {total_params} params {total_numel} elements")
+
+
+def _get_fp32_state_dict_from_zero3_checkpoint(world_size, fp32_flat_groups, zero_model_states):
+    state_dict = OrderedDict()
+
+    # buffers
+    buffers = zero_model_states[0].buffers
+    state_dict.update(buffers)
+    if debug:
+        print(f"added {len(buffers)} buffers")
+
+    _zero3_merge_frozen_params(state_dict, world_size, zero_model_states)
+
+    _zero3_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states)
+
+    # recover shared parameters
+    for pair in zero_model_states[0].shared_params:
+        if pair[1] in state_dict:
+            state_dict[pair[0]] = state_dict[pair[1]]
+
+    return state_dict
+
+
+def get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag=None):
+    """
+    Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated state_dict that can be loaded with
+    ``load_state_dict()`` and used for training without DeepSpeed or shared with others, for example
+    via a model hub.
+
+    Args:
+        - ``checkpoint_dir``: path to the desired checkpoint folder
+        - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in 'latest' file. e.g., ``global_step14``
+
+    Returns:
+        - pytorch ``state_dict``
+
+    Note: this approach may not work if your application doesn't have sufficient free CPU memory and
+    you may need to use the offline approach using the ``zero_to_fp32.py`` script that is saved with
+    the checkpoint.
+
+    A typical usage might be ::
+
+        from deepspeed.utils.zero_to_fp32 import get_fp32_state_dict_from_zero_checkpoint
+        # do the training and checkpoint saving
+        state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir) # already on cpu
+        model = model.cpu() # move to cpu
+        model.load_state_dict(state_dict)
+        # submit to model hub or save the model to share with others
+
+    In this example the ``model`` will no longer be usable in the deepspeed context of the same
+    application. i.e. you will need to re-initialize the deepspeed engine, since
+    ``model.load_state_dict(state_dict)`` will remove all the deepspeed magic from it.
+
+    If you want it all done for you, use ``load_state_dict_from_zero_checkpoint`` instead.
+
+    """
+    if tag is None:
+        latest_path = os.path.join(checkpoint_dir, 'latest')
+        if os.path.isfile(latest_path):
+            with open(latest_path, 'r') as fd:
+                tag = fd.read().strip()
+        else:
+            raise ValueError(f"Unable to find 'latest' file at {latest_path}")
+
+    ds_checkpoint_dir = os.path.join(checkpoint_dir, tag)
+
+    if not os.path.isdir(ds_checkpoint_dir):
+        raise FileNotFoundError(f"Directory '{ds_checkpoint_dir}' doesn't exist")
+
+    return _get_fp32_state_dict_from_zero_checkpoint(ds_checkpoint_dir)
+
+
+def convert_zero_checkpoint_to_fp32_state_dict(checkpoint_dir, output_file, tag=None):
+    """
+    Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated ``state_dict`` file that can be
+    loaded with ``torch.load(file)`` + ``load_state_dict()`` and used for training without DeepSpeed.
+
+    Args:
+        - ``checkpoint_dir``: path to the desired checkpoint folder. (one that contains the tag-folder, like ``global_step14``)
+        - ``output_file``: path to the pytorch fp32 state_dict output file (e.g. path/pytorch_model.bin)
+        - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in the file named ``latest`` in the checkpoint folder, e.g., ``global_step14``
+    """
+
+    state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag)
+    print(f"Saving fp32 state dict to {output_file}")
+    torch.save(state_dict, output_file)
+
+
+def load_state_dict_from_zero_checkpoint(model, checkpoint_dir, tag=None):
+    """
+    1. Put the provided model to cpu
+    2. Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated ``state_dict``
+    3. Load it into the provided model
+
+    Args:
+        - ``model``: the model object to update
+        - ``checkpoint_dir``: path to the desired checkpoint folder. (one that contains the tag-folder, like ``global_step14``)
+        - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in the file named ``latest`` in the checkpoint folder, e.g., ``global_step14``
+
+    Returns:
+        - ``model`: modified model
+
+    Make sure you have plenty of CPU memory available before you call this function. If you don't
+    have enough use the ``zero_to_fp32.py`` utility to do the conversion. You will find it
+    conveniently placed for you in the checkpoint folder.
+
+    A typical usage might be ::
+
+        from deepspeed.utils.zero_to_fp32 import load_state_dict_from_zero_checkpoint
+        model = load_state_dict_from_zero_checkpoint(trainer.model, checkpoint_dir)
+        # submit to model hub or save the model to share with others
+
+    Note, that once this was run, the ``model`` will no longer be usable in the deepspeed context
+    of the same application. i.e. you will need to re-initialize the deepspeed engine, since
+    ``model.load_state_dict(state_dict)`` will remove all the deepspeed magic from it.
+
+    """
+    logger.info(f"Extracting fp32 weights")
+    state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag)
+
+    logger.info(f"Overwriting model with fp32 weights")
+    model = model.cpu()
+    model.load_state_dict(state_dict, strict=False)
+
+    return model
+
+
+if __name__ == "__main__":
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument("checkpoint_dir",
+                        type=str,
+                        help="path to the desired checkpoint folder, e.g., path/checkpoint-12")
+    parser.add_argument(
+        "output_file",
+        type=str,
+        help="path to the pytorch fp32 state_dict output file (e.g. path/checkpoint-12/pytorch_model.bin)")
+    parser.add_argument("-t",
+                        "--tag",
+                        type=str,
+                        default=None,
+                        help="checkpoint tag used as a unique identifier for checkpoint. e.g., global_step1")
+    parser.add_argument("-d", "--debug", action='store_true', help="enable debug")
+    args = parser.parse_args()
+
+    debug = args.debug
+
+    convert_zero_checkpoint_to_fp32_state_dict(args.checkpoint_dir, args.output_file, tag=args.tag)
diff --git a/audio/.gitattributes b/audio/.gitattributes
new file mode 100644
index 0000000000000000000000000000000000000000..279ed54b50840fc7db83ba48fb918a5b21e7ced7
--- /dev/null
+++ b/audio/.gitattributes
@@ -0,0 +1 @@
+model.safetensors filter=lfs diff=lfs merge=lfs -text
diff --git a/audio/added_tokens.json b/audio/added_tokens.json
new file mode 100644
index 0000000000000000000000000000000000000000..fa19ac6d83a25691b2629b35d7006a009dc996cb
--- /dev/null
+++ b/audio/added_tokens.json
@@ -0,0 +1,3290 @@
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+}
diff --git a/audio/chat_template.json b/audio/chat_template.json
new file mode 100644
index 0000000000000000000000000000000000000000..4e478a97e984f90e1c2e0dce6ce27359c74a13f0
--- /dev/null
+++ b/audio/chat_template.json
@@ -0,0 +1,3 @@
+{
+  "chat_template": "{% set audio_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n{% endif %}<|im_start|>{{ message['role'] }}\n{% if message['content'] is string %}{{ message['content'] }}<|im_end|>\n{% else %}{% for content in message['content'] %}{% if 'audio' in content or 'audio_url' in content %}{% set audio_count.value = audio_count.value + 1 %}Audio {{ audio_count.value }}: <|audio_bos|><|AUDIO|><|audio_eos|>\n{% elif 'text' in content %}{{ content['text'] }}{% endif %}{% endfor %}<|im_end|>\n{% endif %}{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant\n{% endif %}"
+}
diff --git a/audio/config.json b/audio/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..a72c32335ac524ac5b15fbb0dd284d655bed521c
--- /dev/null
+++ b/audio/config.json
@@ -0,0 +1,33 @@
+{
+  "_name_or_path": "/mnt/petrelfs/caoyuhang/InternLM-XComposer/finetune_audio/models/sft_base_3x_with_pt_extra",
+  "architectures": [
+    "Qwen2AudioForConditionalGeneration"
+  ],
+  "audio_config": {
+    "model_type": "qwen2_audio_encoder"
+  },
+  "audio_token_index": 151646,
+  "hidden_size": 1536,
+  "ignore_index": -100,
+  "model_type": "qwen2_audio",
+  "text_config": {
+    "bos_token_id": 151643,
+    "eos_token_id": 151645,
+    "hidden_size": 1536,
+    "intermediate_size": 8960,
+    "max_position_embeddings": 8192,
+    "model_type": "qwen2",
+    "num_attention_heads": 12,
+    "num_hidden_layers": 28,
+    "num_key_value_heads": 2,
+    "rms_norm_eps": 1e-05,
+    "tie_word_embeddings": true,
+    "torch_dtype": "bfloat16",
+    "use_mrope": false,
+    "vocab_size": 156032
+  },
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.45.0.dev0",
+  "use_cache": false,
+  "vocab_size": 156032
+}
diff --git a/audio/generation_config.json b/audio/generation_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..414d1ff36efff7f4227a885eb327d7e3d98b0287
--- /dev/null
+++ b/audio/generation_config.json
@@ -0,0 +1,7 @@
+{
+  "bos_token_id": 151643,
+  "eos_token_id": 151645,
+  "max_new_tokens": 2048,
+  "pad_token_id": 151643,
+  "transformers_version": "4.45.0.dev0"
+}
diff --git a/audio/model.safetensors b/audio/model.safetensors
new file mode 100644
index 0000000000000000000000000000000000000000..566247b09773b4e890e9e17dab70dedd9e0cc73c
--- /dev/null
+++ b/audio/model.safetensors
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:aba6b80d0789dc7ea0ff5576d0ef1d189fff78c1ce6f4abf66c570549875e5d2
+size 4377984696
diff --git a/audio/preprocessor_config.json b/audio/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..3cd6c4610c3e6e98af27fcdf9ffdcb83c498549a
--- /dev/null
+++ b/audio/preprocessor_config.json
@@ -0,0 +1,14 @@
+{
+  "chunk_length": 30,
+  "feature_extractor_type": "WhisperFeatureExtractor",
+  "feature_size": 128,
+  "hop_length": 160,
+  "n_fft": 400,
+  "n_samples": 480000,
+  "nb_max_frames": 3000,
+  "padding_side": "right",
+  "padding_value": 0.0,
+  "processor_class": "Qwen2AudioProcessor",
+  "return_attention_mask": true,
+  "sampling_rate": 16000
+}
diff --git a/audio/sft_args.json b/audio/sft_args.json
new file mode 100644
index 0000000000000000000000000000000000000000..bbd7cec025269df175c01e99d9a9eb8c414a110b
--- /dev/null
+++ b/audio/sft_args.json
@@ -0,0 +1,247 @@
+{
+  "model_type": "qwen2-audio-7b-instruct",
+  "model_id_or_path": "/mnt/petrelfs/caoyuhang/InternLM-XComposer/finetune_audio/models/sft_base_3x_with_pt_extra",
+  "model_revision": "master",
+  "full_determinism": false,
+  "sft_type": "full",
+  "freeze_parameters": [
+    "audio_tower"
+  ],
+  "freeze_vit": false,
+  "freeze_parameters_ratio": 0.0,
+  "additional_trainable_parameters": [],
+  "tuner_backend": "peft",
+  "template_type": "qwen2-audio",
+  "output_dir": "/mnt/petrelfs/caoyuhang/InternLM-XComposer/finetune_audio/output/sft-continue_base_silence/qwen2-audio-7b-instruct/v0-20241120-155458",
+  "add_output_dir_suffix": true,
+  "ddp_backend": "nccl",
+  "ddp_find_unused_parameters": null,
+  "ddp_broadcast_buffers": null,
+  "ddp_timeout": 1800,
+  "seed": 42,
+  "resume_from_checkpoint": null,
+  "resume_only_model": false,
+  "ignore_data_skip": false,
+  "dtype": "bf16",
+  "packing": false,
+  "train_backend": "transformers",
+  "tp": 1,
+  "pp": 1,
+  "min_lr": null,
+  "sequence_parallel": false,
+  "model_kwargs": null,
+  "loss_name": null,
+  "dataset": [
+    "data/sft_base_silence.jsonl"
+  ],
+  "val_dataset": [],
+  "dataset_seed": 42,
+  "dataset_test_ratio": 0.01,
+  "use_loss_scale": false,
+  "loss_scale_config_path": "/mnt/petrelfs/caoyuhang/ms-swift/swift/llm/agent/default_loss_scale_config.json",
+  "system": "You are a helpful assistant.",
+  "tools_prompt": "react_en",
+  "max_length": 2048,
+  "truncation_strategy": "delete",
+  "check_dataset_strategy": "none",
+  "streaming": false,
+  "streaming_val_size": 0,
+  "streaming_buffer_size": 16384,
+  "model_name": [
+    null,
+    null
+  ],
+  "model_author": [
+    null,
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+  ],
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+  "quantization_bit": 0,
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+  "hqq_dynamic_config_path": null,
+  "bnb_4bit_comp_dtype": "bf16",
+  "bnb_4bit_quant_type": "nf4",
+  "bnb_4bit_use_double_quant": true,
+  "bnb_4bit_quant_storage": null,
+  "rescale_image": -1,
+  "target_modules": "^(language_model|multi_modal_projector)(?!.*(lm_head|output|emb|wte|shared)).*",
+  "target_regex": null,
+  "modules_to_save": [],
+  "lora_rank": 8,
+  "lora_alpha": 32,
+  "lora_dropout": 0.05,
+  "lora_bias_trainable": "none",
+  "lora_dtype": "AUTO",
+  "lora_lr_ratio": null,
+  "use_rslora": false,
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+  "init_lora_weights": "true",
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+  "fourier_scaling": 300.0,
+  "rope_scaling": null,
+  "boft_block_size": 4,
+  "boft_block_num": 0,
+  "boft_n_butterfly_factor": 1,
+  "boft_dropout": 0.0,
+  "vera_rank": 256,
+  "vera_projection_prng_key": 0,
+  "vera_dropout": 0.0,
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+  "adapter_act": "gelu",
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+  "use_galore": false,
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+  "galore_rank": 128,
+  "galore_update_proj_gap": 50,
+  "galore_scale": 1.0,
+  "galore_proj_type": "std",
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+  "galore_with_embedding": false,
+  "galore_quantization": false,
+  "galore_proj_quant": false,
+  "galore_proj_bits": 4,
+  "galore_proj_group_size": 256,
+  "galore_cos_threshold": 0.4,
+  "galore_gamma_proj": 2,
+  "galore_queue_size": 5,
+  "adalora_target_r": 8,
+  "adalora_init_r": 12,
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+  "adalora_tfinal": 0,
+  "adalora_deltaT": 1,
+  "adalora_beta1": 0.85,
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+  "neftune_backend": "transformers",
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+  "lisa_step_interval": 20,
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+  "reft_layers": null,
+  "reft_rank": 4,
+  "reft_intervention_type": "LoreftIntervention",
+  "reft_args": null,
+  "use_liger": false,
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+  "auto_find_batch_size": false,
+  "num_train_epochs": 3,
+  "max_steps": -1,
+  "optim": "adamw_torch",
+  "adam_beta1": 0.9,
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+  "adam_epsilon": 1e-08,
+  "learning_rate": 0.0002,
+  "weight_decay": 0.1,
+  "gradient_accumulation_steps": 1,
+  "max_grad_norm": 1,
+  "predict_with_generate": false,
+  "lr_scheduler_type": "cosine",
+  "lr_scheduler_kwargs": {},
+  "warmup_ratio": 0.05,
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+  "push_to_hub": false,
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+  "hub_private_repo": false,
+  "hub_strategy": "every_save",
+  "test_oom_error": false,
+  "disable_tqdm": false,
+  "lazy_tokenize": true,
+  "preprocess_num_proc": 1,
+  "use_flash_attn": null,
+  "ignore_args_error": false,
+  "check_model_is_latest": true,
+  "logging_dir": "/mnt/petrelfs/caoyuhang/InternLM-XComposer/finetune_audio/output/sft-continue_base_silence/qwen2-audio-7b-instruct/v0-20241120-155458/runs",
+  "report_to": [
+    "tensorboard"
+  ],
+  "acc_strategy": "token",
+  "save_on_each_node": false,
+  "evaluation_strategy": "steps",
+  "save_strategy": "steps",
+  "save_safetensors": true,
+  "gpu_memory_fraction": null,
+  "include_num_input_tokens_seen": false,
+  "local_repo_path": null,
+  "custom_register_path": null,
+  "custom_dataset_info": null,
+  "device_map_config": null,
+  "device_max_memory": [],
+  "max_new_tokens": 2048,
+  "do_sample": null,
+  "temperature": null,
+  "top_k": null,
+  "top_p": null,
+  "repetition_penalty": null,
+  "num_beams": 1,
+  "fsdp": "",
+  "fsdp_config": null,
+  "sequence_parallel_size": 1,
+  "model_layer_cls_name": null,
+  "metric_warmup_step": 0,
+  "fsdp_num": 1,
+  "per_device_train_batch_size": null,
+  "per_device_eval_batch_size": null,
+  "eval_strategy": null,
+  "self_cognition_sample": 0,
+  "train_dataset_mix_ratio": 0.0,
+  "train_dataset_mix_ds": [
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+  "val_dataset_sample": null,
+  "safe_serialization": null,
+  "only_save_model": null,
+  "neftune_alpha": null,
+  "deepspeed_config_path": null,
+  "model_cache_dir": null,
+  "lora_dropout_p": null,
+  "lora_target_modules": [],
+  "lora_target_regex": null,
+  "lora_modules_to_save": [],
+  "boft_target_modules": [],
+  "boft_modules_to_save": [],
+  "vera_target_modules": [],
+  "vera_modules_to_save": [],
+  "ia3_target_modules": [],
+  "ia3_modules_to_save": [],
+  "custom_train_dataset_path": [],
+  "custom_val_dataset_path": [],
+  "device_map_config_path": null,
+  "push_hub_strategy": null,
+  "use_self_cognition": false,
+  "is_multimodal": true,
+  "is_vision": false,
+  "lora_use_embedding": false,
+  "lora_use_all": false,
+  "lora_m2s_use_embedding": false,
+  "lora_m2s_use_ln": false,
+  "torch_dtype": "torch.bfloat16",
+  "fp16": false,
+  "bf16": true,
+  "rank": 0,
+  "local_rank": 0,
+  "world_size": 8,
+  "local_world_size": 8,
+  "bnb_4bit_compute_dtype": "torch.bfloat16",
+  "load_in_4bit": false,
+  "load_in_8bit": false,
+  "train_sampler_random": true,
+  "train_type": "sft",
+  "training_args": "Seq2SeqTrainingArguments(output_dir='/mnt/petrelfs/caoyuhang/InternLM-XComposer/finetune_audio/output/sft-continue_base_silence/qwen2-audio-7b-instruct/v0-20241120-155458', overwrite_output_dir=False, do_train=False, do_eval=True, do_predict=False, eval_strategy=<IntervalStrategy.STEPS: 'steps'>, prediction_loss_only=False, per_device_train_batch_size=16, per_device_eval_batch_size=16, per_gpu_train_batch_size=None, per_gpu_eval_batch_size=None, gradient_accumulation_steps=1, eval_accumulation_steps=None, eval_delay=0, torch_empty_cache_steps=None, learning_rate=0.0002, weight_decay=0.1, adam_beta1=0.9, adam_beta2=0.95, adam_epsilon=1e-08, max_grad_norm=1, num_train_epochs=3, max_steps=-1, lr_scheduler_type=<SchedulerType.COSINE: 'cosine'>, lr_scheduler_kwargs={}, warmup_ratio=0.05, warmup_steps=0, log_level='passive', log_level_replica='warning', log_on_each_node=True, logging_dir='/mnt/petrelfs/caoyuhang/InternLM-XComposer/finetune_audio/output/sft-continue_base_silence/qwen2-audio-7b-instruct/v0-20241120-155458/runs', logging_strategy=<IntervalStrategy.STEPS: 'steps'>, logging_first_step=True, logging_steps=20, logging_nan_inf_filter=True, save_strategy=<IntervalStrategy.STEPS: 'steps'>, save_steps=2000, save_total_limit=2, save_safetensors=True, save_on_each_node=False, save_only_model=False, restore_callback_states_from_checkpoint=False, no_cuda=False, use_cpu=False, use_mps_device=False, seed=42, data_seed=42, jit_mode_eval=False, use_ipex=False, bf16=True, fp16=False, fp16_opt_level='O1', half_precision_backend='auto', bf16_full_eval=False, fp16_full_eval=False, tf32=None, local_rank=0, ddp_backend='nccl', tpu_num_cores=None, tpu_metrics_debug=False, debug=[], dataloader_drop_last=False, eval_steps=2000, dataloader_num_workers=4, dataloader_prefetch_factor=None, past_index=-1, run_name='/mnt/petrelfs/caoyuhang/InternLM-XComposer/finetune_audio/output/sft-continue_base_silence/qwen2-audio-7b-instruct/v0-20241120-155458', disable_tqdm=False, remove_unused_columns=False, label_names=None, load_best_model_at_end=False, metric_for_best_model='loss', greater_is_better=False, ignore_data_skip=False, fsdp=[], fsdp_min_num_params=0, fsdp_config={'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, fsdp_transformer_layer_cls_to_wrap=None, accelerator_config=AcceleratorConfig(split_batches=False, dispatch_batches=False, even_batches=True, use_seedable_sampler=True, non_blocking=False, gradient_accumulation_kwargs=None, use_configured_state=False), deepspeed=None, label_smoothing_factor=0.0, optim=<OptimizerNames.ADAMW_TORCH: 'adamw_torch'>, optim_args=None, adafactor=False, group_by_length=False, length_column_name='length', report_to=['tensorboard'], ddp_find_unused_parameters=False, ddp_bucket_cap_mb=None, ddp_broadcast_buffers=False, dataloader_pin_memory=True, dataloader_persistent_workers=False, skip_memory_metrics=True, use_legacy_prediction_loop=False, push_to_hub=False, resume_from_checkpoint=None, hub_model_id=None, hub_strategy=<HubStrategy.EVERY_SAVE: 'every_save'>, hub_token=None, hub_private_repo=False, hub_always_push=False, gradient_checkpointing=True, gradient_checkpointing_kwargs=None, include_inputs_for_metrics=False, eval_do_concat_batches=True, fp16_backend='auto', evaluation_strategy=None, push_to_hub_model_id=None, push_to_hub_organization=None, push_to_hub_token=None, mp_parameters='', auto_find_batch_size=False, full_determinism=False, torchdynamo=None, ray_scope='last', ddp_timeout=1800, torch_compile=False, torch_compile_backend=None, torch_compile_mode=None, dispatch_batches=None, split_batches=None, include_tokens_per_second=False, include_num_input_tokens_seen=False, neftune_noise_alpha=None, optim_target_modules=None, batch_eval_metrics=False, eval_on_start=False, use_liger_kernel=False, eval_use_gather_object=False, sortish_sampler=False, predict_with_generate=False, generation_max_length=None, generation_num_beams=None, generation_config=GenerationConfig {\n  \"bos_token_id\": 151643,\n  \"eos_token_id\": 151645,\n  \"max_new_tokens\": 2048,\n  \"pad_token_id\": 151643\n}\n, acc_strategy='token', loss_name=None, additional_saved_files=[], train_sampler_random=True, metric_warmup_step=0, train_dataset_sample=-1)"
+}
\ No newline at end of file
diff --git a/audio/special_tokens_map.json b/audio/special_tokens_map.json
new file mode 100644
index 0000000000000000000000000000000000000000..527f1ea6a6b58598c75c8d2ea50ba17f8c45ebb9
--- /dev/null
+++ b/audio/special_tokens_map.json
@@ -0,0 +1,3305 @@
+{
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+    "<|im_start|>",
+    "<|im_end|>",
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+    "<|midi_pitch_123|>",
+    "<|midi_pitch_124|>",
+    "<|midi_pitch_125|>",
+    "<|midi_pitch_126|>",
+    "<|midi_pitch_127|>",
+    "<|midi_velocity_0|>",
+    "<|midi_velocity_1|>",
+    "<|midi_velocity_2|>",
+    "<|midi_velocity_3|>",
+    "<|midi_velocity_4|>",
+    "<|midi_velocity_5|>",
+    "<|midi_velocity_6|>",
+    "<|midi_velocity_7|>",
+    "<|midi_velocity_8|>",
+    "<|midi_velocity_9|>",
+    "<|midi_velocity_10|>",
+    "<|midi_velocity_11|>",
+    "<|midi_velocity_12|>",
+    "<|midi_velocity_13|>",
+    "<|midi_velocity_14|>",
+    "<|midi_velocity_15|>",
+    "<|midi_velocity_16|>",
+    "<|midi_velocity_17|>",
+    "<|midi_velocity_18|>",
+    "<|midi_velocity_19|>",
+    "<|midi_velocity_20|>",
+    "<|midi_velocity_21|>",
+    "<|midi_velocity_22|>",
+    "<|midi_velocity_23|>",
+    "<|midi_velocity_24|>",
+    "<|midi_velocity_25|>",
+    "<|midi_velocity_26|>",
+    "<|midi_velocity_27|>",
+    "<|midi_velocity_28|>",
+    "<|midi_velocity_29|>",
+    "<|midi_velocity_30|>",
+    "<|midi_velocity_31|>",
+    "<|midi_velocity_32|>",
+    "<|midi_velocity_33|>",
+    "<|midi_velocity_34|>",
+    "<|midi_velocity_35|>",
+    "<|midi_velocity_36|>",
+    "<|midi_velocity_37|>",
+    "<|midi_velocity_38|>",
+    "<|midi_velocity_39|>",
+    "<|midi_velocity_40|>",
+    "<|midi_velocity_41|>",
+    "<|midi_velocity_42|>",
+    "<|midi_velocity_43|>",
+    "<|midi_velocity_44|>",
+    "<|midi_velocity_45|>",
+    "<|midi_velocity_46|>",
+    "<|midi_velocity_47|>",
+    "<|midi_velocity_48|>",
+    "<|midi_velocity_49|>",
+    "<|midi_velocity_50|>",
+    "<|midi_velocity_51|>",
+    "<|midi_velocity_52|>",
+    "<|midi_velocity_53|>",
+    "<|midi_velocity_54|>",
+    "<|midi_velocity_55|>",
+    "<|midi_velocity_56|>",
+    "<|midi_velocity_57|>",
+    "<|midi_velocity_58|>",
+    "<|midi_velocity_59|>",
+    "<|midi_velocity_60|>",
+    "<|midi_velocity_61|>",
+    "<|midi_velocity_62|>",
+    "<|midi_velocity_63|>",
+    "<|midi_velocity_64|>",
+    "<|midi_velocity_65|>",
+    "<|midi_velocity_66|>",
+    "<|midi_velocity_67|>",
+    "<|midi_velocity_68|>",
+    "<|midi_velocity_69|>",
+    "<|midi_velocity_70|>",
+    "<|midi_velocity_71|>",
+    "<|midi_velocity_72|>",
+    "<|midi_velocity_73|>",
+    "<|midi_velocity_74|>",
+    "<|midi_velocity_75|>",
+    "<|midi_velocity_76|>",
+    "<|midi_velocity_77|>",
+    "<|midi_velocity_78|>",
+    "<|midi_velocity_79|>",
+    "<|midi_velocity_80|>",
+    "<|midi_velocity_81|>",
+    "<|midi_velocity_82|>",
+    "<|midi_velocity_83|>",
+    "<|midi_velocity_84|>",
+    "<|midi_velocity_85|>",
+    "<|midi_velocity_86|>",
+    "<|midi_velocity_87|>",
+    "<|midi_velocity_88|>",
+    "<|midi_velocity_89|>",
+    "<|midi_velocity_90|>",
+    "<|midi_velocity_91|>",
+    "<|midi_velocity_92|>",
+    "<|midi_velocity_93|>",
+    "<|midi_velocity_94|>",
+    "<|midi_velocity_95|>",
+    "<|midi_velocity_96|>",
+    "<|midi_velocity_97|>",
+    "<|midi_velocity_98|>",
+    "<|midi_velocity_99|>",
+    "<|midi_velocity_100|>",
+    "<|midi_velocity_101|>",
+    "<|midi_velocity_102|>",
+    "<|midi_velocity_103|>",
+    "<|midi_velocity_104|>",
+    "<|midi_velocity_105|>",
+    "<|midi_velocity_106|>",
+    "<|midi_velocity_107|>",
+    "<|midi_velocity_108|>",
+    "<|midi_velocity_109|>",
+    "<|midi_velocity_110|>",
+    "<|midi_velocity_111|>",
+    "<|midi_velocity_112|>",
+    "<|midi_velocity_113|>",
+    "<|midi_velocity_114|>",
+    "<|midi_velocity_115|>",
+    "<|midi_velocity_116|>",
+    "<|midi_velocity_117|>",
+    "<|midi_velocity_118|>",
+    "<|midi_velocity_119|>",
+    "<|midi_velocity_120|>",
+    "<|midi_velocity_121|>",
+    "<|midi_velocity_122|>",
+    "<|midi_velocity_123|>",
+    "<|midi_velocity_124|>",
+    "<|midi_velocity_125|>",
+    "<|midi_velocity_126|>",
+    "<|midi_velocity_127|>",
+    "<|unknown|>",
+    "<|zh_tw|>",
+    "<|en|>",
+    "<|zh|>",
+    "<|de|>",
+    "<|es|>",
+    "<|ko|>",
+    "<|fr|>",
+    "<|ja|>",
+    "<|it|>",
+    "<|ru|>",
+    "<|pt|>",
+    "<|ar|>",
+    "<|yue|>",
+    "<|wuu|>",
+    "<|nan|>"
+  ],
+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}
diff --git a/audio/tokenizer.json b/audio/tokenizer.json
new file mode 100644
index 0000000000000000000000000000000000000000..895d4d6edeb018b3617b06d14fe3cc3148ba8393
--- /dev/null
+++ b/audio/tokenizer.json
@@ -0,0 +1,332677 @@
+{
+  "version": "1.0",
+  "truncation": null,
+  "padding": null,
+  "added_tokens": [
+    {
+      "id": 151643,
+      "content": "<|endoftext|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151644,
+      "content": "<|im_start|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151645,
+      "content": "<|im_end|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151646,
+      "content": "<|AUDIO|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151647,
+      "content": "<|audio_bos|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151648,
+      "content": "<|audio_eos|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151649,
+      "content": "<|sil|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151650,
+      "content": "<|0.00|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151651,
+      "content": "<|0.01|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151652,
+      "content": "<|0.02|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151653,
+      "content": "<|0.03|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151654,
+      "content": "<|0.04|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151655,
+      "content": "<|0.05|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151656,
+      "content": "<|0.06|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151657,
+      "content": "<|0.07|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151658,
+      "content": "<|0.08|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151659,
+      "content": "<|0.09|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151660,
+      "content": "<|0.10|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151661,
+      "content": "<|0.11|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151662,
+      "content": "<|0.12|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151663,
+      "content": "<|0.13|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151664,
+      "content": "<|0.14|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151665,
+      "content": "<|0.15|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151666,
+      "content": "<|0.16|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151667,
+      "content": "<|0.17|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151668,
+      "content": "<|0.18|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151669,
+      "content": "<|0.19|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151670,
+      "content": "<|0.20|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151671,
+      "content": "<|0.21|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151672,
+      "content": "<|0.22|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151673,
+      "content": "<|0.23|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151674,
+      "content": "<|0.24|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151675,
+      "content": "<|0.25|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151676,
+      "content": "<|0.26|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151677,
+      "content": "<|0.27|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151678,
+      "content": "<|0.28|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151679,
+      "content": "<|0.29|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151680,
+      "content": "<|0.30|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151681,
+      "content": "<|0.31|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151682,
+      "content": "<|0.32|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151683,
+      "content": "<|0.33|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151684,
+      "content": "<|0.34|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151685,
+      "content": "<|0.35|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151686,
+      "content": "<|0.36|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151687,
+      "content": "<|0.37|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151688,
+      "content": "<|0.38|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151689,
+      "content": "<|0.39|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151690,
+      "content": "<|0.40|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151691,
+      "content": "<|0.41|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151692,
+      "content": "<|0.42|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151693,
+      "content": "<|0.43|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151694,
+      "content": "<|0.44|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151695,
+      "content": "<|0.45|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151696,
+      "content": "<|0.46|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151697,
+      "content": "<|0.47|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 151698,
+      "content": "<|0.48|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
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+      "content": "<|0.49|>",
+      "single_word": false,
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+      "normalized": false,
+      "special": true
+    },
+    {
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+      "content": "<|0.50|>",
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+      "normalized": false,
+      "special": true
+    },
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+      "content": "<|0.51|>",
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+      "special": true
+    },
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+      "special": true
+    },
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+    },
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+      "special": true
+    },
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+      "special": true
+    },
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+    },
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+    },
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+    },
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+    },
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+    },
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+      "çŀ Ń",
+      "æķ ŀ",
+      "ä¹ ĸ",
+      "éŁ §",
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+      "ä ²",
+      "ð« Ķ",
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+      "åĦ¿ åŃIJ",
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+      "åħ· å¤ĩ",
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+      "足 çIJĥ",
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+      "女 åĦ¿",
+      "èĪ ¶",
+      "çµ ¦",
+      "ä¼ļ åijĺ",
+      "æĪĸ 许",
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+      "举 æĸ¹",
+      "天 津",
+      "è¿ij å¹´",
+      "çľĭ æĿ¥",
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+      "æĢĿ ç»´",
+      "æĭħ å¿ĥ",
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+      "æľº åľº",
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+      "ç§ij çłĶ",
+      "å¤į æĿĤ",
+      "æľº åĻ¨",
+      "çĪ± æĥħ",
+      "çħ§ çīĩ",
+      "å¹´ é¾Ħ",
+      "è³ĩ æĸĻ",
+      "ç² Ĺ",
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+      "åĬł ä¸Ĭ",
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+      "è° IJ",
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+      "èĥĮ æĻ¯",
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+      "äºĭ 项",
+      "åĬ¨ ä½ľ",
+      "ç¥ ¥",
+      "æĢ» ä½ĵ",
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+      "大 æ¦Ĥ",
+      "é«ĺ æķĪ",
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+      "çķĻ ä¸ĭ",
+      "è¡£ æľį",
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+      "深 度",
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+      "æĪIJ çĨŁ",
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+      "çĽ ¾",
+      "好 好",
+      "第 åĽĽ",
+      "åĨł åĨĽ",
+      "è´¢ å¯Į",
+      "æľĢ 好çļĦ",
+      "车 åŀĭ",
+      "éĸ Ģ",
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+      "éĿĴ å²Ľ",
+      "纷 纷",
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+      "å¹³ è¡¡",
+      "å¹³æĸ¹ ç±³",
+      "éĤ£ ç§į",
+      "åĩº çĶŁ",
+      "éĿĴ æĺ¥",
+      "人 群",
+      "人 工",
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+      "åľ¨ æѤ",
+      "åįļ 士",
+      "æŶ åĪ»",
+      "æ²³ åĮĹ",
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+      "éĢļ éģĵ",
+      "森 æŀĹ",
+      "çĸ Ĩ",
+      "æķ ¸",
+      "èĬ ³",
+      "æīĵ åĩ»",
+      "æĽ ¹",
+      "åĮĸ åѦ",
+      "æĥ³ 象",
+      "ä¸ĩ 人",
+      "è´¢ ç»ı",
+      "åħĥ ç´ł",
+      "ä¼ļ 计",
+      "åħ¨ ä½ĵ",
+      "æĦ Ľ",
+      "é«ĺ ä¸Ń",
+      "æľº éģĩ",
+      "声 éŁ³",
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+      "æµ ©",
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+      "åĽ½ å¤ĸ",
+      "èijĹ åIJį",
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+      "å§ ľ",
+      "带 é¢Ĩ",
+      "é¢ľ èī²",
+      "ä¸Ĭ ä¸ĭ",
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+      "ä¸Ģ åıª",
+      "çIJ ´",
+      "梦 æĥ³",
+      "秣 èµģ",
+      "å¼Ģ åIJ¯",
+      "è´Ń çī©",
+      "åĮħ åIJ«",
+      "åĪ© çİĩ",
+      "èµ· äºĨ",
+      "æľī åĬĽ",
+      "éĤ£ éĩĮ",
+      "审 æī¹",
+      "对 æīĭ",
+      "çİ° éĩij",
+      "天 çĦ¶",
+      "çĽ Ĵ",
+      "çĪ ½",
+      "å¿ħ çĦ¶",
+      "åĮĸ å·¥",
+      "ä¸ĵ åĪ©",
+      "åķ ¡",
+      "å¼Ģ å¿ĥ",
+      "人 ä½ĵ",
+      "éģĵ 士",
+      "æĢģ 度",
+      "空 è°ĥ",
+      "æĭĽ åķĨ",
+      "å§ »",
+      "第 äºĶ",
+      "æ£ Ĵ",
+      "ä¸Ģ ç³»åĪĹ",
+      "åį± æľº",
+      "转 åıĺ",
+      "åľº æīĢ",
+      "é¸ £",
+      "æĪ¿ éĹ´",
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+      "对 å¤ĸ",
+      "åĩº åı°",
+      "åľ¨ è¿Ļ",
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+      "第 ä¸Ģ个",
+      "è´µ å·ŀ",
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+      "æľ¬ æĿ¥",
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+      "éĻ ¶",
+      "ä¸Ģ è·¯",
+      "èĤ ĸ",
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+      "æľī æľº",
+      "åIJį åįķ",
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+      "åij¼ åIJ¸",
+      "ä¸ Ī",
+      "ç¦ı 建",
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+      "å¼ķ åıij",
+      "ä¹Ł 没",
+      "ä¸į ä½ı",
+      "çĨŁ æĤī",
+      "èIJ ¬",
+      "ä¸į èī¯",
+      "çł ĸ",
+      "èĩ´ åĬĽ",
+      "çŃ¾ 订",
+      "åIJ Ĭ",
+      "ä¾ ¯",
+      "çĺ ¦",
+      "å§ij å¨ĺ",
+      "æĸ ¤",
+      "妻 åŃIJ",
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+      "çĪ ¬",
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+      "éħ ·",
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+      "ä»Ģ 麼",
+      "认 åı¯",
+      "åĪĨ åŃIJ",
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+      "å¼ ·",
+      "马 ä¸Ĭ",
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+      "å®ī å¾½",
+      "ç¥ŀ ç»ı",
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+      "åįı åIJĮ",
+      "æµģ åĬ¨",
+      "åıij åĬ¨",
+      "åĿļ å®ļ",
+      "表 æĺİ",
+      "åIJİ éĿ¢",
+      "ä¹ī åĬ¡",
+      "å¦ ĸ",
+      "æľī åı¯èĥ½",
+      "年轻 人",
+      "大 éĻĨ",
+      "å² ³",
+      "ä¸į èµ·",
+      "çŀ¬ éĹ´",
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+      "çŃ¾ 约",
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+      "便 åĪ©",
+      "éļı æŶ",
+      "å¥ ī",
+      "称 为",
+      "产 æĿĥ",
+      "åIJ ķ",
+      "çĽ Ĩ",
+      "课 åłĤ",
+      "ç· ļ",
+      "æ£ ī",
+      "线 ä¸ĭ",
+      "èĩª è¡Į",
+      "举 æݪ",
+      "åݦ éŨ",
+      "èĩª ä¿¡",
+      "å½± è§Ĩ",
+      "ä» Ķ",
+      "çĶŁæ´» ä¸Ń",
+      "æĿĥ çĽĬ",
+      "çĻ½ èī²",
+      "å°± ä¸į",
+      "è¿Ľ å±ķ",
+      "æ¯ı æĹ¥",
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+      "çIJĨ è´¢",
+      "ä¾Ŀ æŧ",
+      "ä¸Ĭ åįĪ",
+      "è¯Ĩ åĪ«",
+      "çĽĪ åĪ©",
+      "çł Ĥ",
+      "许 åı¯",
+      "åIJĮ äºĭ",
+      "åĺ Ľ",
+      "éģ ¸",
+      "çĿĢ åĬĽ",
+      "éŨ åı£",
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+      "åħ¶ 次",
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+      "çī© çIJĨ",
+      "åĨħ å¿ĥ",
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+      "æĢ» 绣",
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+      "积 累",
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+      "æłij ç«ĭ",
+      "社 交",
+      "ç§ ©",
+      "åįģ ä¸Ģ",
+      "éĤ ĵ",
+      "驱 åĬ¨",
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+      "èĬ¯ çīĩ",
+      "è¦ģ ç´ł",
+      "åıį 对",
+      "çİĩ åħĪ",
+      "è´§ çī©",
+      "æĹ¥ çĶµ",
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+      "æĪIJ åĪĨ",
+      "åĽł èĢĮ",
+      "åĩı èĤ¥",
+      "æ½ ĺ",
+      "å±±ä¸ľ çľģ",
+      "åĬ Ŀ",
+      "åŁ ĭ",
+      "æѦ è£ħ",
+      "æ±ĩ æĬ¥",
+      "ä¸Ģ个 æľĪ",
+      "çĥŃ éŨ",
+      "大 éģĵ",
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+      "éĥ½ å¾Ī",
+      "çĶµ 梯",
+      "ç´§ æĢ¥",
+      "åĢº åĬ¡",
+      "客 æľį",
+      "ä¸Ģ éĥ¨",
+      "ä½ł æĺ¯",
+      "çİ° çĬ¶",
+      "æŃ£ç¡® çļĦ",
+      "ä¹ĭ å¤Ħ",
+      "ç¼ĸ åĪ¶",
+      "ä½ł åı¯ä»¥",
+      "çŃī åľ°",
+      "èİ ī",
+      "对 è¯Ŀ",
+      "æ·ĺ å®Ŀ",
+      "è°ĥ èĬĤ",
+      "æİĴ æĶ¾",
+      "åºĵ åŃĺ",
+      "ç´ ļ",
+      "çļĦ ä¼ĺåĬ¿",
+      "æĿĥ å¨ģ",
+      "以ä¸ĭ ç®Ģ称",
+      "ä¸Ģ 项",
+      "èģļ éĽĨ",
+      "ä¼łç»Ł çļĦ",
+      "æ·· åIJĪ",
+      "è¿Ļä¸Ģ çĤ¹",
+      "ä¸Ģ çľ¼",
+      "æĹł éĻIJ",
+      "èİ·å¾Ĺ äºĨ",
+      "éĢī æīĭ",
+      "åĪ¶ åĵģ",
+      "åįı ä½ľ",
+      "çĭ¬çī¹ çļĦ",
+      "ä¸Ģ 级",
+      "è¿Ļ个 éĹ®é¢ĺ",
+      "æĸ Į",
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+      "æķĮ 人",
+      "æ¸ħ æ´Ĺ",
+      "ä¸Ģ缴 åľ¨",
+      "å°ı ç±³",
+      "çļĦ è¿ĩç¨ĭ",
+      "åľ¨ åĮĹ京",
+      "ä¸Ģ æĶ¯",
+      "æĹ© ä¸Ĭ",
+      "æĸĩ èīº",
+      "ç¦ı åĪ©",
+      "é£Ł çĶ¨",
+      "æĦŁ åĬ¨",
+      "åħ¨ ç¨ĭ",
+      "æĶ¯ åĩº",
+      "æĸ° 建",
+      "å¸ ķ",
+      "æĺ¾ çĦ¶",
+      "羣 çļĦæĺ¯",
+      "æĸ°éĹ» ç½ij",
+      "èĥ½ åIJ¦",
+      "åįı åĬ©",
+      "亲 èĩª",
+      "å¾Ī æľī",
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+      "æĦı 大",
+      "æĦı大 åĪ©",
+      "çĶµ ç½ij",
+      "æĹ¥ çĽĬ",
+      "çĨ ±",
+      "èĤĮ èĤ¤",
+      "çĶ· æĢ§",
+      "ç»Ħ 建",
+      "çŃī éĹ®é¢ĺ",
+      "æ¶Ī éĻ¤",
+      "æĬ¤ çIJĨ",
+      "å¡ij æĸĻ",
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+      "ä¹Įåħĭ åħ°",
+      "åķĨ æłĩ",
+      "çIJ ³",
+      "æĸ° æīĭ",
+      "çļĦ çī¹çĤ¹",
+      "åĴ ¬",
+      "å½ĵ ä¸ĭ",
+      "设计 å¸Ī",
+      "èµĶ åģ¿",
+      "第 åįģ",
+      "æĻºèĥ½ åĮĸ",
+      "å¼Ģåıij åĮº",
+      "åı¯ä»¥ éĢļè¿ĩ",
+      "åħ±äº§ åħļ",
+      "åİī 害",
+      "çģµ æ´»",
+      "æŶ åħī",
+      "éĥ¨ ä½į",
+      "人 æĸĩ",
+      "è¿Ľ æĿ¥",
+      "ä¹ĭ æīĢ以",
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+      "éĺ² æĬ¤",
+      "åĽ½ 产",
+      "æ·±åľ³ å¸Ĥ",
+      "éĤ£ å°±æĺ¯",
+      "åĪ° ä½į",
+      "çī¹ æľĹ",
+      "çī¹æľĹ æĻ®",
+      "å®ŀ æŶ",
+      "åı° çģ£",
+      "èĢĮ ä¸į",
+      "æĮĩ å®ļ",
+      "åĿ Ŀ",
+      "èħIJ è´¥",
+      "çī¹ å®ļ",
+      "å¢ŀ éĢŁ",
+      "æłĩ çŃ¾",
+      "æĪ¿ ä»·",
+      "æĦ ģ",
+      "贯彻 èIJ½å®ŀ",
+      "æĢ§ è´¨",
+      "çłĶ究 çĶŁ",
+      "ç¾İ 容",
+      "æī¹ è¯Ħ",
+      "究 竣",
+      "人åĬĽ èµĦæºIJ",
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+      "åĽŀ å½Ĵ",
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+      "æłĩåĩĨ åĮĸ",
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+      "åĭ ¾",
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+      "ç®Ģåįķ çļĦ",
+      "å¤į åĪ¶",
+      "æ¸IJ æ¸IJ",
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+      "èģĶ åĬ¨",
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+      "æĢ§ åĴĮ",
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+      "çļĦ åIJįåŃĹ",
+      "éŁ ¦",
+      "ä½ł è¦ģ",
+      "å¢ĥ å¤ĸ",
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+      "åĪĿ æŃ¥",
+      "è´¦ åı·",
+      "害 æĢķ",
+      "æĺ¨ æĹ¥",
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+      "ç¥ŀ ç§ĺ",
+      "ç²¾ å¿ĥ",
+      "æµģ éĢļ",
+      "åħ¨ æĸ¹ä½į",
+      "以 å¾Ģ",
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+      "æĺ¯ ä¸ŃåĽ½",
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+      "å°Ĩ åĨĽ",
+      "æij Ĭ",
+      "æľĢ 为",
+      "第ä¸Ģ æŶéĹ´",
+      "æ¶Ī æ¯Ĵ",
+      "å°Ĩ äºİ",
+      "å¨ģ èĥģ",
+      "èĭ± æĸĩ",
+      "æīĭ ä¸Ń",
+      "çIJĥ è¿·",
+      "è§Ĥ çľĭ",
+      "离 å©ļ",
+      "æľ¬ åľŁ",
+      "åĪĨ æķ£",
+      "æĻ ´",
+      "è¦ģ 注æĦı",
+      "浪 费",
+      "管 æݧ",
+      "åĩº åĶ®",
+      "æĢ» è£ģ",
+      "ä¸Ģ éĺµ",
+      "å¨ ĩ",
+      "äºĶ 个",
+      "å½ĵ åĪĿ",
+      "çºł 纷",
+      "ä¸ĵ çĶ¨",
+      "å¤ĩ æ¡Ī",
+      "åĪĿ æľŁ",
+      "å®ĥ æĺ¯",
+      "åĮº åĿĹ",
+      "åĮºåĿĹ éĵ¾",
+      "大 è¿ŀ",
+      "è¿Ļ ç±»",
+      "åıĺ æĪIJäºĨ",
+      "éĤĦ æĺ¯",
+      "åįļ 客",
+      "çı¾ åľ¨",
+      "ä¸Ģ æĸ¹",
+      "å®ĮæĪIJ äºĨ",
+      "è¿Ļ个 æŶåĢĻ",
+      "åħ¨ å¹´",
+      "ä¸Ĭ 线",
+      "ç½ IJ",
+      "ç«ŀ èµĽ",
+      "åĩºçīĪ 社",
+      "åĵ¥ åĵ¥",
+      "å¯ «",
+      "å¾Ĺ 以",
+      "èĬ± åĽŃ",
+      "äºĨ èµ·æĿ¥",
+      "èĦ±è´« æĶ»åĿļ",
+      "çļĦ åİŁåĪĻ",
+      "讲 解",
+      "æ¶Ī åĮĸ",
+      "æįŁ 害",
+      "æļĤ æŶ",
+      "å¾Ĺ çŁ¥",
+      "éĢĤ çĶ¨",
+      "éŨ åºĹ",
+      "解 读",
+      "æĻ® åıĬ",
+      "人æ°ij æ³ķéĻ¢",
+      "åī¯ 主任",
+      "å¿ĥ çģµ",
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+      "è¯ī 讼",
+      "æĶ¾ æĿ¾",
+      "çªĹ åı£",
+      "ä¼ģ æ¥Ń",
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+      "åĬłæĭ¿ 大",
+      "ä¹° äºĨ",
+      "主 æµģ",
+      "æĩĤ å¾Ĺ",
+      "å°Ĩ åħ¶",
+      "éĢı æĺİ",
+      "å·¥ä½ľ ä¸Ń",
+      "èĤ¡ ä»·",
+      "æ¡£ æ¡Ī",
+      "没æľī ä»»ä½ķ",
+      "åijĬ çŁ¥",
+      "å¹´ åĪĿ",
+      "æĹ¥ ä¸ĭåįĪ",
+      "åİĤ åķĨ",
+      "èĬĤ å¥ı",
+      "主 导",
+      "è£ Ŀ",
+      "åħ³éĶ® è¯į",
+      "èģĬ 天",
+      "åĨĻ ä½ľ",
+      "æĶ¹éĿ© å¼ĢæĶ¾",
+      "æľī æľĽ",
+      "éĢļ æĬ¥",
+      "èIJ Į",
+      "æĢ» é¢Ŀ",
+      "çŁŃ æľŁ",
+      "ä¸Ģ çķª",
+      "çĶŁæ´» çļĦ",
+      "åĮĸ çļĦ",
+      "æĺ¥ å¤©",
+      "è¿Ļ åľº",
+      "æĸ°å¼Ģ ä¼łå¥ĩ",
+      "æĺ¯ è¦ģ",
+      "å°ļ æľª",
+      "åıĺ æĽ´",
+      "ä¸Ģ åij¨",
+      "客 è§Ĥ",
+      "æĹ¥ èĩ³",
+      "é¹ °",
+      "çİ ²",
+      "å°Ĩ æĿ¥",
+      "客 人",
+      "åıĺ éĿ©",
+      "说 äºĨ",
+      "åİŁ çIJĨ",
+      "èģĮ åĬ¡",
+      "åıĪ æľī",
+      "ä¸Ģ åı¥è¯Ŀ",
+      "æĦŁ åıĹåĪ°",
+      "ç¬Ķ èĢħ",
+      "移 æ°ij",
+      "西 åįĹ",
+      "ä¹ĥ èĩ³",
+      "æŃ£ è§Ħ",
+      "åĪĿ ä¸Ń",
+      "çĬ ¬",
+      "å½ĵ äºĭ",
+      "å½ĵäºĭ 人",
+      "æĪij们 è¦ģ",
+      "åħ¥ åı£",
+      "éĤ£ æŶ",
+      "æľīéĻIJ 责任",
+      "å°ij 女",
+      "è¿Ļä¹Ī å¤ļ",
+      "åĪĨ åħ¬åı¸",
+      "å®ĩ å®Ļ",
+      "çļĦ éĢīæĭ©",
+      "å§IJ å§IJ",
+      "åıij èµ·",
+      "è» į",
+      "æĽ´å¥½ åľ°",
+      "éĻĨ ç»Ń",
+      "æľ¬ æľįåĭĻ",
+      "å« ©",
+      "赶 紧",
+      "èĦĤ èĤª",
+      "第äºĮ 天",
+      "æĪij ä¼ļ",
+      "两 ä½į",
+      "æķ ²",
+      "åħ¬å®ī æľºåħ³",
+      "ç§ijæĬĢ åĪĽæĸ°",
+      "尺 寸",
+      "è¾IJ å°Ħ",
+      "å®Ĺ æķĻ",
+      "转 æį¢",
+      "åĩº çİ°åľ¨",
+      "ä¸Ģ é¢Ĺ",
+      "æľŁ éĻIJ",
+      "åIJĮåѦ 们",
+      "åĮĹ æĸ¹",
+      "ä½ł å°±",
+      "ä¸Ģ带 ä¸Ģè·¯",
+      "èĢģ å©Ĩ",
+      "游æĪı çݩ家",
+      "çļĦ ç»ĵæŀľ",
+      "è¡¥ åģ¿",
+      "å¤ĸ è´¸",
+      "对 å¾ħ",
+      "ç»´ çĶŁç´ł",
+      "ç»ıéĶĢ åķĨ",
+      "è¿ĺ å°Ĩ",
+      "åŃIJ 女",
+      "æĽ´ é«ĺ",
+      "ä¸į 大",
+      "éī´ å®ļ",
+      "让 ä»ĸ们",
+      "æīĢè°ĵ çļĦ",
+      "æŃ» äºĨ",
+      "帮 æī¶",
+      "åĵ² åѦ",
+      "以ä¸Ĭ çļĦ",
+      "çļĦ åħ³éĶ®",
+      "æĹ© å°±",
+      "æĬ¥ ä»·",
+      "éģµ å®Ī",
+      "æī© å¼ł",
+      "æĺ¯ å¾Ī",
+      "å¼Ģ éĢļ",
+      "æĸ° åĬł",
+      "æĸ°åĬł åĿ¡",
+      "ç¿» è¯ij",
+      "询 éĹ®",
+      "é¸ Ń",
+      "ä½ĵ åĨħ",
+      "两 个人",
+      "çĪ ¹",
+      "éľ ľ",
+      "乡æĿij æĮ¯åħ´",
+      "çĿ¡ è§ī",
+      "å®ĺ åijĺ",
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+      "åį³ 便",
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+      "ä¼ģä¸ļ 家",
+      "æ¸ £",
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+      "èģª æĺİ",
+      "è¿Ļ ä¹Ł",
+      "å½ķ åıĸ",
+      "åĨ² çªģ",
+      "åħ¨ 身",
+      "åŃ£ èĬĤ",
+      "忽 çĦ¶",
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+      "ä¸Ĭæµ· å¸Ĥ",
+      "æIJº æīĭ",
+      "çļĦ ä¿¡æģ¯",
+      "åķĨ åľº",
+      "çļĦ æĢĿæĥ³",
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+      "毫 æĹł",
+      "æĢĢ åŃķ",
+      "硬 件",
+      "åĨħ èĴĻåı¤",
+      "æİ¢ 讨",
+      "åħ» çĶŁ",
+      "çļĦ 表çİ°",
+      "空 ä¸Ń",
+      "æģIJ æĢĸ",
+      "å¾Ī é«ĺ",
+      "ç»ıæµİ 社ä¼ļ",
+      "ä¸Ĭ æĿ¥",
+      "延 ç»Ń",
+      "éĩį å¤į",
+      "éĺ² èĮĥ",
+      "çļĦ å½¢å¼ı",
+      "æľĪ åºķ",
+      "èĢģ 年人",
+      "绿 åĮĸ",
+      "å±± åĮº",
+      "æĭ¿ åĩº",
+      "æĹħ 客",
+      "æĽ´ æį¢",
+      "åħ¬ 主",
+      "èĬĤ 约",
+      "åħ¨ åİ¿",
+      "åĽŀ æĬ¥",
+      "çIJĨ æĢ§",
+      "çĸ¯ çĭĤ",
+      "æ¶ī å«Į",
+      "åī§ æĥħ",
+      "åĨ¬ åŃ£",
+      "åIJİ ç»Ń",
+      "è¿Ļæĺ¯ ä¸Ģ个",
+      "æ¼Ķ 讲",
+      "ä¸Ģ å±Ĥ",
+      "æľīåħ³ éĥ¨éŨ",
+      "æĹł å¥Ī",
+      "ç§į ç±»",
+      "缸åħ³ çļĦ",
+      "æĪĸèĢħ æĺ¯",
+      "æī¶ æĮģ",
+      "å¤ļ æķ°",
+      "çļĦ ä½ľåĵģ",
+      "ä¸ĭ ä¸ĢæŃ¥",
+      "å¸Ī åĤħ",
+      "é«ĺéĢŁ åħ¬è·¯",
+      "好 åıĭ",
+      "ä¼ĺç§Ģ çļĦ",
+      "è¿Ľ äºĨ",
+      "æģIJ æĢķ",
+      "äºĨ åIJ§",
+      "大 è§Ħ模",
+      "çļĦ ä¸ĸçķĮ",
+      "æĢĢ çĸij",
+      "å· ·",
+      "åħ´ å¥ĭ",
+      "æĪ °",
+      "æĿij éĩĮ",
+      "æľĭåıĭ åľĪ",
+      "åĨ¬ 天",
+      "ä¸Ńåįİ äººæ°ij",
+      "åįı åķĨ",
+      "è¯Ħ éĢī",
+      "æĹ Ń",
+      "å¢ŀåĬł äºĨ",
+      "åıĹ ä¼¤",
+      "ä¸Ģ èĤ¡",
+      "便 æį·",
+      "ä¸ ij",
+      "é¹ ¤",
+      "å¤ĸ è§Ĥ",
+      "å·¥ç¨ĭ å¸Ī",
+      "åĴĮ åħ¶ä»ĸ",
+      "è¿Ļ å°±",
+      "ä¸Ńå°ı ä¼ģä¸ļ",
+      "西 åĮĹ",
+      "åĽ½æľī ä¼ģä¸ļ",
+      "èĭ¥ æĺ¯",
+      "åı¯ æĥľ",
+      "çĶŁ æĹ¥",
+      "åĩ ½",
+      "ä¹° åįĸ",
+      "ç¥Ŀ ç¦ı",
+      "人æ°ij 群ä¼Ĺ",
+      "åħī æĺİ",
+      "åħ¬ å¯ĵ",
+      "æĺ¯ è°ģ",
+      "æĪij çŁ¥éģĵ",
+      "è¯Ń æĸĩ",
+      "æķı æĦŁ",
+      "ä¸įéĶĻ çļĦ",
+      "æĿ¥ 讲",
+      "æ³¢ åĬ¨",
+      "çļĦ 第ä¸Ģ",
+      "åľ° éľĩ",
+      "åľ¨ åħ¨åĽ½",
+      "骨 干",
+      "å®ī ç½®",
+      "家 çĶµ",
+      "ä¸İ æѤ",
+      "ä¸İæѤ åIJĮæŶ",
+      "åıĹ çģ¾",
+      "çĥŃ çº¿",
+      "çļĦ æĬĢæľ¯",
+      "æµĭ éĩı",
+      "ä¾Ŀ èµĸ",
+      "ä¸ŃåĽ½ çļĦ",
+      "çī¹ æĢ§",
+      "è¾ĥ é«ĺ",
+      "è¸ ©",
+      "ä¼ļ åľ¨",
+      "建 éĢł",
+      "导 èĪª",
+      "æĥ³ èµ·",
+      "åħ¨ ä¸ĸçķĮ",
+      "建 æĿIJ",
+      "ç¯ Ģ",
+      "çļĦ åŁºç¡Ģ",
+      "èĩªåĬ¨ åĮĸ",
+      "åīį åIJİ",
+      "çĿ¡ çľł",
+      "æݨ è¡Į",
+      "æį® äºĨ解",
+      "ä»Ģä¹Ī æŶåĢĻ",
+      "ä¸į åĸľæ¬¢",
+      "çħ¤ çĤŃ",
+      "éĤ£ä¹Ī å¤ļ",
+      "å¸Ĥåľº åĮĸ",
+      "ä¸į管 æĺ¯",
+      "ç«ĭ åľº",
+      "éĥ½ 没",
+      "课 é¢ĺ",
+      "æĪij们 å°Ĩ",
+      "è¿ĩ çļĦ",
+      "åĨį åĬłä¸Ĭ",
+      "çĪ ¾",
+      "身 æĿIJ",
+      "çĶ· 女",
+      "è¿ľ è¿ľ",
+      "çĶ· çĶŁ",
+      "èĩªèº« çļĦ",
+      "è´Ł æĭħ",
+      "çĻ¾ ä¸ĩ",
+      "西 çıŃ",
+      "西çıŃ çīĻ",
+      "åĩĢ åĪ©æ¶¦",
+      "澳 大",
+      "澳大 åĪ©äºļ",
+      "ä¸į åİ»",
+      "æī¿ åıĹ",
+      "楼 çĽĺ",
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+      "éĹľ ä¿Ĥ",
+      "çļĦ èĦ¸",
+      "æĥ Ł",
+      "ä¸į ä¸Ģå®ļ",
+      "ç¶ Ń",
+      "çģ« çĪĨ",
+      "秣 éĩij",
+      "çŀ §",
+      "éĩį 建",
+      "è· ª",
+      "ä¸Ģ 種",
+      "çļĦ åIJĪä½ľ",
+      "å®ī æħ°",
+      "ä»į æĺ¯",
+      "ä¸ĵä¸ļ åĮĸ",
+      "è°ĥ 解",
+      "ä¸į 妨",
+      "éĢĻ æĺ¯",
+      "å¿ħ éłĪ",
+      "ä¼Ĭ æľĹ",
+      "å¾Ĺ äºĨ",
+      "æľįåĬ¡ å¹³åı°",
+      "å§ ¬",
+      "åħĪ éĶĭ",
+      "çİĭ åŃIJ",
+      "çļĦä¸Ģ åĪĩ",
+      "æĢ» çIJĨ",
+      "åĵ ¼",
+      "çª ij",
+      "çļĦå¿ĥ æĥħ",
+      "çļĦ éĩį大",
+      "çij Ł",
+      "ä¸Ģ ç¬ij",
+      "åıijå±ķ ä¸Ń",
+      "åģ¥åº· åıijå±ķ",
+      "åĵģçīĮ çļĦ",
+      "ç¦ ®",
+      "ä½Ļ 人",
+      "ä»Ĭå¹´ 以æĿ¥",
+      "æķ° çłģ",
+      "çŃ¾ è¯ģ",
+      "åİ» æī¾",
+      "åŁºéĩij ä¼ļ",
+      "æĬ± æĢ¨",
+      "æŃ£ å½ĵ",
+      "çıŃåŃIJ æĪIJåijĺ",
+      "ä¸į åIJĪæł¼",
+      "åĪ¶ å®ļäºĨ",
+      "ç¼ĵ æħ¢",
+      "åĪ¶ 约",
+      "æłı 缮",
+      "å¸Ĥåľº ç»ıæµİ",
+      "ç»ĦæĪIJ çļĦ",
+      "严 峻",
+      "æĹ¥ 讯",
+      "ä¸ĢçĤ¹ çĤ¹",
+      "æĺ¯ æĢİä¹Ī",
+      "çļĦ çħ§çīĩ",
+      "éĺ» æŃ¢",
+      "模 ç³Ĭ",
+      "ç¼ ¸",
+      "éģķ åıį",
+      "æIJ¬ è¿ģ",
+      "éĩij éĴ±",
+      "å½ ¬",
+      "ä¸į å®ī",
+      "æĪĺçķ¥ åIJĪä½ľ",
+      "å¡« åĨĻ",
+      "讲 究",
+      "åħħåĪĨ åĪ©çĶ¨",
+      "èĥ½ å¤ł",
+      "èij¡èIJĦ éħĴ",
+      "éĩĩçĶ¨ äºĨ",
+      "åľ¨ ä»Ĭå¹´",
+      "ä¸Ńå°ı åѦ",
+      "åľ¨ æĦı",
+      "çļĦ åİĭåĬĽ",
+      "ä¸į 幸",
+      "åĪ¶ èį¯",
+      "åı¯ä»¥ 让",
+      "被 è¯Ħ为",
+      "ç»Ĩ èıĮ",
+      "æĪı åī§",
+      "åįĬ 导",
+      "åįĬ导 ä½ĵ",
+      "è§Ĩ è§Ĵ",
+      "åĸľ æŃ¡",
+      "å¾ģ æĶ¶",
+      "è°ĭ åĪĴ",
+      "æŀģ 大çļĦ",
+      "çĤ¹ èµŀ",
+      "è®°èĢħ ä»İ",
+      "两 åIJį",
+      "èĩª åĬ©",
+      "èµ· æŃ¥",
+      "æĬ¤ 士",
+      "å®Ŀ 马",
+      "太 åŃIJ",
+      "å°ıå°ı çļĦ",
+      "温 æ³ī",
+      "åĩºç§Ł 车",
+      "秣 æĪ¿",
+      "两 家",
+      "éľĩ æĴ¼",
+      "ç§ī æī¿",
+      "ä¸Ģ件 äºĭ",
+      "çĥĪ 士",
+      "å®ĺ åħµ",
+      "转 身",
+      "ä¹IJ åĽŃ",
+      "çĻĮ çĹĩ",
+      "模 èĮĥ",
+      "æĦ £",
+      "è¿ĩåİ» çļĦ",
+      "代 价",
+      "çļĦ æ¦Ĥ念",
+      "åĩł çĻ¾",
+      "è´µ éĺ³",
+      "æĭħ 忧",
+      "éĢĤ å®ľ",
+      "çݯå¢ĥ ä¿ĿæĬ¤",
+      "çĥ «",
+      "ä½ł æĥ³",
+      "æѤ åIJİ",
+      "ä½ł ä¹Ł",
+      "çį İ",
+      "éĻ¤ æѤ",
+      "éĻ¤æѤ ä¹ĭå¤ĸ",
+      "è°ĥ 度",
+      "ç§ij 缮",
+      "æīĢ说 çļĦ",
+      "åĬ ĩ",
+      "忽 è§Ĩ",
+      "ä¸ī 次",
+      "ä¸Ģ æĹ¥",
+      "åŀĤ 缴",
+      "ç«ŀ æĬĢ",
+      "éĿ¢ åĮħ",
+      "大 æĪĺ",
+      "æIJº 带",
+      "å¦Ĥæŀľ 没æľī",
+      "åħ» æĪIJ",
+      "åĩº è¡Ģ",
+      "çĪ±å¥½ èĢħ",
+      "æīĵ éĢļ",
+      "èµ· è¯ī",
+      "åijĪ çİ°åĩº",
+      "æŃĮ æīĭ",
+      "åľ¨ å¤ĸ",
+      "é¢Ĩ导 å¹²éĥ¨",
+      "åĨ ¥",
+      "èĪĨ 论",
+      "æıIJ åıĸ",
+      "éĺ¿ å°Ķ",
+      "æľĽ çĿĢ",
+      "ä¸ī äºļ",
+      "è² ¡",
+      "åĪ ·æĸ°",
+      "æĻļ æĬ¥",
+      "è¿ĺæľī ä¸Ģ个",
+      "åĨ° ç®±",
+      "ç½ij çĤ¹",
+      "åĩº åħ·",
+      "强çĥĪ çļĦ",
+      "æĪij çĽ¸ä¿¡",
+      "å¸ĮæľĽ èĥ½",
+      "çīĻ 齿",
+      "äºĭ å®ľ",
+      "ä¸ļåĨħ 人士",
+      "代 æĽ¿",
+      "åıĺ å½¢",
+      "éĽ ²",
+      "è°ĥ æݧ",
+      "åĪĽæĸ° åĪĽä¸ļ",
+      "æĭĨ è¿ģ",
+      "æł¸ æŁ¥",
+      "éĢ Ĺ",
+      "åħ¥ åѦ",
+      "æĦı åIJij",
+      "æı Ľ",
+      "ä¸ĭ 次",
+      "ä¼ł è¾ĵ",
+      "ä»ĸ们 åľ¨",
+      "èĢĮä¸Ķ è¿ĺ",
+      "æĹ¥ åľ¨",
+      "æķĻ è®Ń",
+      "æ´» çĿĢ",
+      "çļĦ æľīæķĪ",
+      "å¤įå·¥ å¤į",
+      "å¤įå·¥å¤į 产",
+      "æĺ¯ä¸Ģ 件",
+      "çŃī çĿĢ",
+      "å¾ ©",
+      "åĭĩ æķ¢",
+      "éģŃ åıĹ",
+      "å¥Ķ é©°",
+      "讲 座",
+      "说 å®Į",
+      "ç»Ļ åĩº",
+      "è° ¦",
+      "è¯Ĭ çĸĹ",
+      "çĽ² 缮",
+      "客 è¿IJ",
+      "å°± è¿ŀ",
+      "å¼Ģ åħĥ",
+      "å¼Ģåħĥ æ£ĭçīĮ",
+      "ä¸įæĸŃ æıIJåįĩ",
+      "çĶ¨æĪ· çļĦ",
+      "æĴ ķ",
+      "ä¾Ľ æ°´",
+      "ç¶ĵ æ¿Ł",
+      "ä¸Ń åĮ»èį¯",
+      "èģĶ æĥ³",
+      "åħ¬äº¤ 车",
+      "èĪª çıŃ",
+      "æĬĢ è¡ĵ",
+      "å¼ķèµ· çļĦ",
+      "å° ¹",
+      "èµĦ æ·±",
+      "åĽ½èµĦ å§Ķ",
+      "èĺ Ń",
+      "é¼» åŃIJ",
+      "éĹ ½",
+      "æİĴ éĺŁ",
+      "è§Ĥ åħī",
+      "éģĹ åĿĢ",
+      "举 京",
+      "é¥Ń åºĹ",
+      "ä¸įæĸŃ çļĦ",
+      "å°±æĺ¯ ä¸Ģ个",
+      "éķ¿ ä¹ħ",
+      "çļĦ è§ĤçĤ¹",
+      "å¨ ¶",
+      "æĪij çİ°åľ¨",
+      "çķ °",
+      "å¾Ĺ åĩº",
+      "å¿ħ å®ļ",
+      "ä¸į åıĹ",
+      "åıª éľĢè¦ģ",
+      "åĽ° æī°",
+      "ç§ijåѦ æĬĢæľ¯",
+      "çīĽ èĤī",
+      "è¾ĥ é«ĺçļĦ",
+      "è·ij æŃ¥",
+      "æ² ¾",
+      "èı© èIJ¨",
+      "æľĢ å¾Į",
+      "ä¿Ŀ å¯Ĩ",
+      "æ²» å®ī",
+      "éĤ ±",
+      "常 è¯Ĩ",
+      "èĦ¸ èī²",
+      "åĮĹ å¤§",
+      "æ±ĩ èģļ",
+      "æijĨ èĦ±",
+      "é¾Ļ头 ä¼ģä¸ļ",
+      "女 åıĭ",
+      "çŃī å·¥ä½ľ",
+      "ä¸Ń ç¾İ",
+      "èģĮ åľº",
+      "èĦij è¢ĭ",
+      "åĨĻ çļĦ",
+      "饲 æĸĻ",
+      "åĬ³ åĬ¨åĬĽ",
+      "å± ¯",
+      "æĮģ èĤ¡",
+      "åĽ¾ åĥı",
+      "è¿ĩåİ» äºĨ",
+      "è² ¨",
+      "è¾ ²",
+      "éĹ® æĪij",
+      "è·Ł ä½ł",
+      "çĶŁ æŃ»",
+      "审 ç¾İ",
+      "é¢Ĺ ç²Ĵ",
+      "ä¸Ń æĸ¹",
+      "åĬł çĥŃ",
+      "æĹħè¡Į 社",
+      "çĻ¼ çĶŁ",
+      "ä¸į åłª",
+      "åĤ ·",
+      "æ¥ ł",
+      "åĬŀ æ¡Ī",
+      "æŁ Ħ",
+      "æĹ¢ æĺ¯",
+      "å¤Ħ åĪĨ",
+      "羣å®ŀ çļĦ",
+      "æĬ¥ 纸",
+      "å¸Ī çĪ¶",
+      "å®īå¾½ çľģ",
+      "åī¯ 主å¸Ń",
+      "ä¹ĭ éģĵ",
+      "导 弹",
+      "åŃ¦æł¡ çļĦ",
+      "åŁİå¸Ĥ çļĦ",
+      "è°Ī åĪ°",
+      "æ¢ Ĺ",
+      "å¹³ éĿ¢",
+      "说 ä»Ģä¹Ī",
+      "é¢ij çİĩ",
+      "éķ¿ ä¸īè§Ĵ",
+      "çļĦ åĪ©çĽĬ",
+      "é» ¨",
+      "è±Ĩ èħIJ",
+      "å®ŀéĻħ æĥħåĨµ",
+      "æŀĹ ä¸ļ",
+      "纪æ£Ģ çĽijå¯Ł",
+      "ä½ı éĻ¢",
+      "çļĦ æķ´ä½ĵ",
+      "åīį è¡Į",
+      "æĮ ¨",
+      "çħ¤ çŁ¿",
+      "åī¯æĢ» è£ģ",
+      "å°ı åIJĥ",
+      "æŀģ 端",
+      "å©Ĩ å©Ĩ",
+      "çİ° è´§",
+      "è¯Ĺ æŃĮ",
+      "éĴ¥ åĮĻ",
+      "缩 çŁŃ",
+      "ä½Ĩ è¿Ļ",
+      "æĸ° åĵģ",
+      "è¿Ļ 对",
+      "çŁ¥åIJį 度",
+      "å¿ĹæĦ¿ æľįåĬ¡",
+      "大 å±Ģ",
+      "è¡¡ éĩı",
+      "ä½ĵçİ° äºĨ",
+      "æ¡ĥ èĬ±",
+      "åIJ¸å¼ķ åĬĽ",
+      "åł ¤",
+      "æĵħ éķ¿",
+      "åĴ Ĵ",
+      "缸 æľº",
+      "ä¸Ģ ç«Ļ",
+      "ä¸Ģç«Ļ å¼ı",
+      "æľĢ ç¾İ",
+      "æ°¸ ä¹ħ",
+      "çļĦ éĥ¨åĪĨ",
+      "åĪĨ å·¥",
+      "å·¥ç¨ĭ 建设",
+      "æIJŃ è½½",
+      "æ°´ ä¸Ń",
+      "èĮ ¨",
+      "çļĦ æĵįä½ľ",
+      "绣 æ²»",
+      "çķħ éĢļ",
+      "åħļçļĦ åįģ",
+      "è¼ ¸",
+      "æ¸ ¬",
+      "ç¾İ è§Ĥ",
+      "ä¸į åĪ©",
+      "åıį æĢĿ",
+      "éªĦ åĤ²",
+      "æłĩ çļĦ",
+      "æĿĢ 人",
+      "éĺ¿ å§¨",
+      "é£Ł æĿIJ",
+      "åIJĥ çļĦ",
+      "åIJİ åĨį",
+      "çŁ £",
+      "两 侧",
+      "æ¸ħ æ°´",
+      "è¿Ľ çIJĥ",
+      "å¼Ģå§ĭ äºĨ",
+      "åIJ¬ äºĨ",
+      "çĦĬ æİ¥",
+      "çŁ ®",
+      "å¨ Ł",
+      "为 人",
+      "éĢģ ç»Ļ",
+      "åĨĴ éĻ©",
+      "æķ ·",
+      "ç»Ī æŃ¢",
+      "æīį çŁ¥éģĵ",
+      "è¿IJ æ°Ķ",
+      "éĢļ é£İ",
+      "æĥĬ 讶",
+      "ç§ijåѦ éĻ¢",
+      "æıIJ éĹ®",
+      "太 åİŁ",
+      "缸åIJĮ çļĦ",
+      "ä» ķ",
+      "èģ ĸ",
+      "æĥħ æ³ģ",
+      "é¢Ĩ导 人",
+      "åĩºæĿ¥ äºĨ",
+      "沿 线",
+      "éĻ ½",
+      "æĦŁ 覺",
+      "ä»į åľ¨",
+      "æ© Ļ",
+      "约 为",
+      "åĸĿ éħĴ",
+      "çĶ¨ èį¯",
+      "ä¸ĭ ä¸Ģ",
+      "æ³ķ å®ĺ",
+      "顺 åºı",
+      "åģļ ä¸Ģ个",
+      "åĭ ¢",
+      "æŃ ª",
+      "çĶµ ç«ŀ",
+      "ä¼´ éļıçĿĢ",
+      "ä¹ĭ åĬĽ",
+      "ä¹ĭ 人",
+      "äºij 计ç®Ĺ",
+      "åĪ«äºº çļĦ",
+      "ç§ijåѦ åıijå±ķ",
+      "第 åħ«",
+      "å¹² æī°",
+      "女 ç¥ŀ",
+      "è¿Ļæł· åģļ",
+      "å¤Ħ åľ¨",
+      "æ°´ è´¨",
+      "éķ¿ æĺ¥",
+      "å¸Ĥåľº éľĢæ±Ĥ",
+      "ç»´ æĿĥ",
+      "èĢ³ æľµ",
+      "æĸĩåĮĸ çļĦ",
+      "奶 ç²ī",
+      "ä¼ł è¾¾",
+      "æīĭæľº çīĪ",
+      "æĽ¾ åľ¨",
+      "äºĮ æľŁ",
+      "åİŁåĽł æĺ¯",
+      "æºIJ 头",
+      "åıĪ èĥ½",
+      "è£ ¸",
+      "æĬĢæľ¯ åĪĽæĸ°",
+      "æĸĩåĮĸ æĹħ游",
+      "åıij 票",
+      "年 级",
+      "ä½ł ä¸į",
+      "ä¹ĭ å¿ĥ",
+      "æķ° çĻ¾",
+      "åIJij å¾Ģ",
+      "èĢģ 家",
+      "åľĭ éļĽ",
+      "çļĦ é«ĺ度",
+      "æľĿ éĺ³",
+      "æ¸ħ éĻ¤",
+      "èĩª æľī",
+      "书 ä¸Ń",
+      "游æĪı è£ħå¤ĩ",
+      "ä¸ĩ å¤ļ",
+      "驾驶 åijĺ",
+      "ä½ł çŁ¥éģĵ",
+      "åĽ½ åºĨ",
+      "é£Ł åłĤ",
+      "æİ¥ åı£",
+      "æĢ» æķ°",
+      "åħ¶ä»ĸ çļĦ",
+      "çĶŁåij½ çļĦ",
+      "ä½ł åľ¨",
+      "çļĦ 缮åħī",
+      "è¿Ļ æĸ¹éĿ¢",
+      "éĥ½ 说",
+      "çĸĹ æ³ķ",
+      "åĭĩ 士",
+      "åľ¨ åħ¨çIJĥ",
+      "ä¿ĿéĻ© åħ¬åı¸",
+      "çĿ£ æŁ¥",
+      "åĸĦ èī¯",
+      "表 彰",
+      "è¹ ²",
+      "路 段",
+      "æľĥåĵ¡ è¦ı",
+      "æľĥåĵ¡è¦ı ç¯Ħ",
+      "æĪ· åŀĭ",
+      "ä¿ĥ 使",
+      "修 建",
+      "é«ĺ æ°´å¹³",
+      "åģļ åĩºäºĨ",
+      "主 åľº",
+      "è¡Į èµ°",
+      "空 çĻ½",
+      "æľī人 说",
+      "è¿Ļ个 ä¸ĸçķĮ",
+      "åIJį ä¹ī",
+      "å®Į ç¾İçļĦ",
+      "羡 æħķ",
+      "åıĬ åħ¶ä»ĸ",
+      "åı¯ çĶ¨",
+      "æĭ IJ",
+      "è¾ĥ 大çļĦ",
+      "æĬĢæľ¯ åĴĮ",
+      "å°¼ äºļ",
+      "çĻ¾ è´§",
+      "æı ī",
+      "éĢī è´Ń",
+      "éĺŁ åıĭ",
+      "ä¼ł æĦŁ",
+      "ä¼łæĦŁ åĻ¨",
+      "åıªè¦ģ ä½ł",
+      "为ä»Ģä¹Ī è¦ģ",
+      "ä¸ĵ注 äºİ",
+      "ä½Ļ é¢Ŀ",
+      "åħ¸åŀĭ çļĦ",
+      "缮åīį å·²",
+      "欲 æľĽ",
+      "èģĶ 绾",
+      "æµģ ä¼ł",
+      "çļĦ 家åºŃ",
+      "åı· åı¬",
+      "çıį è´µ",
+      "ä¼Ł 大çļĦ",
+      "éī´ äºİ",
+      "è·Ł ä»ĸ",
+      "产 çī©",
+      "ä¸į å·²",
+      "è¿Ŀæ³ķ è¡Į为",
+      "头 ä¸Ĭ",
+      "åĪĨ 解",
+      "åı¯ä»¥ çľĭåĩº",
+      "æł¡ åĮº",
+      "åŃĹ ä½ĵ",
+      "ä¿® çĤ¼",
+      "çĶļèĩ³ æĺ¯",
+      "微信 åħ¬ä¼Ĺ",
+      "åıĸ 代",
+      "èIJ¥ä¸ļ æĶ¶åħ¥",
+      "æ½į åĿĬ",
+      "ä½ł èĥ½",
+      "社ä¼ļ ä¿Ŀéļľ",
+      "æ¯ĶèµĽ ä¸Ń",
+      "污水 å¤ĦçIJĨ",
+      "夫 å¦ĩ",
+      "ä¸Ģ å¹ħ",
+      "沿 海",
+      "åı£ æĦŁ",
+      "ä½Ĩ åį´",
+      "å½ĵ æĹ¥",
+      "çļĦ æľĢ大",
+      "æ¯ı ä¸Ģä½į",
+      "没 äºĭ",
+      "çī¹ åĪ¥",
+      "å¼Ģ åѦ",
+      "è·¯ éĿ¢",
+      "å¿ĥçIJĨ åѦ",
+      "æĶ¾ ç½®",
+      "éĩįåºĨ å¸Ĥ",
+      "ä½ł èĩªå·±",
+      "æ¶Īè´¹èĢħ çļĦ",
+      "ä¸Ģ æ³¢",
+      "èѦ æĥķ",
+      "åį§ 室",
+      "注 å°Ħ",
+      "é£İ 鼨",
+      "沿 çĿĢ",
+      "åijĬ 訴",
+      "表 çİ°åĩº",
+      "åĽĽ æĺ¯",
+      "åı¤ åħ¸",
+      "æĽ´ éĩįè¦ģçļĦ",
+      "好 äºĭ",
+      "çľ¼ 泪",
+      "æ¨ ĵ",
+      "审 åĪ¤",
+      "碰 æĴŀ",
+      "车 ç«Ļ",
+      "è¿Ľåħ¥ äºĨ",
+      "éĽĨ åIJĪ",
+      "æł¼ å¤ĸ",
+      "宾 é¦Ĩ",
+      "æĶ¯ä»ĺ å®Ŀ",
+      "她 æĺ¯",
+      "æĺ¯ å¦Ĥä½ķ",
+      "人 次",
+      "çļĦ æĪIJåĬŁ",
+      "æĹł åĬĽ",
+      "æµ· æĭĶ",
+      "æĺ¥ åŃ£",
+      "éĥ½ ä¸įä¼ļ",
+      "çŃī å¤ļç§į",
+      "ä¸Ģ个 å°ı",
+      "åģľè½¦ åľº",
+      "让 æĽ´å¤ļ",
+      "è¿Ļ çĤ¹",
+      "æĪIJ åĵģ",
+      "éĴ ī",
+      "éģĩ è§ģ",
+      "çıŃ ä¸»ä»»",
+      "æĦı æĦ¿",
+      "çļĦ åIJĮåѦ",
+      "游 è§Ī",
+      "åİĭ 缩",
+      "åľ¨ ä¼łå¥ĩ",
+      "å¼¹ æĢ§",
+      "æĹ¥ åĨħ",
+      "ç¦ı建 çľģ",
+      "è§Ĵ èIJ½",
+      "åĪĨ å¼Ģ",
+      "ä¼ļ 让",
+      "å¤ĸ åĽ´",
+      "çĨŁæĤī çļĦ",
+      "çĨ Ķ",
+      "ä¸ĩ è¾Ĩ",
+      "å¤ľ éĹ´",
+      "车 身",
+      "ä¸Ń æľŁ",
+      "å®ĮåĸĦ çļĦ",
+      "åĵģ ç±»",
+      "åıĭ è°Ĭ",
+      "éĢīæĭ Ķ",
+      "éªij 士",
+      "å½ ¦",
+      "çļĦ çľĭæ³ķ",
+      "åĽ½ çİĭ",
+      "è¾£ æ¤Ĵ",
+      "åıijå¸ĥ æŶéĹ´",
+      "åı¤ åŁİ",
+      "éļı æľº",
+      "ç« ĸ",
+      "å¼Ģ è¾Ł",
+      "ä¼Ĺ çĶŁ",
+      "没 åĬŀæ³ķ",
+      "åįĥ éĩĮ",
+      "æĿ¥æºIJ äºİ",
+      "çļĦ æĿĥåĪ©",
+      "æ¯Ķ åĪĨ",
+      "满æĦı çļĦ",
+      "ä¿® è¡Į",
+      "åĿ ł",
+      "大 海",
+      "èİ ¹",
+      "åĩº 身",
+      "è« ĩ",
+      "åħ³ èĬĤ",
+      "åIJį 人",
+      "éľĢè¦ģ 注æĦı",
+      "æĹ© æĻ¨",
+      "å¤ĸ åįĸ",
+      "åıĪ è¦ģ",
+      "æ¶ī æ¡Ī",
+      "çĶ³è¯· 人",
+      "éĻĦè¿ij çļĦ",
+      "åĬłå¿« æİ¨è¿Ľ",
+      "æĸ° å¹´",
+      "大 è¡Ĺ",
+      "ä¸Ģ é»ŀ",
+      "èĭı å®ģ",
+      "æĤĦ æĤĦ",
+      "èĦ¾ æ°Ķ",
+      "å¸Į èħĬ",
+      "éļı åį³",
+      "æķ¢ äºİ",
+      "å®ŀè·µ ä¸Ń",
+      "æĺ¯ æ²¡æľī",
+      "æľī趣 çļĦ",
+      "æĿ¥èĩª äºİ",
+      "è£ģ åĪ¤",
+      "女 åŃ©åŃIJ",
+      "èĩ³ åħ³",
+      "èĩ³åħ³ éĩįè¦ģ",
+      "æĻº åĬĽ",
+      "èµ° åĩºåİ»",
+      "çŁŃ æĿ¿",
+      "大 åĽ½",
+      "çļĦ 认è¯Ĩ",
+      "å¹´ å¤ľ",
+      "åĨį åĪ°",
+      "åIJĮ æł·çļĦ",
+      "å¯Ĩ å°ģ",
+      "å¤ĸ交 éĥ¨",
+      "çĶŁ æķĪ",
+      "æĤ¨ åı¯ä»¥",
+      "ä½ł åĢij",
+      "è¿ĩ å¹´",
+      "å¼ ĵ",
+      "è¡Į æĿİ",
+      "æ¯Ķ èµ·",
+      "身 é«ĺ",
+      "è¿Ļ个 人",
+      "ä¸Ń å¤ĸ",
+      "éģĵ æŃī",
+      "çĽ¯ çĿĢ",
+      "亲 åŃIJ",
+      "éĹ ¸",
+      "çĻ½ äºij",
+      "èĦĸ åŃIJ",
+      "ä¸ĢåĪĩ éĥ½",
+      "æ· ij",
+      "è° ľ",
+      "åģ¶ çĦ¶",
+      "éĿł è°±",
+      "é«ĺ 管",
+      "ä¸ĭ åıij",
+      "æĶ¾ åĪ°",
+      "ç±» åĪ«",
+      "ä¸ĭ åĪĹ",
+      "æ·· ä¹±",
+      "åIJĪæ³ķ æĿĥçĽĬ",
+      "çݯ çIJĥ",
+      "æľīæķĪ åľ°",
+      "åķĨ æĪ·",
+      "æ¹ĸ 人",
+      "海 岸",
+      "æĬķ 产",
+      "两 个æľĪ",
+      "éĥ½ éĿŀ常",
+      "å¢ŀ强 äºĨ",
+      "æĿ¥ åĪ°äºĨ",
+      "åī© ä½Ļ",
+      "æĤ¨çļĦ åŃ©åŃIJ",
+      "æµģ æ°´",
+      "æŃ£ ä¹ī",
+      "天 çĮ«",
+      "åģļ è¿ĩ",
+      "ä½ķ æŶ",
+      "æĪij åİ»",
+      "çľģ 份",
+      "å¥ĸ éĩij",
+      "该 å¦Ĥä½ķ",
+      "ä¸ĭ çıŃ",
+      "åģ¶ åĥı",
+      "æijĨ æĶ¾",
+      "æĸ° 模å¼ı",
+      "æĬķ è³ĩ",
+      "è·¯ åı£",
+      "åĨľæ°ij å·¥",
+      "大 åѸ",
+      "件 äºĭ",
+      "æł¹æľ¬ ä¸į",
+      "æµĵ 度",
+      "æµĵ åİļ",
+      "è½® èĥİ",
+      "æĪ¿ ä¼ģ",
+      "éĿŀ常 好",
+      "ä»İ ä¸Ń",
+      "人 æł¼",
+      "ç¿ ģ",
+      "æŶéĹ´ åĴĮ",
+      "è¿Ļ ä¸įæĺ¯",
+      "åĪ¸ åķĨ",
+      "æĥĬ 人",
+      "åĻ¨ å®ĺ",
+      "åĩĨ åĪĻ",
+      "æĥħ æĻ¯",
+      "æĽ´ é«ĺçļĦ",
+      "åѦ 家",
+      "泡 沫",
+      "åľ°æĸ¹ æĶ¿åºľ",
+      "å°± çŁ¥éģĵ",
+      "åij¼ åIJģ",
+      "ç»ı è´¸",
+      "èĬ± éĴ±",
+      "æľī ä¸Ģ次",
+      "æĦŁ æħ¨",
+      "ä¸Ģ åįĥ",
+      "å¤ľ æĻļ",
+      "詹 å§Ĩ",
+      "詹å§Ĩ æĸ¯",
+      "è¦ģ éĹ»",
+      "ç» Ĵ",
+      "æºIJ äºİ",
+      "çļĦ è´¨éĩı",
+      "注æĦı äºĭ项",
+      "æħ¢ æĢ§",
+      "稳å®ļ çļĦ",
+      "建设 åĴĮ",
+      "æĻ¯ 象",
+      "éĩı åĮĸ",
+      "çļĦ 話",
+      "è¯Ħ 级",
+      "æº ľ",
+      "红 åĮħ",
+      "éĢļ éģİ",
+      "社ä¼ļ 责任",
+      "æĸ° 产åĵģ",
+      "åĨ· éĿĻ",
+      "çľĭ ä¸įåĪ°",
+      "èģĶ éĤ¦",
+      "éŃ Ħ",
+      "çļĦ åīįæıIJ",
+      "çļĦåīįæıIJ ä¸ĭ",
+      "è¾ĥ 好",
+      "çļĦ æĦŁæĥħ",
+      "客æĪ· æıIJä¾Ľ",
+      "çĭ¬ èĩª",
+      "å¢ŀ æĶ¶",
+      "æĸĩ çĮ®",
+      "æĭ¼ åij½",
+      "管çIJĨ åĴĮ",
+      "æµģåĬ¨ æĢ§",
+      "åħ¨ 家",
+      "ä¸Ĭ æĸ¹",
+      "æݨåĩº çļĦ",
+      "ä¸ī åĽ½",
+      "ä¸Ģ个 æĺ¯",
+      "æĸ° ä¸Ģè½®",
+      "æĸĩåĮĸ éģĹ产",
+      "æ® º",
+      "大 æ¹¾åĮº",
+      "éĥ½ éľĢè¦ģ",
+      "çļĦ å®ŀéĻħ",
+      "ç· Ĭ",
+      "大 å¥ĸ",
+      "åħī èĬĴ",
+      "便 äºİ",
+      "çļĦ 表æĥħ",
+      "æ¼Ķ ç»İ",
+      "红 åĨĽ",
+      "å½ĵ æĪij",
+      "æ²» æĦĪ",
+      "é¢Ŀ 度",
+      "éĿ ľ",
+      "ä»»ä½ķ 人",
+      "è¡Ĺ 头",
+      "çī¹ æĸ¯",
+      "çī¹æĸ¯ æĭī",
+      "åĮ»çĸĹ æľºæŀĦ",
+      "ç»Ļ åŃ©åŃIJ",
+      "è§Ħ 磩",
+      "è£ ľ",
+      "çļĦ 身影",
+      "ä¸ĵ æłı",
+      "æĿ¥ 临",
+      "ç«¥ å¹´",
+      "å¤į èĭı",
+      "è¨ Ĥ",
+      "åŀĭ åı·",
+      "åĽ¾ æ¡Ī",
+      "ç®Ģ åİĨ",
+      "æĭ ±",
+      "èį· åħ°",
+      "ä»» æĦı",
+      "æī¿ æİ¥",
+      "è¿Ļ æīį",
+      "客 车",
+      "æľĿ çĿĢ",
+      "éłħ 缮",
+      "åı° é£İ",
+      "çļĦ æĪ¿åŃIJ",
+      "éª ı",
+      "æĿ± 西",
+      "éģĹ ä¼ł",
+      "è¶Ĭ å¤ļ",
+      "äºĨ ä»ĸçļĦ",
+      "ä¸Ĭ åij¨",
+      "管çIJĨ åĪ¶åº¦",
+      "失 ä¸ļ",
+      "çĶ· åıĭ",
+      "æİ¥ ç§į",
+      "å¨ģ åIJį",
+      "çĴ° å¢ĥ",
+      "åıijçĶŁ åľ¨",
+      "个 åĽ½å®¶",
+      "åĪĽæĸ° åıijå±ķ",
+      "æĶ¹åıĺ äºĨ",
+      "åģ¥åº· çļĦ",
+      "åĢ¼å¾Ĺ ä¸Ģ",
+      "åĢ¼å¾Ĺä¸Ģ æıIJ",
+      "åĽ¢ ä¼Ļ",
+      "åģĩ 设",
+      "åı° ä¸Ĭ",
+      "è§ĦèĮĥ åĮĸ",
+      "éĻª åIJĮ",
+      "座 æ¤ħ",
+      "åı¯ æĢľ",
+      "åħĭæĢĿ 主ä¹ī",
+      "æ³ķå¾ĭ 责任",
+      "ä¸Ģ é¡¿",
+      "æĬ¬ 头",
+      "为 éĩįçĤ¹",
+      "è¿ľ æ´ĭ",
+      "éĢı è¿ĩ",
+      "åħ¨çIJĥ åĮĸ",
+      "趣 åij³",
+      "票 æĪ¿",
+      "æ¯ı 人",
+      "åIJĦç§į åIJĦæł·",
+      "äºĨ åĩºæĿ¥",
+      "ç»Ŀ对 æĺ¯",
+      "ä¸ĭ å±ŀ",
+      "ä¸Ģ åıĮ",
+      "è¿Ļ åĿĹ",
+      "æĬĹ çĸ«",
+      "è¦ģ çĤ¹",
+      "å½¢æĪIJ çļĦ",
+      "æĪij çľĭ",
+      "ä¸ĩ éĩĮ",
+      "èĢĥ çłĶ",
+      "为 åħ¶",
+      "æ°ij 宿",
+      "å¤ļ ä½į",
+      "大 èĩ´",
+      "ä»ĺ è´¹",
+      "åħ¥ æīĭ",
+      "å±ħ 家",
+      "æīĢåľ¨ åľ°",
+      "人 身",
+      "è¿ĩ å¾Ĺ",
+      "è¯ķ è¯ķ",
+      "访 è°Ī",
+      "åĬł éĩį",
+      "å°± ä¸įä¼ļ",
+      "çĶŁäº§ ä¼ģä¸ļ",
+      "åĽŀ åĽ½",
+      "åºķ 线",
+      "赶 åĪ°",
+      "æĶ¯ éĺŁ",
+      "æĪij们 éĥ½",
+      "éĤ® æĶ¿",
+      "缴 èĩ³",
+      "éĴ¢ çIJ´",
+      "åħ ľ",
+      "çłĶ讨 ä¼ļ",
+      "æľĪ 亮",
+      "åĿļæĮģ 以",
+      "åħ¬å®ī éĥ¨",
+      "éĴ¢ 管",
+      "å°ı çĻ½",
+      "ç½® ä¸ļ",
+      "èģ ĭ",
+      "书 åĨĻ",
+      "æĿ ı",
+      "éħį æĸ¹",
+      "èĢĮ åıĪ",
+      "çijŀ 士",
+      "çķĮ çļĦ",
+      "èĢģ 大",
+      "æĪIJçĨŁ çļĦ",
+      "å¹² ä»Ģä¹Ī",
+      "ä¸ĵ项 æĸĹäºī",
+      "çŃī å¤ļ个",
+      "èĦ± 离",
+      "ä¸ī 个æľĪ",
+      "çłĶ究 åijĺ",
+      "æĹĭ 转",
+      "æŀģ èĩ´",
+      "åħį è´£",
+      "åħįè´£ 声æĺİ",
+      "å¾Īå¤ļ çݩ家",
+      "车 ä¸Ĭ",
+      "交 äºĴ",
+      "å·² æĺ¯",
+      "ä¸Ģ å°ı",
+      "çļĦ éĩįçĤ¹",
+      "èĬ± äºĨ",
+      "ä¸į æĺİ",
+      "æľīåħ³ è§Ħå®ļ",
+      "çĬ¹ å¦Ĥ",
+      "çľ ¸",
+      "å¯ ¡",
+      "çļĦ è¡£æľį",
+      "åĮħ 裹",
+      "身 åŃIJ",
+      "å¸ĪèĮĥ 大åѦ",
+      "äºĭ åħĪ",
+      "线 æĿ¡",
+      "æ³ķ åĪ¶",
+      "åħ» æĬ¤",
+      "稳å®ļ æĢ§",
+      "éĤ µ",
+      "åŀĦ æĸŃ",
+      "é¡ į",
+      "èĢĥ åı¤",
+      "æĿł æĿĨ",
+      "èĭı èģĶ",
+      "æ°´ çĶµ",
+      "åħ·ä½ĵ çļĦ",
+      "æ¿Ģ æ´»",
+      "æĪij æł¡",
+      "åĪļ å¼Ģå§ĭ",
+      "åĩ¸ æĺ¾",
+      "ç¦ ¾",
+      "åħ¼ èģĮ",
+      "éĢı éģİ",
+      "åľ¨ 游æĪıä¸Ń",
+      "社ä¼ļ åıijå±ķ",
+      "好 çİ©",
+      "å¹» æĥ³",
+      "ä¸į 代表",
+      "注æĦı åĬĽ",
+      "æ£ į",
+      "çĶ¨ æīĭ",
+      "ç¾İ 人",
+      "许å¤ļ 人",
+      "å¾Ī æĺ¯",
+      "çļĦ çłĶåıij",
+      "æīĵ åĩº",
+      "åIJĪä¼Ļ 人",
+      "ä¸Ģ å¤ľ",
+      "ç¼ĵ ç¼ĵ",
+      "ä¿® æŃ£",
+      "æĦŁ çŁ¥",
+      "ç»Ī 身",
+      "æ¿Ģ ç´ł",
+      "çݯå¢ĥ ä¸ĭ",
+      "次 ä¼ļè®®",
+      "ç»ıæµİ å¢ŀéķ¿",
+      "æī Ľ",
+      "åıij éħµ",
+      "åĪĨæŀIJ å¸Ī",
+      "åľ¨ æľªæĿ¥",
+      "主è¦ģ æľī",
+      "ä¸Ģ åŃ£åº¦",
+      "çļĦ 说æ³ķ",
+      "ä»İæĿ¥ 没æľī",
+      "货 车",
+      "缩 å°ı",
+      "太 è¿ĩ",
+      "æķĪ åĬĽ",
+      "ä¸į ä¸ĭ",
+      "æĬķ 稿",
+      "èį¯ ä¸ļ",
+      "ç»Ħ éķ¿",
+      "ç«Ļ çĤ¹",
+      "å¾Ī åĸľæ¬¢",
+      "éIJ µ",
+      "åĬ¿ 头",
+      "æ¼ı æ´ŀ",
+      "æĦ¤ æĢĴ",
+      "åħħ å®ŀ",
+      "åĪĽä¸ļ æĿ¿",
+      "çĪ ª",
+      "æľª å¿ħ",
+      "åºķ éĥ¨",
+      "å¾Ĺ åĪĨ",
+      "人æ°ij åĮ»éĻ¢",
+      "äºĮæīĭ æĪ¿",
+      "å·²ç»ı 被",
+      "大 楼",
+      "æĸ° æĪ¿",
+      "辦 æ³ķ",
+      "çĶ¨ åĬĽ",
+      "æĭĵ 宽",
+      "åĨħ åľ¨",
+      "æĴŃ åĩº",
+      "饰 æ¼Ķ",
+      "ä¹Ł 让",
+      "ä½ľ çĤº",
+      "çī©ä¸ļ 管çIJĨ",
+      "åį´ ä¸į",
+      "为 ä¸ŃåĽ½",
+      "å±Ģ åĬ¿",
+      "ä¸į èĤ¯",
+      "æľĢ æĸ°çļĦ",
+      "åı¯ä»¥ éĢīæĭ©",
+      "æĺ¾ çİ°",
+      "å°± ç®Ĺæĺ¯",
+      "åľ¨ æł¡",
+      "é¾ Ł",
+      "两 æĿ¡",
+      "çļĦ å®ŀåĬĽ",
+      "è¶Ĭ 好",
+      "她 åľ¨",
+      "å¿ł è¯ļ",
+      "ä¹Ł éľĢè¦ģ",
+      "游æĪı æĵįä½ľ",
+      "è¶ħ åĩº",
+      "å¦Ĥæŀľ ä¸į",
+      "æīĢåľ¨ çļĦ",
+      "ä½ł è¿ĺ",
+      "以 åĨħ",
+      "æľī ä¸Ģå®ļ",
+      "åı¯ è¾¾",
+      "è·ij åĪ°",
+      "åī Ľ",
+      "建ç«ĭ åģ¥åħ¨",
+      "æķ´ 车",
+      "åīį æĸ¹",
+      "éĹ´ æİ¥",
+      "çŃ¹ å¤ĩ",
+      "çĸ² åĬ³",
+      "离 å¼ĢäºĨ",
+      "æ± Ŀ",
+      "éĿ¢ éĥ¨",
+      "ä¹ĭåīį çļĦ",
+      "åıĺ 为",
+      "å¦Ĥæŀľ 说",
+      "对 ä»ĺ",
+      "åĿĩ åı¯",
+      "被åijĬ 人",
+      "ç²¾ ç¾İ",
+      "èģļ ä¼ļ",
+      "çĿĢ æĢ¥",
+      "è°· æŃĮ",
+      "ä¸Ģ åı·",
+      "红 åĪ©",
+      "ä¼łå¥ĩ 游æĪı",
+      "å» ĸ",
+      "è´ ŀ",
+      "ä¹° åĪ°",
+      "éŃ ļ",
+      "ä½ĵ è´¨",
+      "å°ij äºĨ",
+      "æ³ī å·ŀ",
+      "åIJ Ł",
+      "ç»Ŀ ä¸į",
+      "é»ij æģ¶",
+      "é»ijæģ¶ åĬ¿åĬĽ",
+      "ä¸Ĭ æĺł",
+      "çļĦè¯Ŀ é¢ĺ",
+      "ä¸ĩ人 次",
+      "ä¸ĸ éĹ´",
+      "çĶ¨ å·¥",
+      "è´¯ ç©¿",
+      "å®Ŀ çŁ³",
+      "ä½ł 好",
+      "åĪĩ åī²",
+      "强 åĽ½",
+      "åĽŀ èIJ½",
+      "æ°´ æĻ¶",
+      "模 仿",
+      "æ´ª æ°´",
+      "éĢĻ 麼",
+      "åįģä¸ī äºĶ",
+      "ä½ ij",
+      "éĻ Ħ件",
+      "çļĦ å¢ŀéķ¿",
+      "éĻĦ å±ŀ",
+      "çİ° å·²",
+      "帮 ä½ł",
+      "éĩij çīĮ",
+      "é«ĺ åİŁ",
+      "åľ¨ 家éĩĮ",
+      "éĺ² èħIJ",
+      "ç¡®å®ŀ æĺ¯",
+      "宣 讲",
+      "天 æīį",
+      "ç»ıèIJ¥ 管çIJĨ",
+      "éĶħ çĤī",
+      "åIJĪ ä¸Ģ",
+      "è§Ĥ èµı",
+      "éķ¿ è¾¾",
+      "主ä¹ī æĢĿæĥ³",
+      "éĤ£ 麼",
+      "é£İ äºij",
+      "为主 çļĦ",
+      "æļij åģĩ",
+      "æĮģ ä¹ħ",
+      "å¼Ĥ åľ°",
+      "å¼Ģ éŨ",
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+      "ä¸į 便",
+      "天 çĶŁ",
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+      "æĩ ·",
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+      "çļĦå¿ĥ æĢģ",
+      "è¿ĺ 好",
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+      "åħ© åĢĭ",
+      "åı¯ åľ¨",
+      "éĤ£ ä½į",
+      "å¥ł å®ļäºĨ",
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+      "æı´ åĬ©",
+      "ä¸ĩ çī©",
+      "æĥħ æĬ¥",
+      "é¦ĸåħĪ è¦ģ",
+      "æĸĩåĮĸ åĴĮ",
+      "éĥ½ å·²ç»ı",
+      "ä¸Ĭ ä¸ĸ纪",
+      "åĨľ åľº",
+      "大 æī¹",
+      "æĺİçĻ½ äºĨ",
+      "çļĦ æĪIJéķ¿",
+      "çļĦ æ¯ĶèµĽ",
+      "失 误",
+      "åģļ æĪIJ",
+      "ä»Ĭ天 å°ıç¼ĸ",
+      "é¢Ĩ è¢ĸ",
+      "æıIJåįĩ äºĨ",
+      "å¾IJ å·ŀ",
+      "ä»į æľī",
+      "è¿ĩ 滤",
+      "å¹½ é»ĺ",
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+      "åĩł ç§į",
+      "åĢ¡ è®®",
+      "å°±åı¯ä»¥ äºĨ",
+      "æİĴ åĪĹ",
+      "éĩį éĩį",
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+      "ä¸ĵ å±ŀ",
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+      "è¿ĺ å¾Ĺ",
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+      "å¤ ¢",
+      "ä»ĸ 对",
+      "å¿ħ å°Ĩ",
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+      "åĩº åľº",
+      "å·²ç»ı æľī",
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+      "é«ĺ æ¡£",
+      "ä¸Ģ æīĢ",
+      "æł Ĺ",
+      "让 åѦçĶŁ",
+      "æĽ¹ æĵį",
+      "æŁIJ ä¸Ģ",
+      "伸 åĩº",
+      "èĬ± åįī",
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+      "èħ ³",
+      "æ©¡ èĥ¶",
+      "éķ¿ å¾Ĺ",
+      "绿 åľ°",
+      "è¢ į",
+      "çļĦ èīºæľ¯",
+      "女 æľĭåıĭ",
+      "ä¸Ń è¶ħ",
+      "离 åŃIJ",
+      "å¤ļæł· åĮĸ",
+      "éĺ³ åı°",
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+      "ä¸Ģ ç±»",
+      "çŃīæĸ¹éĿ¢ çļĦ",
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+      "羣 çIJĨ",
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+      "æľĢ æľī",
+      "è¿ĻäºĽ éĥ½æĺ¯",
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+      "æįIJ 款",
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+      "ç¾İ æĻ¯",
+      "è¿ĺ 羣",
+      "æĭ¥ æĬ±",
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+      "注 å®ļ",
+      "å§IJ 妹",
+      "åĮº åĨħ",
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+      "æļĹ ç¤º",
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+      "æħ° éĹ®",
+      "å¸Ĥåľº 份é¢Ŀ",
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+      "éĩij åĪļ",
+      "大 声",
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+      "çļĩ åIJİ",
+      "åĽ½ ä¼ģ",
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+      "ç¼ĸ åĨĻ",
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+      "åĴĮ åľ°åĮº",
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+      "çĶ» 家",
+      "æľ¬ çĿĢ",
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+      "审 çIJĨ",
+      "ä¸Ģ åIJij",
+      "åıijå±ķ è¶ĭåĬ¿",
+      "åĮº éĹ´",
+      "注åĨĮ èµĦæľ¬",
+      "çIJ ¦",
+      "ä¸į åı¯ä»¥",
+      "çļĦ åĦ¿åŃIJ",
+      "åĢ¼ çıŃ",
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+      "ç«ĭ 马",
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+      "å°ı åŃIJ",
+      "管çIJĨ ç³»ç»Ł",
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+      "äºĮæīĭ 车",
+      "åİ¿ å§Ķ",
+      "èīº 人",
+      "å¥ ķ",
+      "è¿İ æĿ¥äºĨ",
+      "ç»ĵæĿŁ äºĨ",
+      "çļĦ ä¼łç»Ł",
+      "æĭ¼ æIJı",
+      "奥 迪",
+      "çĸij æĥij",
+      "ä¹ĭ æĹ¥èµ·",
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+      "åľ° åįĢ",
+      "è¯ł éĩĬ",
+      "åĪ° æľŁ",
+      "åħ¨ éĥ½",
+      "çŁŃ æļĤ",
+      "æĺ¯ æĪijåĽ½",
+      "æĪij å·²ç»ı",
+      "æ»´ æ»´",
+      "天 èµĭ",
+      "对 她",
+      "åį«çĶŁ éĹ´",
+      "çĶŁäº§ åŁºåľ°",
+      "æĹ¥ è®°",
+      "çļĦ æķĻåѦ",
+      "åĵ ĩ",
+      "æ°ij äºĭ",
+      "è¿ĺ åİŁ",
+      "æīĭ ä¸ŃçļĦ",
+      "çļĦ èī¯å¥½",
+      "æ· «",
+      "ä¸Ńåħ± ä¸Ń央",
+      "åĪ ĥ",
+      "åĵ Ħ",
+      "åľ¨ ä»ĸçļĦ",
+      "å°Ī æ¥Ń",
+      "åľº éĿ¢",
+      "éĤ» å±ħ",
+      "çĹ Ĵ",
+      "å¦ Ħ",
+      "å¤ĸ ç§ij",
+      "ä¸į éĢĤ",
+      "举åĬŀ çļĦ",
+      "é Ĥ¹",
+      "åħļçļĦ 建设",
+      "çĻ¼ 表",
+      "è·¨ çķĮ",
+      "æ²ī æ·Ģ",
+      "大 çīĩ",
+      "è¶Ĭ é«ĺ",
+      "å°Ĩ æĺ¯",
+      "è§ī éĨĴ",
+      "åĤ¨ åŃĺ",
+      "å¢ŀ 大",
+      "ä¸į 让",
+      "æķ´ å½¢",
+      "å¹³åı° ä¸Ĭ",
+      "åĩł ä½į",
+      "è¯ī æ±Ĥ",
+      "好 ä¸į好",
+      "åľ į",
+      "æĸĩ æľ¬",
+      "éĢ² åħ¥",
+      "ç´ į",
+      "æł¹ æĵļ",
+      "èįī æ¡Ī",
+      "åħŃ ä¸ª",
+      "åĭ ¿",
+      "åĪ¶ æĪIJ",
+      "饮 水",
+      "æ°¸ æģĴ",
+      "èĩª æĿĢ",
+      "åı¸ 马",
+      "éļ¾ çĤ¹",
+      "为 æĪij们",
+      "å¼ §",
+      "åī© ä¸ĭçļĦ",
+      "åĩĨå¤ĩ 好",
+      "çļĦ æľĢä½³",
+      "èģĶåIJĪ ä¼ļ",
+      "æĤ£èĢħ çļĦ",
+      "æĪijä¸į çŁ¥éģĵ",
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+      "åıijå±ķ æĸ¹åIJij",
+      "ç¬ ¨",
+      "æīĢ以 æĪij们",
+      "åĨĻ äºĨ",
+      "éĢł æĪIJäºĨ",
+      "æ²Ļ æ¼ł",
+      "çŃĽ éĢī",
+      "çģ¾ åĮº",
+      "ä¸Ĭ çľĭ",
+      "éħ ¶",
+      "æ»ļ åĬ¨",
+      "éļ¾ åħį",
+      "åIJī åĪ©",
+      "ä¸Ģ ä¸Ģ",
+      "ç²¾ å¯Ĩ",
+      "伸 æīĭ",
+      "礼 仪",
+      "åħ¨ æĺ¯",
+      "è¶Ĭ 大",
+      "ä¸Ń æłĩ",
+      "åıĸ åĨ³",
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+      "éĢĶ ä¸Ń",
+      "讨 åİĮ",
+      "æīĭ åĨĮ",
+      "第 ä¹Ŀ",
+      "åŃĶ åŃIJ",
+      "çĦ¶ å¾Į",
+      "ä¸Ģ åħ±",
+      "æµ· æĬ¥",
+      "款 å¼ı",
+      "æķ´ 天",
+      "è¾¹ çķĮ",
+      "è·¯ è¾¹",
+      "æĻĭ 级",
+      "åIJIJ 槽",
+      "çļĦ åħ³æ³¨",
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+      "å°±æĺ¯ åľ¨",
+      "缮 çļĦæĺ¯",
+      "åį³ä½¿ æĺ¯",
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+      "å®īåħ¨ éļIJæĤ£",
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+      "座 ä½į",
+      "èµ¢å¾Ĺ äºĨ",
+      "åİŁæĿ¥ çļĦ",
+      "身 为",
+      "书 åºĹ",
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+      "丧 失",
+      "çļĦ å±ĢéĿ¢",
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+      "å¤ĸ 表",
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+      "çĬ¯ç½ª å«Įçĸij",
+      "å°Ĩ 以",
+      "çİĩ é¢Ĩ",
+      "éħĴ åIJ§",
+      "è¡Įä¸ļ åıijå±ķ",
+      "å¹´ èĩ³",
+      "åĻ¨ æĿIJ",
+      "åĴĮ æĬĢæľ¯",
+      "æľĢ å°ı",
+      "è¿Ļä¸Ģ åĪĩ",
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+      "å½ĵ ä½ľ",
+      "æİĢ èµ·",
+      "åĴ ĭ",
+      "ä¸Ń éĥ¨",
+      "æīĭ èĩĤ",
+      "ç½¢ äºĨ",
+      "媳 å¦ĩ",
+      "æ´½ è°Ī",
+      "æĹ¶ä»£ ä¸ŃåĽ½",
+      "人çĶŁ çļĦ",
+      "æŀģ éĻIJ",
+      "ç¦ Ħ",
+      "åĮº æĶ¿åºľ",
+      "æľ¬ éĴ±",
+      "礼 åĵģ",
+      "çļĦ éĤ£ä¸ª",
+      "侦 æŁ¥",
+      "太å¤ļ çļĦ",
+      "å®ŀæĸ½ æĸ¹æ¡Ī",
+      "é«ĺ æłĩåĩĨ",
+      "æĮĩæĮ¥ éĥ¨",
+      "åĢ¾ æĸľ",
+      "çī¹èī² 社ä¼ļ",
+      "çµIJ æŀľ",
+      "éĴ» çŁ³",
+      "移 æ¤į",
+      "çī¹ ç§į",
+      "èĩª æĦ¿",
+      "æĭľ çĻ»",
+      "åįķ 身",
+      "åį´ åıĪ",
+      "åĪ¥ 人",
+      "åIJĪ è§Ħ",
+      "æľº çĶµ",
+      "çī¹ æĦı",
+      "å½ĵåīį ä½įç½®",
+      "买 家",
+      "åIJĪ 约",
+      "èĤ© èĨĢ",
+      "为 åĩĨ",
+      "家 è£ħ",
+      "çļĦ çĥŃæĥħ",
+      "éĿŀ éģĹ",
+      "çļĦ éŃħåĬĽ",
+      "åİŁ åijĬ",
+      "社ä¼ļ åIJĦçķĮ",
+      "ä¹° çļĦ",
+      "å¤ļ åIJĥ",
+      "éĽķ å¡ij",
+      "èµ· ä¹ī",
+      "åĬł åī§",
+      "éĤ£ä¸Ģ åĪ»",
+      "å°Ĩ è¿Ľä¸ĢæŃ¥",
+      "æ¡Ĥ æŀĹ",
+      "æĽ´ 强",
+      "对 ä¼ģä¸ļ",
+      "æĹł æĦı",
+      "ä¹łè¿ijå¹³ æĸ°",
+      "æµģ 失",
+      "微 软",
+      "缸 对äºİ",
+      "座è°Ī ä¼ļ",
+      "主 èIJ¥ä¸ļ",
+      "主èIJ¥ä¸ļ åĬ¡",
+      "ç§ģ åĭŁ",
+      "å±ķ示 äºĨ",
+      "常æĢģ åĮĸ",
+      "è² ´",
+      "符 åı·",
+      "å¹´è½» çļĦ",
+      "å°± éľĢè¦ģ",
+      "ä¹Ł æĽ¾",
+      "çļĦæĥħ 绪",
+      "è¾¾ æłĩ",
+      "èĩ ¨",
+      "ä½į å±ħ",
+      "ä»ħ 为",
+      "é¦ĸ 家",
+      "éĺ´ éĺ³",
+      "ä¸įåĨį æĺ¯",
+      "åĽłä¸º å®ĥ",
+      "ä¼ģä¸ļ åľ¨",
+      "çĺ ¾",
+      "åIJ¬ è§ģ",
+      "åİŁ æľī",
+      "åĪ¶ è£ģ",
+      "å¯Ĥ å¯ŀ",
+      "éĢļè¿ĩ 对",
+      "æ»ij éĽª",
+      "è¿Ļ å¼ł",
+      "çļĦ çIJĨ解",
+      "æĸ° ä¸ŃåĽ½",
+      "è¿Ļ åĦ¿",
+      "ä½İ ä»·",
+      "æĥ³ è¿ĩ",
+      "çļĦ ä¿¡å¿ĥ",
+      "建çŃij çī©",
+      "çļĦ é¢ľèī²",
+      "ä¸į åºĶ该",
+      "æĹłçĸij æĺ¯",
+      "å¼ķèµ· äºĨ",
+      "åħ¨ åijĺ",
+      "æĿ° åĩº",
+      "è¿Ļæĺ¯ æĪij",
+      "èª °",
+      "èĺ ĩ",
+      "éĺµ åľ°",
+      "åħħ åĢ¼",
+      "çŁ¿ ä¸ļ",
+      "çĿĢ ä»ĸ",
+      "信 访",
+      "ä¸ĩ è¾¾",
+      "æij© æĵ¦",
+      "å¼Ģ 端",
+      "èı² å¾ĭ",
+      "èı²å¾ĭ 宾",
+      "车 åŃIJ",
+      "æľ¬èº« çļĦ",
+      "çģ«è½¦ ç«Ļ",
+      "常 å·ŀ",
+      "为 代表",
+      "为代表 çļĦ",
+      "广 çĶµ",
+      "亲 人",
+      "åı³ æīĭ",
+      "éĽĨ è£ħ",
+      "éĽĨè£ħ ç®±",
+      "çļĦ åį°è±¡",
+      "æ©Ł æľĥ",
+      "åĮĨ åĮĨ",
+      "åħī çĶµ",
+      "大 æĸ¹",
+      "è¿ĺ æľª",
+      "åĪ© 好",
+      "ç»Ŀ 大å¤ļæķ°",
+      "åľ¨ è¿Ļç§į",
+      "ä¸Ģ ç»Ħ",
+      "æĸ° èĤ¡",
+      "转 åıij",
+      "æ³ķ åºŃ",
+      "æĹł æīĢ",
+      "éģĵ è·¯ä¸Ĭ",
+      "çŁ¿ å±±",
+      "èij ī",
+      "æĶ¶ åĽŀ",
+      "称 ä¹ĭ",
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+      "æıŃ éľ²",
+      "åı£ 岸",
+      "åIJ ¼",
+      "å¿ĥ æĥ³",
+      "çļĦ 梦æĥ³",
+      "éĽ ¯",
+      "ä¹ĭ åĪĿ",
+      "å¥ĸ 项",
+      "订 éĺħ",
+      "èĵĿ 天",
+      "åĿ¦ åħĭ",
+      "ç«ĭ æ¡Ī",
+      "èģĶ æīĭ",
+      "ä½Ĩæĺ¯ æĪij",
+      "帮 æĪij",
+      "ä»ħ 代表",
+      "说 æĪij",
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+      "æ¯Ķè¾ĥ 大",
+      "èµ° å»Ĭ",
+      "éĩįçĤ¹ é¡¹çĽ®",
+      "èµĮ åľº",
+      "åIJį çīĩ",
+      "æĦŁ åı¹",
+      "åľ¨ åľ°ä¸Ĭ",
+      "åıij çĥŃ",
+      "èĮĥ çķ´",
+      "çļĦ éģĵè·¯",
+      "éĩij èī²",
+      "ä»ĸ åıĪ",
+      "ä¼ļ 产çĶŁ",
+      "æ°ij åĽ½",
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+      "ç»Ĩ èħ»",
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+      "æĸ ĭ",
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+      "åį³ 便æĺ¯",
+      "çݰ代 åĨľä¸ļ",
+      "æ¯Ķè¾ĥ é«ĺ",
+      "è¦ģ çľĭ",
+      "没 äºĨ",
+      "解 決",
+      "çݯ æ¯Ķ",
+      "åĨ² åĬ¨",
+      "æ·± å¤ľ",
+      "åĩł åįĥ",
+      "ä¿ ı",
+      "ç½ij æ°ij",
+      "就 没",
+      "ä»ĸ 表示",
+      "éĩı åŃIJ",
+      "æĹ©é¤IJ åĬłçĽŁ",
+      "åįĬ å²Ľ",
+      "æIJŀ ç¬ij",
+      "ä¸Ĭ æĬ¥",
+      "å¯ ©",
+      "é¢Ħ 订",
+      "èľĤ èľľ",
+      "æŁ¥ æī¾",
+      "ä¼Ĺ æīĢ",
+      "ä¼ĹæīĢ åij¨",
+      "ä¼ĹæīĢåij¨ çŁ¥",
+      "æĹ© æĹ¥",
+      "åıij æī¬",
+      "åĴĮ 个人",
+      "åĬłåħ¥ äºĨ",
+      "åĸ® ä½į",
+      "åĪĨ æĺİ",
+      "第ä¸Ģ æī¹",
+      "ç¾İ åĨĽ",
+      "æĿĢ æīĭ",
+      "éŨ å¤ĸ",
+      "åķĨ åľĪ",
+      "ä¸Ģ åĪ»",
+      "çļĦçľ¼ ç¥ŀ",
+      "éľ Ħ",
+      "äºĽ ä»Ģä¹Ī",
+      "åĬł æ·±",
+      "æ¯ı ä½į",
+      "å¸Ĥ éĿ¢ä¸Ĭ",
+      "åıĶ åıĶ",
+      "çļĦ éĤ£ç§į",
+      "粤 港澳",
+      "è´´ å¿ĥ",
+      "æĸĩåĮĸ 产ä¸ļ",
+      "红 æĹĹ",
+      "åĺī åħ´",
+      "æĶ¶ çĽĺ",
+      "å®ĮæĪIJ åIJİ",
+      "ä¼ģä¸ļ 管çIJĨ",
+      "纵 横",
+      "ä¸į ä¿¡",
+      "æĪIJ éĥ½å¸Ĥ",
+      "æ´Ĺ 澡",
+      "举è¡Į çļĦ",
+      "çĶ¢ çĶŁ",
+      "ç©¿ ä¸Ĭ",
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+      "åħī 线",
+      "æīĵ æŀ¶",
+      "è¿Ļ æľ¬ä¹¦",
+      "åĶ®åIJİ æľįåĬ¡",
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+      "ä¸Ĭ 次",
+      "ä¸į åĪĨ",
+      "产 åIJİ",
+      "éģ¿ å¼Ģ",
+      "ç»Ī æŀģ",
+      "代表 大ä¼ļ",
+      "æ¼Ķ æĬĢ",
+      "åĽŀ è´Ń",
+      "åѦ è´¹",
+      "éĺ» ç¢į",
+      "ä¸Ģ大 æī¹",
+      "ç«£ å·¥",
+      "åĨ³ å®ļäºĨ",
+      "ä½Ĩ å¦Ĥæŀľ",
+      "çĶµ æµģ",
+      "ä¸Ŀ 毫",
+      "èĥ½å¤Ł åľ¨",
+      "éĶĢåĶ® æĶ¶åħ¥",
+      "åľ¨ åŃ¦æł¡",
+      "æ°´ åĩĨ",
+      "è§Ĩ 线",
+      "èĩª åľ¨",
+      "åķĨä¸ļ éĵ¶è¡Į",
+      "为äºĨ 让",
+      "çį² å¾Ĺ",
+      "çݩ家 æľĭåıĭ",
+      "éĿ¢ èĨľ",
+      "åĪĨ åī²",
+      "åī§ æľ¬",
+      "ç« Ń",
+      "说 å¾Ĺ",
+      "æĥ³ çŁ¥éģĵ",
+      "çļĦ人 çī©",
+      "èĮħ åı°",
+      "åIJĮ ä¸Ģ个",
+      "æķ°æį® ä¸Ńå¿ĥ",
+      "çĶ Ħ",
+      "åĸľ æĤ¦",
+      "ä¸ĭæĿ¥ çļĦ",
+      "å®ļ åIJij",
+      "æŀģ åħ·",
+      "çļĦ åľŁåľ°",
+      "éĤ£ åĢĭ",
+      "æijĦ åħ¥",
+      "äºĨ æĪijçļĦ",
+      "马 路",
+      "åħ¨ 社ä¼ļ",
+      "è®® æ¡Ī",
+      "å±ĭ åŃIJ",
+      "åIJį åı«",
+      "åĮ ª",
+      "åľ¨ å¤ĸéĿ¢",
+      "åįİ åįĹ",
+      "åıij è´§",
+      "å¯Ĵ åĨ·",
+      "é«ĺçŃī æķĻèĤ²",
+      "详ç»Ĩ çļĦ",
+      "个 é¡¹çĽ®",
+      "çĶŁäº§ åĬĽ",
+      "æŶ 常",
+      "å°± æľĥ",
+      "ä¸ĩ èĤ¡",
+      "éĻĮçĶŁ 人",
+      "æıı ç»ĺ",
+      "å½ĵ çĦ¶æĺ¯",
+      "æĭī åĬ¨",
+      "éĵ¾ æĿ¡",
+      "æī£ éĻ¤",
+      "ä¸Ģ缴 éĥ½",
+      "å°ı åŃ©åŃIJ",
+      "伤 åı£",
+      "第äºĮ å±Ĭ",
+      "è´Ń ç½®",
+      "çļĩ 马",
+      "æĹł èģĬ",
+      "表 åĨ³",
+      "诸 å¦Ĥ",
+      "åĵį èµ·",
+      "é£İ æļ´",
+      "ä¸Ģæµģ çļĦ",
+      "ç ·¨",
+      "解æĶ¾ åĨĽ",
+      "室 å¤ĸ",
+      "å°± è¿Ļä¹Ī",
+      "å³ ¶",
+      "æīĢæľī 人éĥ½",
+      "æIJľç´¢ å¼ķæĵİ",
+      "çļĦ æĪIJæľ¬",
+      "åħļ æĶ¿",
+      "åıijè¡Į 人",
+      "çļĦ äºĭå®ŀ",
+      "对 该",
+      "åıĹ æįŁ",
+      "ä¿Ħ ä¹Į",
+      "é²ľ èĬ±",
+      "åĨľ èį¯",
+      "æŀģ éĢŁ",
+      "æĢ¥ æĢ§",
+      "两 ä¼ļ",
+      "ä¸ĢèĪ¬ æĿ¥è¯´",
+      "æµ· é²ľ",
+      "åĨ Ī",
+      "çĶ¨ 人",
+      "çĶ¨äºº åįķä½į",
+      "åĢ ª",
+      "åĦª æĥł",
+      "æł¹ æºIJ",
+      "åĽ¢ è´Ń",
+      "ç¾İ æ´²",
+      "ä¸ĭ è¡Į",
+      "å¹´ æľ«",
+      "èľ ¡",
+      "è¯ģ 件",
+      "åľ¨ æĪijåĽ½",
+      "ä¸į åºĶ",
+      "æĮī æŶ",
+      "åłª 称",
+      "åľº ä¸Ĭ",
+      "å¹²éĥ¨ èģĮå·¥",
+      "æľī å¾Ī大çļĦ",
+      "æķ°åŃĹ ç»ıæµİ",
+      "æ¼Ķ ç»ĥ",
+      "æį® ç»Łè®¡",
+      "å¾Ģ æĿ¥",
+      "广åijĬ æľįåĬ¡",
+      "çļĦ è·Ŀ离",
+      "æŃ ¸",
+      "è¨Ģ è¯Ń",
+      "被 èªī",
+      "被èªī 为",
+      "åĭī 强",
+      "å°Ĭ æķ¬",
+      "ä¸ĩ 亿åħĥ",
+      "ä¸ŃåĽ½ åĽ½éĻħ",
+      "å¹² é¢Ħ",
+      "年 产",
+      "èĢķ åľ°",
+      "èĮ İ",
+      "åį³ æĺ¯",
+      "æĺ¨ æĻļ",
+      "æĪIJ为 ä¸Ģ个",
+      "çºł æŃ£",
+      "åij½ åIJį",
+      "é¢ģ å¸ĥ",
+      "çĮľ æµĭ",
+      "ä¿ĿèŃ· æĶ¿çŃĸ",
+      "æĭ ¢",
+      "æ´» æ³¼",
+      "çŃī éĥ¨éŨ",
+      "åѦ åĪ°",
+      "å¢ŀåĢ¼ ç¨İ",
+      "èĪª 线",
+      "åĨ ¤",
+      "åįģ åĩłå¹´",
+      "æݧèĤ¡ èĤ¡ä¸ľ",
+      "ä¸Ģ éŨ",
+      "个 å·¥ä½ľ",
+      "ä¸ªå·¥ä½ľ æĹ¥",
+      "æĸ° 西",
+      "æĸ°è¥¿ åħ°",
+      "论 è¯ģ",
+      "ä» Ĩ",
+      "åı¦å¤ĸ ä¸Ģ个",
+      "æĶ¹ ç¼ĸ",
+      "严 ç¦ģ",
+      "åĸľ 好",
+      "个人 ä¿¡æģ¯",
+      "满æĦı 度",
+      "åĵ ¨",
+      "å¸Ī èµĦ",
+      "æĶ¹ 为",
+      "ç«ŀäºī 对æīĭ",
+      "åĩº çĤī",
+      "åķĨ 人",
+      "大 æ£ļ",
+      "æĮĩ导 ä¸ĭ",
+      "å¦ĩ ç§ij",
+      "è¼ ª",
+      "æī ģ",
+      "åIJĮæŶ è¿ĺ",
+      "并 éĢļè¿ĩ",
+      "æĪĺ éĺŁ",
+      "èĶĵ 延",
+      "ä¿ ŀ",
+      "éĢĤå½ĵ çļĦ",
+      "åīį è¾Ī",
+      "åĵģ åij³",
+      "湿 åľ°",
+      "æĪIJ åŀĭ",
+      "ä¸į åıªæĺ¯",
+      "æĥ© ç½ļ",
+      "åĩºåı° äºĨ",
+      "çİ© 游æĪı",
+      "æīį åıijçİ°",
+      "åºĶ èģĺ",
+      "å¤ĸ æĿ¥",
+      "åįł é¢Ĩ",
+      "å±ķ æľĽ",
+      "å« Ĥ",
+      "港 èĤ¡",
+      "æ¡Į ä¸Ĭ",
+      "æĶ¯ æŁ±",
+      "çļĦæĥħ å½¢",
+      "广éĺĶ çļĦ",
+      "æĶ¯ è¡Į",
+      "å´© æºĥ",
+      "æľĪ ä¸Ń",
+      "æľĪä¸Ń æŬ",
+      "ç»į åħ´",
+      "临 è¿ij",
+      "æĬ¤ æłı",
+      "æļ ®",
+      "åįķ èģĮä¸ļ",
+      "è¾¹ å¢ĥ",
+      "æĹ¥ çħ§",
+      "ä¸Ģ åłĨ",
+      "缴 å¾Ħ",
+      "åħ±åIJĮ ä½ĵ",
+      "æĸ°åįİ ç½ij",
+      "æīĵ 好",
+      "çĶµåĬ¨ 汽车",
+      "ä¸į æĺİçĻ½",
+      "éĢĻ 裡",
+      "缼 大",
+      "çİĭ æľĿ",
+      "åĨį ä¸Ģ次",
+      "åĬŀåħ¬ åİħ",
+      "è´¨ æĬ¼",
+      "åIJĪ åĩ»",
+      "人们 对",
+      "鼶 é£Ł",
+      "éĥ½ä¸į çŁ¥éģĵ",
+      "çļĦ è¯Ńè¨Ģ",
+      "åĭŁéĽĨ èµĦéĩij",
+      "åĬ¨ èĦī",
+      "å½ ¤",
+      "è¿Ļ åĩłå¹´",
+      "çŁŃ è§Ĩé¢ij",
+      "太 é«ĺ",
+      "常 å§Ķä¼ļ",
+      "åĬł çıŃ",
+      "éĩį å¿ĥ",
+      "åªĴä½ĵ æĬ¥éģĵ",
+      "没 æ³ķ",
+      "éĹ» åIJį",
+      "çĥŃ åº¦",
+      "å¹¿æ³Ľ çļĦ",
+      "åħŃ å¤§",
+      "çī© ä½ĵ",
+      "ä¸į 该",
+      "é¢ĺ 主",
+      "精彩 çļĦ",
+      "为 è¿Ľä¸ĢæŃ¥",
+      "èĻ ŀ",
+      "åĽº çĦ¶",
+      "è´µå·ŀ çľģ",
+      "çºł ç»ĵ",
+      "代çIJĨ 人",
+      "æ³ķå®ļ 代表",
+      "åı¦ä¸Ģ ç§į",
+      "ä¸į åIJ«",
+      "æĭ¯ æķij",
+      "ä¼ļ ç»Ļ",
+      "è¯Ĺ è¯į",
+      "åIJĮ ç±»",
+      "å¾Ĺ ä¸įåĪ°",
+      "æĬĵ ç´§",
+      "以 åħ¶",
+      "åħ¥ åħļ",
+      "è¿ĺ åı¯",
+      "æľŁ åĪĬ",
+      "å¾Īå¤ļ æŶåĢĻ",
+      "æĹ¥ åIJİ",
+      "åħ¬ 约",
+      "ä¸Ģ 举",
+      "æ¯Ķè¾ĥ å¤ļ",
+      "éĩij æ²Ļ",
+      "æį ŀ",
+      "æİĴ åĩº",
+      "æѦ æľ¯",
+      "ä¸į æĸ·",
+      "ä¸Ń èĢĥ",
+      "ä¿¡ èµĸ",
+      "ä»İä¸ļ 人åijĺ",
+      "çģ« çĦ°",
+      "éĨĴ æĿ¥",
+      "ä½İ 温",
+      "éĢ¾ æľŁ",
+      "åĬ± å¿Ĺ",
+      "éħ ¥",
+      "åı¯è°ĵ æĺ¯",
+      "è¿Ļ æĦıåij³çĿĢ",
+      "é¢ł è¦Ĩ",
+      "åĮĹ京 大åѦ",
+      "ä¸ĵ 线",
+      "åıĬ 以ä¸Ĭ",
+      "è¨ ª",
+      "èĢĮ åIJİ",
+      "çŁ¥ ä¹İ",
+      "ä¸Ģ对 ä¸Ģ",
+      "å¨ĥ å¨ĥ",
+      "çģ¾ éļ¾",
+      "åħ¨ å±Ģ",
+      "æīĢå¾Ĺ ç¨İ",
+      "å®ŀ æĥł",
+      "èļĤ èļģ",
+      "ä¹Ł çŁ¥éģĵ",
+      "温 åĴĮ",
+      "èIJ½ ä¸ĭ",
+      "åŀĭ ä¼ģä¸ļ",
+      "åĨį ä¹Ł",
+      "ä¾Ľ çĥŃ",
+      "é«ĺ æ½®",
+      "çĢı覽 åĻ¨",
+      "çļĦ 巨大",
+      "åħĪ 天",
+      "å¹´ ä¸ŃåĽ½",
+      "类似 çļĦ",
+      "çIJĨäºĭ ä¼ļ",
+      "空 éĸĵ",
+      "çģµ æĦŁ",
+      "åĬĽ æ°Ķ",
+      "带 ä¸Ĭ",
+      "ä¸į好 æĦıæĢĿ",
+      "æľī ä½ķ",
+      "å·² åľ¨",
+      "åıĸ åĩº",
+      "è¿Ŀæ³ķ çĬ¯ç½ª",
+      "åŃ¦ä¹ł 贯彻",
+      "åľ° 带",
+      "楼 梯",
+      "çŃī æĥħåĨµ",
+      "ä»İ åīį",
+      "çļĦ ä¹łæĥ¯",
+      "ç³Ł ç³ķ",
+      "å°± èĥ½å¤Ł",
+      "è© ķ",
+      "ä¸Ģ å¾ĭ",
+      "æĮ« æĬĺ",
+      "åİŁæĸĩ åľ°åĿĢ",
+      "å½ĵ å±Ģ",
+      "ä¸į éĢļ",
+      "æķ° åįĥ",
+      "éĺŁä¼į 建设",
+      "æŶ èĬĤ",
+      "åģļ èµ·",
+      "çļĦ è®°å¿Ĩ",
+      "ç½ij绾 å®īåħ¨",
+      "åĩ¡ æĺ¯",
+      "æ° ¯",
+      "éĽķ åĪ»",
+      "åŁĥ åıĬ",
+      "æĪij åı¯ä»¥",
+      "çĽij çIJĨ",
+      "æĽ´ åħ·",
+      "åŁİ 管",
+      "èĭ ¯",
+      "åı¥ åŃIJ",
+      "èĭ¥ æľī",
+      "ä»İæĿ¥ ä¸į",
+      "缸åħ³ è´Łè´£",
+      "å®īåħ¨ æĦŁ",
+      "æĽ´ è¦ģ",
+      "çļĦæĥħ æĦŁ",
+      "çī¢ çī¢",
+      "è¾ĥ 好çļĦ",
+      "æ° ®",
+      "ç¬ij è¯Ŀ",
+      "车 å±ķ",
+      "ä¹ĭ ç¾İ",
+      "ç®Ģ 约",
+      "ç±»åŀĭ çļĦ",
+      "èĢģ åĮĸ",
+      "çľĭ ä½ł",
+      "è¿ĩ åĪĨ",
+      "éŨ åīį",
+      "ä¸Ģ éĹ´",
+      "æĥ³ åİ»",
+      "åª Ľ",
+      "åľŁ è±Ĩ",
+      "åıĪ 称",
+      "ä¸Ń ä¿¡",
+      "åŃĺ éĩı",
+      "马 äºij",
+      "èĩ´ 使",
+      "åħĪ åīį",
+      "èĢģ åŃIJ",
+      "æīĵ æī®",
+      "æ¯ķä¸ļ äºİ",
+      "æ¯ķä¸ļ åIJİ",
+      "ç¾İ好 çĶŁæ´»",
+      "å·¥ä¸ļ ä¼ģä¸ļ",
+      "就好 äºĨ",
+      "èħIJ èļĢ",
+      "çıį çıł",
+      "åĪ° è¿ĻéĩĮ",
+      "æīĢéľĢ çļĦ",
+      "è¿Ļæĺ¯ åĽłä¸º",
+      "çIJĨæĥ³ çļĦ",
+      "å·®å¼Ĥ åĮĸ",
+      "é ®",
+      "é® ®",
+      "äºļ 太",
+      "æĹł ç©·",
+      "æıIJ çİ°",
+      "ä¸ĵä¸ļ æĬĢæľ¯",
+      "çĶ¢ æ¥Ń",
+      "åѦ åŃIJ",
+      "ç§ij å¹»",
+      "åįłåľ° éĿ¢ç§¯",
+      "ä¸į åĩĨ",
+      "æľªæĪIJ 年人",
+      "æĶ¶ å½ķ",
+      "è¿ĺ 款",
+      "éĴ¢ çŃĭ",
+      "æ¼ ¢",
+      "å¾Ĺ æĦı",
+      "综åIJĪ ä½ĵ",
+      "æŀģ é«ĺ",
+      "åįķ è¯į",
+      "é«ĺæķĪ çļĦ",
+      "骨 头",
+      "æī§ çĿĢ",
+      "缼 ä¸ĸ",
+      "模 çī¹",
+      "æĽ´ èĥ½",
+      "ç»Ŀ æľĽ",
+      "对åºĶ çļĦ",
+      "æ¨ Ĭ",
+      "æĸ° ä¸ī",
+      "æĸ°ä¸ī æĿ¿",
+      "æģ° æģ°",
+      "åIJį 家",
+      "æł¸å¿ĥ æĬĢæľ¯",
+      "个 å°ı",
+      "æĢİä¹Ī ä¼ļ",
+      "说 ä¸įå®ļ",
+      "西 çĵľ",
+      "åĵ İ",
+      "ç¢ Ł",
+      "å¿ħ ä¸įåı¯",
+      "å¿ħä¸įåı¯ å°ij",
+      "ä¹ĭ éĸĵ",
+      "åĪĨ 管",
+      "交éĢļ äºĭæķħ",
+      "å¼Ģ åĬŀ",
+      "å¾ģæ±Ĥ æĦıè§ģ",
+      "äº ¨",
+      "鼻åŃIJ éĥµ",
+      "鼻åŃIJéĥµ 件",
+      "ä¿¡æģ¯ æľįåĬ¡",
+      "ä½ł è§īå¾Ĺ",
+      "缴 è§Ĥ",
+      "å·² å®ĮæĪIJ",
+      "åĪĨ ä¼ļ",
+      "åĽŀ åįĩ",
+      "éļ »",
+      "好 人",
+      "äºĨ解 ä¸Ģä¸ĭ",
+      "åį« æµ´",
+      "æľĢ çĪ±",
+      "åºŀ 大",
+      "客 æĪ¿",
+      "çijŀ åħ¸",
+      "éĥ½ ä¸įæĺ¯",
+      "é¤ ¨",
+      "èĹ ī",
+      "çļĦ åIJĦ项",
+      "为 缮æłĩ",
+      "çļĦ è®¤çŁ¥",
+      "å½±åĵįåĬĽ çļĦ",
+      "夸 å¼ł",
+      "佩 æĪ´",
+      "æ±ĩ çİĩ",
+      "çļĦ çĪ±æĥħ",
+      "æĺ¥ é£İ",
+      "æĺ¯ æĪijçļĦ",
+      "æ¨ ¹",
+      "åįĬ å°ıæŶ",
+      "å±± åİ¿",
+      "å±± 西çľģ",
+      "èĢĮ è¿Ļ",
+      "æĽ´å¤ļ ä¿¡æģ¯",
+      "è¿ĺ æľīä¸ĢäºĽ",
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+      "å¹´ éĻIJ",
+      "éģĭ åĭķ",
+      "åıĮ çľ¼",
+      "è¦ģ ç´§",
+      "对 çŃĸ",
+      "åľº é¦Ĩ",
+      "çĻ¾ ç§ij",
+      "è¶Ĭ éĩİ",
+      "å¯Į åIJ«",
+      "大å¤ļæķ° 人",
+      "æľĢ å°ij",
+      "åı¬ åĶ¤",
+      "åħ¸ èĮĥ",
+      "åĨľ æľº",
+      "æŃ£ æĸĩ",
+      "åºĶçĶ¨ äºİ",
+      "æ·± èĢķ",
+      "ä¿ Ń",
+      "ä»Ģä¹Ī ä¸ľè¥¿",
+      "å¥Ĺ é¤IJ",
+      "å½ĵ éĢī",
+      "å·¦ æīĭ",
+      "è°ĥ çIJĨ",
+      "æĻļ é¤IJ",
+      "éļ¾ åħ³",
+      "åĩŃ è¯ģ",
+      "çĪ± 人",
+      "æĮĩ è´£",
+      "è´£ ç¼ĸ",
+      "çļĦä¸Ģ 款",
+      "éĵ ²",
+      "åįģ 个",
+      "èĢ »",
+      "æľįåĬ¡ åķĨ",
+      "åľ° çĭ±",
+      "è¿ŀ å¿Ļ",
+      "åĽ° æĥij",
+      "çļ ĵ",
+      "ä¸į åIJĥ",
+      "çİ°åľ¨ å·²ç»ı",
+      "çĽĺ çĤ¹",
+      "ä¸įåģľ åľ°",
+      "管çIJĨ 模å¼ı",
+      "è¿Ļ 段æŶéĹ´",
+      "æ¤ °",
+      "礼 åĮħ",
+      "æµģ 转",
+      "æī« çłģ",
+      "éĽĨä¸Ń åľ¨",
+      "æ±Ĥ åĬ©",
+      "åįĬ 个",
+      "å¿«éĢŁ å¢ŀéķ¿",
+      "å¾Ģ ä¸ĭ",
+      "è¯Ħ åĪĨ",
+      "å°± æĥ³",
+      "åķĨåĬ¡ éĥ¨",
+      "æľī éĹ®é¢ĺ",
+      "èİ· åĪ©",
+      "æ¯Ľ çĹħ",
+      "æĦŁ åºĶ",
+      "èī¯ æĢ§",
+      "åĪĨ æѧ",
+      "åĨ ī",
+      "æĪij们 çİ°åľ¨",
+      "è¦ģ åĬłå¼º",
+      "å·§ å¦Ļ",
+      "èŀº æĹĭ",
+      "åĪĩ æį¢",
+      "çĭ Ħ",
+      "顺 çķħ",
+      "å°¤åħ¶ æĺ¯åľ¨",
+      "èĬĿ 麻",
+      "éļ¾ è¿ĩ",
+      "æĹĹ å¸ľ",
+      "å¤į åį°",
+      "å¤įåį° 件",
+      "å¿ħ éľĢ",
+      "对å¤ĸ å¼ĢæĶ¾",
+      "éļ¾ åıĹ",
+      "åİŁæĿ¥ æĺ¯",
+      "ç®Ĺ äºĨ",
+      "é«ĺ å±±",
+      "离 èģĮ",
+      "çµĦ ç¹",
+      "çµĦç¹ Ķ",
+      "å±ģ èĤ¡",
+      "çĻ¾ 家",
+      "éģĩ ä¸Ĭ",
+      "æĺĶ æĹ¥",
+      "ä¸į 容",
+      "çĽij管 éĥ¨éŨ",
+      "主 æĦı",
+      "æµģ åŁŁ",
+      "è·Į å¹ħ",
+      "èĩ³ ä¸Ĭ",
+      "åĪ« 说",
+      "æĺ¯ æ¯Ķè¾ĥ",
+      "å®ıè§Ĥ ç»ıæµİ",
+      "å¸Ĥåľº 主ä½ĵ",
+      "污æŁĵ çī©",
+      "æķij æ²»",
+      "丰 æĶ¶",
+      "åŃĺ æĶ¾",
+      "åĩ Ħ",
+      "éĩij å±±",
+      "æį¢ äºĨ",
+      "ä¸ĵ 人",
+      "éĹľ æĸ¼",
+      "æĹ¢ è¦ģ",
+      "åĽ½ 足",
+      "éļ ĭ",
+      "åıį åĩ»",
+      "起 身",
+      "åħĪ æĺ¯",
+      "å¸ĮæľĽ èĥ½å¤Ł",
+      "åĪ¶ 订",
+      "åºĹ éĿ¢",
+      "åĸ Ģ",
+      "æķĻ ä½ł",
+      "éĻį 温",
+      "åĬĽ æ±Ĥ",
+      "ä¸ī çĻ¾",
+      "çī© ä»·",
+      "丢 失",
+      "å¢Ļ ä¸Ĭ",
+      "éĥ¨ 份",
+      "æł· æĿ¿",
+      "ä¹ĭ æĦı",
+      "ç½ij å°ıç¼ĸ",
+      "ä¸ĸ ä¸Ĭ",
+      "è°ĥ è¯ķ",
+      "污æŁĵ éĺ²æ²»",
+      "å½± éĻ¢",
+      "å®Įåħ¨ åı¯ä»¥",
+      "éĢļ åħ³",
+      "ä¹īåĬ¡ æķĻèĤ²",
+      "没æľī åĬŀæ³ķ",
+      "èĢ ¿",
+      "å¦ ³",
+      "æĹł æĥħ",
+      "å¾Ĺ çĽĬ",
+      "å¾ĹçĽĬ äºİ",
+      "æľŁ çĽ¼",
+      "娱ä¹IJ åľº",
+      "çĶ² æĸ¹",
+      "ä¸Ģ æ±½",
+      "çĹ °",
+      "çĸij ä¼¼",
+      "æĸ°æµª å¾®åįļ",
+      "强 è¡Į",
+      "å½ĵ ä»ĸ",
+      "èĥ º",
+      "çĶ¨æĪ· æıIJä¾Ľ",
+      "åĮº å§Ķ",
+      "æĦ¿ æĻ¯",
+      "æĬĺ æī£",
+      "失 踪",
+      "è¿« åĪĩ",
+      "åŃĹ æ¯į",
+      "åĴ ¯",
+      "èªį èŃĺ",
+      "ä»Ģä¹Ī æĦıæĢĿ",
+      "çĽĴ åŃIJ",
+      "å½ķ éŁ³",
+      "建设 å·¥ç¨ĭ",
+      "ä¸ļ ä½Ļ",
+      "å®ŀè·µ æ´»åĬ¨",
+      "羣 空",
+      "çĤ ĸ",
+      "åľ¨ è·¯ä¸Ĭ",
+      "主è¦ģ åĮħæĭ¬",
+      "该 æĢİä¹Ī",
+      "æĢ» æľī",
+      "æĢ§ æĦŁ",
+      "æ°ij èĪª",
+      "å¼Ģ åºĹ",
+      "欺 éªĹ",
+      "çªģ åĩ»",
+      "缺 失",
+      "æī§ ä¸ļ",
+      "åľ° éģĵ",
+      "并 æĹł",
+      "æ°ij åĬŀ",
+      "ç»Ħç»ĩ çĶŁæ´»",
+      "æĪij å¦Ī",
+      "è¨ĺ èĢħ",
+      "管 åĪ¶",
+      "æī¾ 个",
+      "èĹ »",
+      "çĤİ çĹĩ",
+      "äºĴ åĬ©",
+      "æµıè§Ī åĻ¨",
+      "çݩ家 æĿ¥è¯´",
+      "éĻįä½İ äºĨ",
+      "è£ Ķ",
+      "æĮ£ éĴ±",
+      "åķĨ æľº",
+      "æĶ¹ è£ħ",
+      "æµģ 浪",
+      "æĶ¿ æ³ķ",
+      "èĢģ 头",
+      "çĶŁäº§ åĴĮ",
+      "ç© Ĺ",
+      "亲 çĪ±",
+      "亲çĪ± çļĦ",
+      "å±¥ èģĮ",
+      "åŁİ éĩĮ",
+      "ç»Ĩ åĪĨ",
+      "åĬ³åĬ¨ åIJĪåIJĮ",
+      "åľ¨ æĹ¥æľ¬",
+      "å¨ģ å°Ķ",
+      "åį« è§Ĩ",
+      "éĢ£ çµIJ",
+      "çĿĢ éĩį",
+      "æĬĺ 磨",
+      "åĽ¾ 为",
+      "çľ ·",
+      "å·¥ åºı",
+      "æĵ ģ",
+      "æĵģ æľī",
+      "ç½ijç«Ļ åľ°åĽ¾",
+      "çļĦä¸Ģ 大",
+      "ç»Ħç»ĩ å®ŀæĸ½",
+      "æĬĽ å¼ĥ",
+      "åĴĮ æĶ¯æĮģ",
+      "æ³ķ åĪĻ",
+      "浪 潮",
+      "çİ° æľīçļĦ",
+      "åĩł çİĩ",
+      "为 客æĪ·",
+      "åįģ ä¸ĩ",
+      "è ¹Ħ",
+      "çªģåĩº éĹ®é¢ĺ",
+      "åıĥ åĬł",
+      "éĥ½ä¼ļ æľī",
+      "çĽ ¤",
+      "è°ģ éĥ½",
+      "æīĭ åĬ¨",
+      "缴 è¾¾",
+      "çĤ¹ å¤ļ",
+      "éĺ¶ å±Ĥ",
+      "ä¸į ä½³",
+      "éĤ£ 段",
+      "滨 海",
+      "æĺ¯ åĽ½åĨħ",
+      "æĪij å¸ĮæľĽ",
+      "åIJĽ åŃIJ",
+      "è§Ĥ éŁ³",
+      "åģļ é¥Ń",
+      "æ±½ è»Ĭ",
+      "åħ³ ç¨İ",
+      "çľ¼åīį çļĦ",
+      "æ°´ éĿ¢",
+      "èĢ³ æľº",
+      "追 踪",
+      "æݨ éĢģ",
+      "éĴ± åĮħ",
+      "æģ¶ å¿ĥ",
+      "æµ· åŁŁ",
+      "å· į",
+      "å¼Ģ æĿ¥",
+      "表 æĢģ",
+      "仪 表",
+      "å¹³ åİŁ",
+      "åįģ å¤ļå¹´",
+      "ä¹Ł æĹłæ³ķ",
+      "åħ¼ 顾",
+      "è¡£ æŁľ",
+      "æł½ åŁ¹",
+      "æĪ¿ æºIJ",
+      "设ç«ĭ äºĨ",
+      "ä¸ĩ åIJį",
+      "æķ° é¢Ŀ",
+      "è¦ģ åĿļæĮģ",
+      "åIJīæŀĹ çľģ",
+      "请 èģĶç³»",
+      "ç»ıåİĨ è¿ĩ",
+      "çļĦ æľ¬è´¨",
+      "åħ¥ éŨ",
+      "æľ¬ æ¡Ī",
+      "çİĩ è¾¾åĪ°",
+      "åı° éĺ¶",
+      "éĴ ŀ",
+      "æĪij èĥ½",
+      "èݲ èĬ±",
+      "éĴ ł",
+      "ä¸Ģ äºĭ",
+      "åİŁ æľīçļĦ",
+      "æ¯ı åĢĭ",
+      "æ¯Ķäºļ 迪",
+      "æ£ĭçīĮ 游æĪı",
+      "ä¸įä¼ļ æľī",
+      "å½Ĵ æĿ¥",
+      "äºĶ çĻ¾",
+      "è¿ĩ é«ĺ",
+      "鼷 è¾¾",
+      "ä¸Ģèµ· åİ»",
+      "æķĻ 导",
+      "å°± è¯Ĭ",
+      "å°± å¾Ī",
+      "ä¸įåIJĮ äºİ",
+      "ä¿ º",
+      "å¸ĸ åŃIJ",
+      "æĶ¿åįı å§Ķåijĺ",
+      "çĸ«æĥħ å½±åĵį",
+      "åĪĨ è£Ĥ",
+      "为ä»Ģä¹Ī ä¼ļ",
+      "äºĶ æĺŁ",
+      "å°ij åĦ¿",
+      "æĬ¢ éĻ©",
+      "梦 è§ģ",
+      "è®°èĢħ éĩĩ访",
+      "å±± è·¯",
+      "æĪij 个人",
+      "æ²Ļ 滩",
+      "è¹ Ń",
+      "æĶ¹ è®Ĭ",
+      "æĸ°åŀĭ åĨł",
+      "æĸ°åŀĭåĨł çĬ¶",
+      "åĮ» æĬ¤",
+      "åĮ»æĬ¤ 人åijĺ",
+      "æµ· å°Ķ",
+      "åħ³äºİ æĪij们",
+      "éĻ¤ å¤ĸ",
+      "åº ļ",
+      "宣 åijĬ",
+      "ä¸ī åįĥ",
+      "æ¦ ¨",
+      "ç§ijæĬĢ 大åѦ",
+      "ä¸ĥ åħ«",
+      "顺 åºĶ",
+      "çĪ¸çĪ¸ å¦Īå¦Ī",
+      "éĢī åıĸ",
+      "åī§ çĥĪ",
+      "乡æĿij æĹħ游",
+      "积æŀģ æݢ索",
+      "表çİ° 为",
+      "å¾Ī æ¸ħæ¥ļ",
+      "大 åĨĽ",
+      "æĿ¥ çĶµ",
+      "å¥Ĺ æĪ¿",
+      "çİ° è¡Į",
+      "享 åıĹåĪ°",
+      "çľĭ çĤ¹",
+      "åĽºå®ļ èµĦ产",
+      "以 人为",
+      "以人为 æľ¬",
+      "ä¸į å®Į",
+      "éĻį 鼨",
+      "åģļçļĦ äºĭæĥħ",
+      "并 äºİ",
+      "顽 强",
+      "èĢ ¸",
+      "åĺ´ å·´",
+      "缸åħ³ ä¿¡æģ¯",
+      "æĪij 没",
+      "æĪĺçķ¥ æĢ§",
+      "æĢĿ 念",
+      "åĪĺ å¤ĩ",
+      "åĬ© æĶ»",
+      "é£İ è²Į",
+      "éĿ¢å¯¹ éĿ¢",
+      "积æŀģ å¼Ģå±ķ",
+      "çĸĹ æķĪ",
+      "çľĭ 书",
+      "缺 åı£",
+      "åĽ½æ°ij ç»ıæµİ",
+      "使çĶ¨ æĿĥ",
+      "éģ¥ è¿ľ",
+      "å¡« è¡¥",
+      "第ä¸ī 人",
+      "åįĬ å¤ľ",
+      "æѦæ±ī å¸Ĥ",
+      "æĪij åıijçİ°",
+      "ä¼ĺæĥł æĶ¿çŃĸ",
+      "é£İ åı£",
+      "å°± ä¸įèĥ½",
+      "为 主è¦ģ",
+      "æµģ åĩº",
+      "å´ĩ æĭľ",
+      "并 ä¸įèĥ½",
+      "é«ĺ ä¸ī",
+      "ä¸ĸçķĮä¸Ĭ æľĢ",
+      "æĥ³ å¿ħ",
+      "åħ¶ æīĢ",
+      "åĢĻ éĢī",
+      "åĢĻéĢī 人",
+      "ä¸į çĪ±",
+      "åī¯ ä½ľçĶ¨",
+      "人æ°ij æĹ¥æĬ¥",
+      "æĪij ä¸įæĺ¯",
+      "å®ŀ çī©",
+      "çĶµ åİĤ",
+      "ä¹Ł ç®Ĺæĺ¯",
+      "æľī éĹľ",
+      "æľī èĥ½åĬĽ",
+      "æĮĤ åľ¨",
+      "çľ¼ ä¸ĭ",
+      "约 翰",
+      "å°ı åѦçĶŁ",
+      "èµ· åĪ°äºĨ",
+      "工 夫",
+      "åIJĮ å¿ĥ",
+      "åĿ¦ è¨Ģ",
+      "çł Į",
+      "åıijæĮ¥ äºĨ",
+      "èģĮä¸ļ éģĵå¾·",
+      "è¿ĻäºĽ å¹´",
+      "念 头",
+      "èĢģ é¼ł",
+      "åħ¨ èµĦ",
+      "åħ¨èµĦ åŃIJ",
+      "ä¸Ģ åij³",
+      "å¤ļ ä¸ĩåħĥ",
+      "æł¼ æľĥ",
+      "éķ¿ éĢĶ",
+      "带 走",
+      "èĭ± 寸",
+      "æĸĩ ä½ĵ",
+      "对 ä»ĸ们",
+      "åĵŃ äºĨ",
+      "å¡« æĬ¥",
+      "çīĪæĿĥ 声æĺİ",
+      "çĶµ 线",
+      "è´Ńçī© ä¸Ńå¿ĥ",
+      "饱 满",
+      "ä½İ 头",
+      "强 迫",
+      "ä¿Ŀ æ´ģ",
+      "欧 åĨł",
+      "缸 è¿ŀ",
+      "认 è´Ń",
+      "çģ« æĺŁ",
+      "é«ĺ å°Ķ",
+      "é«ĺå°Ķ 夫",
+      "èij« èĬ¦",
+      "æłĩ 注",
+      "çļĦ çIJĨæĥ³",
+      "æł¸ éħ¸",
+      "æł¸éħ¸ æ£Ģæµĭ",
+      "åĬ ī",
+      "ä¸ĢèĪ¬ æĺ¯",
+      "æĢĿ ç´¢",
+      "轨 迹",
+      "çĥŃ å¸¦",
+      "éĻ £",
+      "åĩĨç¡® æĢ§",
+      "æĪ´ çĿĢ",
+      "åľ¨ çĶŁæ´»ä¸Ń",
+      "æīĢ èĥ½",
+      "æľ¯ åIJİ",
+      "带 ä½ł",
+      "ç¥ ł",
+      "æ®ĭ éħ·",
+      "ä¹Ł åıªæĺ¯",
+      "çĶ³ è´Ń",
+      "举åĬŀ äºĨ",
+      "æľī æĦıä¹ī",
+      "æĹº 缼",
+      "åľ¨ 網",
+      "åľ¨ç¶² è·¯ä¸Ĭ",
+      "å¾Ī大 ç¨ĭ度",
+      "管 è¾ĸ",
+      "çĸ«æĥħ æľŁéĹ´",
+      "触 æij¸",
+      "éĺ¶æ®µ æĢ§",
+      "ä¼ļ è§īå¾Ĺ",
+      "çļĦ çĶ»éĿ¢",
+      "æİ¥åıĹ äºĨ",
+      "表达 äºĨ",
+      "éĤĵ å°ı",
+      "éĤĵå°ı å¹³",
+      "åħļ é£İ",
+      "åħļé£İ å»īæĶ¿",
+      "åķĨ åѦéĻ¢",
+      "åħij æį¢",
+      "é£Łåĵģ èį¯åĵģ",
+      "éĿŀ常 好çļĦ",
+      "çľ ¯",
+      "纳 米",
+      "åĬ¨ æijĩ",
+      "åĽŀ éģ¿",
+      "çľĭ èijĹ",
+      "款 项",
+      "åħ« å¹´",
+      "åģļ 个",
+      "æĸĩ æ¡£",
+      "éĩijèŀį ç§ijæĬĢ",
+      "åħ¶ä¸Ń æľī",
+      "äºĨä¸Ģ ç³»åĪĹ",
+      "æĹĹèĪ° åºĹ",
+      "称 èµŀ",
+      "éĽ¢ éĸĭ",
+      "åĪ¶ åĨ·",
+      "家 éŨåı£",
+      "åįģ å¤ļ",
+      "ä¼´ ä¾£",
+      "çľĭ çĹħ",
+      "æĭī çĿĢ",
+      "æī Ĵ",
+      "çĸ² æĥ«",
+      "å°ijæķ° æ°ijæĹı",
+      "åĽ¾ å½¢",
+      "è½ §",
+      "å¢ŀ éĩı",
+      "饲 åħ»",
+      "çģ« å±±",
+      "æ¯ı 个æľĪ",
+      "ä½ľä¸º ä¸ĢåIJį",
+      "è½´ æī¿",
+      "æĸĩ 书",
+      "ç¼ ķ",
+      "åħ·ä½ĵ æĥħåĨµ",
+      "çĹĽ çĤ¹",
+      "缴 éĶĢ",
+      "å¡ Ĭ",
+      "ä¹Ł æľĥ",
+      "çĥŃ æ½®",
+      "å¹³ æ°ij",
+      "æ¼ĶåĶ± ä¼ļ",
+      "æķĻ çłĶ",
+      "éĢĥ éģ¿",
+      "ä¸Ģ è´¯",
+      "å°± è¶Ĭ",
+      "å®ŀ å®ŀåľ¨",
+      "å®ŀå®ŀåľ¨ åľ¨",
+      "ä¹łè¿ijå¹³ æĢ»",
+      "æº º",
+      "å¿ĥ åºķ",
+      "éķ¿ å¾ģ",
+      "媽 媽",
+      "第ä¸ī 次",
+      "åĩº æ¼Ķ",
+      "çĭĢ æ³ģ",
+      "å°Ķ æĸ¯",
+      "代çIJĨ åķĨ",
+      "çĨ ı",
+      "çļĦ 对象",
+      "çĶµ éĩı",
+      "è¡Į åĪĹ",
+      "åĽ½ 人",
+      "è·ij äºĨ",
+      "åįĶ åĬ©",
+      "èIJ¥ è¿IJ",
+      "å¸Ī åħĦ",
+      "æ¦ ®",
+      "æĥ³ åĥı",
+      "æĢ§ 强",
+      "ç§ijåѦ çłĶ究",
+      "延 å®ī",
+      "ä¸¥æł¼ èIJ½å®ŀ",
+      "é¢Ĩ ä¼ļ",
+      "缸 å·®",
+      "路 人",
+      "çĶ «",
+      "æľī ä»·åĢ¼",
+      "æľīä»·åĢ¼ çļĦ",
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+      "ä¹ĭ ä½Ļ",
+      "åIJĮæŶ ä¹Łæĺ¯",
+      "ä¸ŃåĽ½ éĺŁ",
+      "建æĪIJ åIJİ",
+      "ä¹IJ è§Ĩ",
+      "åij¨ å²ģ",
+      "èį¯ åºĹ",
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+      "è´¨ åľ°",
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+      "åħµ åĻ¨",
+      "æķĻèĤ² æķĻåѦ",
+      "离 åİ»",
+      "åIJĦå¼ı åIJĦæł·",
+      "ä»ĭ ç´",
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+      "å¼Ģ 头",
+      "å°Ĩ èĩªå·±çļĦ",
+      "åIJ¬ åĬĽ",
+      "ä¿¡æģ¯ ç³»ç»Ł",
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+      "éĹ² ç½®",
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+      "ä¸İ æŶ",
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+      "楼 ä¸ĭ",
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+      "äºĭ åıij",
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+      "æµ Ĭ",
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+      "æľĿ å»·",
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+      "åĨ» ç»ĵ",
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+      "åº IJ",
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+      "åĮ»çĸĹ æľįåĬ¡",
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+      "æIJŀ 好",
+      "çļĦ èĦļæŃ¥",
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+      "åı° å·ŀ",
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+      "éĿ© æĸ°",
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+      "åIJĪ å½±",
+      "çĤº ä»Ģ麼",
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+      "çļĦ è¿ĽæŃ¥",
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+      "å½ĵä¹ĭ æĹł",
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+      "è´´ è¿ij",
+      "尺 度",
+      "åľ¨ çİ°åľº",
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+      "å¯ ħ",
+      "导 åħ¥",
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+      "鼷 éľĨ",
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+      "å»ł åķĨ",
+      "声 称",
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+      "å¸ĥ é²ģ",
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+      "两 çĤ¹",
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+      "èĹ į",
+      "弯 æĽ²",
+      "海 峡",
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+      "éĺ² çº¿",
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+      "羣 æĥħ",
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+      "天 é¹ħ",
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+      "æĹħ游 æĻ¯åĮº",
+      "æľī æĽ´å¤ļçļĦ",
+      "丰å¯Į å¤ļ彩",
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+      "åĩº å·®",
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+      "缸 å¹²",
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+      "åī§ åľº",
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+      "å¹³ æķ´",
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+      "åħ¨ä½ĵ åijĺå·¥",
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+      "åIJ¸ 纳",
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+      "æĻ® æŁ¥",
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+      "转 è¿IJ",
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+      "æĶ¹ èī¯",
+      "çĭł çĭł",
+      "åĨ² åĪº",
+      "æĸ° 京",
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+      "ç¥ŀ åĻ¨",
+      "秸 ç§Ĩ",
+      "çĪ º",
+      "å°Ĩ è¿İæĿ¥",
+      "å·¥ ä¿¡",
+      "工信 éĥ¨",
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+      "æIJ¬ è¿IJ",
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+      "åİ» è¿ĩ",
+      "èģĨ åIJ¬",
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+      "大 佬",
+      "åħ¨ 天",
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+      "åIJ ³",
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+      "èİ« æĸ¯",
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+      "天 åºľ",
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+      "积累 äºĨ",
+      "æ¡ Ķ",
+      "çĶ» çĶ»",
+      "ä¹Ł åºĶ该",
+      "åºĶçĶ¨ ç¨ĭåºı",
+      "èĥĥ èĤł",
+      "以 å¾Į",
+      "豪 å®ħ",
+      "æ·± åĬłå·¥",
+      "缴 è¨Ģ",
+      "åĮĸ çŁ³",
+      "åĽ½ éģĵ",
+      "ä¸ĥ 个",
+      "ä»İèĢĮ 使",
+      "èĤł èĥĥ",
+      "æĹ¥ è¶ĭ",
+      "çĪ¶ åŃIJ",
+      "ç· ©",
+      "æĭĽ çīĮ",
+      "产 å¦ĩ",
+      "çķª èĮĦ",
+      "æĪij éĻ¢",
+      "建çŃij å·¥ç¨ĭ",
+      "å±ķè§Ī ä¼ļ",
+      "家éķ¿ 们",
+      "åĨľ ä½ľçī©",
+      "æĹ¥ å¤ľ",
+      "æĶ» æĵĬ",
+      "è§Ħ éģ¿",
+      "èĪŁ å±±",
+      "便 æ°ij",
+      "åħ« åŃĹ",
+      "ä¸į æĽ¾",
+      "æĶ¯ éħį",
+      "çĨ¬ å¤ľ",
+      "人 é¡ŀ",
+      "ç´Ģ éĮĦ",
+      "ç»ıèIJ¥ æ´»åĬ¨",
+      "大 涨",
+      "å¸Ĥå§Ķ 常å§Ķ",
+      "åĪĨ éIJĺ",
+      "ä¸Ģ个 èģĮä¸ļ",
+      "çĹħ åĽł",
+      "è¿Ļ 对äºİ",
+      "ä¸įå¾Ĺä¸į 说",
+      "åıijçĶµ æľº",
+      "æľīæīĢ 帮åĬ©",
+      "缮æłĩ ä»»åĬ¡",
+      "åĽł åľ°",
+      "åĽłåľ° åĪ¶",
+      "åĽłåľ°åĪ¶ å®ľ",
+      "å°Ĩ è¾¾åĪ°",
+      "ç²Ĺ ç³Ļ",
+      "稳 åĽº",
+      "å« £",
+      "çİ°åľ¨ å¾Īå¤ļ",
+      "ä¸ĸçķĮ 级",
+      "å¼ł æŁIJ",
+      "çĤ¹ ç¼Ģ",
+      "èij µ",
+      "社ä¼ļ ç»Ħç»ĩ",
+      "å¾Ģ åIJİ",
+      "åĬł æģ¯",
+      "åĻª 声",
+      "æľī åħ´è¶£",
+      "为æĤ¨ æıIJä¾Ľ",
+      "æ²¹ æ¼Ĩ",
+      "ç¬¬åĽĽ å±Ĭ",
+      "çļĩ 宫",
+      "ä¹Ĵ ä¹ĵ",
+      "ä¹Ĵä¹ĵ çIJĥ",
+      "éļ¨ èijĹ",
+      "éģ© åIJĪ",
+      "åįĹ éĿŀ",
+      "æĵ ´",
+      "西 æ´ĭ",
+      "åĬł å¯Ĩ",
+      "æĪIJåĬŁ 举åĬŀ",
+      "åı£ æ°´",
+      "æĪIJ 年人",
+      "æīĢ æıIJä¾ĽçļĦ",
+      "éļĶ å£ģ",
+      "åľ¨ 京",
+      "å½ĵåľ° æŶéĹ´",
+      "çŃī åIJĦç§į",
+      "é£İ æ°Ķ",
+      "å±ĭ éĩĮ",
+      "ä¸Ģ åŃĹ",
+      "çļĦæŶéĹ´ éĩĮ",
+      "åĺ¿ åĺ¿",
+      "快 讯",
+      "ä¸Ń åľº",
+      "ä¸Ģ çĵ¶",
+      "æ» ķ",
+      "é¢Ĩ è·ij",
+      "好 èݱ",
+      "好èݱ åĿŀ",
+      "没 åħ³ç³»",
+      "åĩº å¢ĥ",
+      "ä¸įæĺ¯ ä¸Ģ个",
+      "éĥ½æĺ¯ éĿŀ常",
+      "éľĩ åĬ¨",
+      "èİ· èĥľ",
+      "åįļ å¼Ī",
+      "æĬļ åħ»",
+      "对 ç«ĭ",
+      "æľįåĬ¡ æľºæŀĦ",
+      "è°£ è¨Ģ",
+      "社ä¼ļ ç§ijåѦ",
+      "åIJ¬è¯´ è¿ĩ",
+      "æī ³",
+      "æīĵ 磨",
+      "åı£ æľį",
+      "好 åĥıæĺ¯",
+      "以åıĬ åħ¶ä»ĸ",
+      "çī¹ è´¨",
+      "亲 è¿ij",
+      "ä¸Ģ ç»ı",
+      "æ¶ Ŀ",
+      "éŃĶ æľ¯",
+      "éģĵè·¯ 交éĢļ",
+      "è§Ħ模 æľĢ大",
+      "å®ŀæĸ½ æĦıè§ģ",
+      "ä¹ ŀ",
+      "ä¸Ģ ä¸ĸ",
+      "åŁ· è¡Į",
+      "è±Ĩ çĵ£",
+      "åĪĹ ä¸º",
+      "æķħ 宫",
+      "çĶŁ åij½åij¨æľŁ",
+      "ä¸īç§į èģĮä¸ļ",
+      "详ç»Ĩ ä»ĭç»į",
+      "å®Į å¤ĩ",
+      "岩 çŁ³",
+      "éļı æīĭ",
+      "é£ ²",
+      "æķĪæŀľ åĽ¾",
+      "ç§ĭ åĨ¬",
+      "åĬŁ å¾·",
+      "è§Ħç«ł åĪ¶åº¦",
+      "æĹ¥ æ¸IJ",
+      "æīĢ éľĢè¦ģ",
+      "æīĢéľĢè¦ģ çļĦ",
+      "å²Ľ ä¸Ĭ",
+      "åĩº åľŁ",
+      "åĽ¾ æĸĩ",
+      "ç§ijæĬĢ è¿ĽæŃ¥",
+      "éĢļ èĥĢ",
+      "èĢģ 太太",
+      "èĭĹ æľ¨",
+      "éĵ¶ å·Ŀ",
+      "å¸IJ 篷",
+      "éĿŀ è¦ģ",
+      "éħį çĶµ",
+      "å¤Ħ å¢ĥ",
+      "èĤ¡æĿĥ æĬķèµĦ",
+      "ä¸Ģ缴 åĪ°",
+      "åĿĩ çĶ±",
+      "æĬĹ æĹ¥",
+      "æį® ä»ĭç»į",
+      "ä½ł åĸľæ¬¢",
+      "åĪĽæĸ° åŀĭ",
+      "åıĺ è¿ģ",
+      "è§Ĩ å¯Ł",
+      "å®Įåħ¨ 没æľī",
+      "åħĥ æŦ",
+      "åı¯ ä¿¡",
+      "åı¦ è¡Į",
+      "æĿij 级",
+      "åħ¥ åľº",
+      "æIJŃ æ¡£",
+      "ä¹Ł åĽłæѤ",
+      "æį¢ æĪIJ",
+      "ä¸į è´Ł",
+      "äºĨ 大éĩıçļĦ",
+      "éģĶ åĪ°",
+      "å¸Ĥ åİ¿",
+      "å¹´ è¼ķ",
+      "å¿« æīĭ",
+      "å¸Į å°Ķ",
+      "èĩª èIJ¥",
+      "éĽª èĬ±",
+      "æIJ ģ",
+      "çľ¼ ç§ij",
+      "æŃ£ 確",
+      "çļĦ 姿æĢģ",
+      "åĿļå®ŀ çļĦ",
+      "æĮĩ 纹",
+      "æªĶ æ¡Ī",
+      "ç½® äºİ",
+      "佩 æľį",
+      "豪 éŨ",
+      "åĵ Ĵ",
+      "æģ° 好",
+      "檢 æŁ¥",
+      "åĪĿ è¡·",
+      "大 åĶIJ",
+      "约 ä¼ļ",
+      "èĴ¸ åıij",
+      "çŃ¹ åĪĴ",
+      "å¹´ ç»Ī",
+      "è¡Į æ¥Ń",
+      "åħ± éĿĴ",
+      "åħ±éĿĴ åĽ¢",
+      "ä¼ļ å¼ķèµ·",
+      "ä¸Ń ç§ij",
+      "ä¸Ńç§ij éĻ¢",
+      "æĮ¯ åĬ¨",
+      "åį´ åıijçİ°",
+      "ä¸įåĬ¨ 产",
+      "èĮ ¹",
+      "æĪ¿éĹ´ éĩĮ",
+      "è´§å¸ģ æĶ¿çŃĸ",
+      "æ²» çĻĤ",
+      "æħİ éĩį",
+      "å¡ŀ å°Ķ",
+      "åĽ½ ç±į",
+      "åĽł æŀľ",
+      "çŃī çī¹çĤ¹",
+      "å±± è°·",
+      "ä¸ĭ è¼ī",
+      "è®ĵ æĪij",
+      "饮 éħĴ",
+      "è¿Ļ个 游æĪı",
+      "ç»Ŀ 大éĥ¨åĪĨ",
+      "åĴ¨è¯¢ æľįåĬ¡",
+      "å¹² æ´»",
+      "è®® ä¼ļ",
+      "æ¦Ĥ è¿°",
+      "åĪĨ åĮº",
+      "æŃ» åIJİ",
+      "ç«Ļ çĿĢ",
+      "主è¦ģ é¢Ĩ导",
+      "åIJĮ åŁİ",
+      "大 æłij",
+      "对 åѦçĶŁ",
+      "社ä¼ļ ä¿ĿéĻ©",
+      "å¢ŀ èµĦ",
+      "主人 åħ¬",
+      "å®£ä¼ł æķĻèĤ²",
+      "æĸĩåĮĸ 交æµģ",
+      "客 æĪ¶",
+      "çŁ¥åIJį åĵģçīĮ",
+      "æ»ŀ åIJİ",
+      "äºĴ è¡¥",
+      "æĦŁ 人",
+      "åī ¿",
+      "åIJİ ä»£",
+      "äºī 龸",
+      "æķĻèĤ² åŁ¹è®Ń",
+      "éĿĻ èĦī",
+      "ä¹ı åĬĽ",
+      "说 åĩºæĿ¥",
+      "çİĭèĢħ èį£èĢĢ",
+      "åĢ «",
+      "åįĩ èµ·",
+      "éķ ģ",
+      "åĩº 游",
+      "éĢļè¡Į è¯ģ",
+      "å·¥ä½ľ å²Ĺä½į",
+      "åĮł å¿ĥ",
+      "æĭ¿ æĿ¥",
+      "æ´Ĺè¡£ æľº",
+      "æĪijä¸į æĥ³",
+      "é¢Ħ è§ģ",
+      "æ¼Ķ 示",
+      "ä¸Ģ缴 没æľī",
+      "è·Ł 她",
+      "对çħ§ æ£ĢæŁ¥",
+      "ç° ¿",
+      "ä¸ĵ å¿ĥ",
+      "è®® äºĭ",
+      "åīį 端",
+      "åį¡ å°Ķ",
+      "è¨Ń å®ļ",
+      "设置 äºĨ",
+      "å©ļ 纱",
+      "åľ¨ åĽ½å¤ĸ",
+      "åı³ 侧",
+      "è³¼ çī©",
+      "å¥ĩ èij©",
+      "å¢ŀåĬł åĢ¼",
+      "好 è¿IJ",
+      "åĽ½éĻħ æľºåľº",
+      "ä¸ĭ 称",
+      "缮åīį 为æŃ¢",
+      "ç¥ŀ ä»Ļ",
+      "å®ĥ åı¯ä»¥",
+      "æ¾Ħ æ¸ħ",
+      "èĥ½ 使",
+      "游 åĩ»",
+      "游åĩ» éĺŁ",
+      "åĩ ¹",
+      "ä¸įè¦ģ åĨį",
+      "åĨ³ èĥľ",
+      "åĨ³ æĪĺ",
+      "æĭ ½",
+      "缼 åħ¸",
+      "å¾Ī好 åľ°",
+      "æľĢ ç¾İçļĦ",
+      "åĥ ļ",
+      "å·´ åŁº",
+      "å·´åŁº æĸ¯åĿ¦",
+      "æľĢ éĢĤåIJĪ",
+      "é«ĺ èģĮ",
+      "ä¿Ŀ å§Ĩ",
+      "æİĪ æ¬Ĭ",
+      "说åĪ° è¿ĻéĩĮ",
+      "æݨ å¼Ģ",
+      "çİĩ è¾¾",
+      "ä¸īåĪĨ ä¹ĭä¸Ģ",
+      "管çIJĨ ä¸Ńå¿ĥ",
+      "交 æ±ĩ",
+      "森æŀĹ åħ¬åĽŃ",
+      "å¾Ģ ä¸Ĭ",
+      "éªij è¡Į",
+      "æį® æѤ",
+      "纽 带",
+      "ç» ŀ",
+      "ä¸ī æĸ¹",
+      "æĦıä¹ī ä¸ĬçļĦ",
+      "æݨ è¿Ł",
+      "å¤ļæł· æĢ§",
+      "æĥ³ èµ·äºĨ",
+      "æİĴåIJį 第",
+      "å·¨ é¢Ŀ",
+      "æĿŁ ç¼ļ",
+      "å®ī å®ļ",
+      "äºĭ 實",
+      "çļĦ æĦ¿æľĽ",
+      "è£ħå¤ĩ åĪ¶éĢł",
+      "人 å±ħ",
+      "人å±ħ çݯå¢ĥ",
+      "å¿ĺè®° äºĨ",
+      "该 游æĪı",
+      "楼 ä¸Ĭ",
+      "å¼Ģ ä¼ļ",
+      "æģ ³",
+      "åıĭæĥħ éĵ¾æİ¥",
+      "ç¡ Ĵ",
+      "ç»ĻäºĪ äºĨ",
+      "åģı 好",
+      "åĵ ī",
+      "交éĢļ å®īåħ¨",
+      "éĽ Į",
+      "æ²» çĹħ",
+      "è§īå¾Ĺ å¾Ī",
+      "衬 衫",
+      "å¿ĥ æĦ¿",
+      "æ´ŀ å¯Ł",
+      "æ°ij æ£Ģå¯ŁéĻ¢",
+      "æıIJ çĤ¼",
+      "è¦ģ è¿Ľä¸ĢæŃ¥",
+      "驾 车",
+      "æĻ® æĥł",
+      "æķ ĸ",
+      "ç¦ı éŁ³",
+      "éĢģ è¾¾",
+      "è§ĦåĪĴ 设计",
+      "æīĭ å¥Ĺ",
+      "å®ī ä¿Ŀ",
+      "è¿ĺä¸į å¦Ĥ",
+      "åīį è¿°",
+      "æłĩ è®°",
+      "ç´§ æİ¥çĿĢ",
+      "æ§ IJ",
+      "深深 åľ°",
+      "满满 çļĦ",
+      "æĺ¥ è¿IJ",
+      "æĹ¥ 产",
+      "çĪ± æĬ¤",
+      "åħ¨ æĹ¥",
+      "åħ¨æĹ¥ åĪ¶",
+      "转 åĬ¨",
+      "ç¥Ń ç¥Ģ",
+      "ä¹° ä¸ľè¥¿",
+      "对 æľªæĿ¥",
+      "æ¶Ī失 äºĨ",
+      "åļ´ éĩį",
+      "ä¸ī æĿ¡",
+      "éħ¸ 奶",
+      "éĽĨåĽ¢ èĤ¡ä»½",
+      "西 路",
+      "åıª å¾Ĺ",
+      "éĢģ åİ»",
+      "çĭł æĬĵ",
+      "åĪ©çĶ¨ çİĩ",
+      "ä¸ĭ åij¨",
+      "å¥ĭ æĪĺ",
+      "æĺ¥èĬĤ æľŁéĹ´",
+      "è´Ł 责任",
+      "æĺĤ è´µ",
+      "å°¾ å·´",
+      "ç¯ĩ æĸĩç«ł",
+      "åħ ®",
+      "è®Ĭ æĪIJ",
+      "å¹ ¹",
+      "çĻ» éĮĦ",
+      "ä½ Ī",
+      "å·¥ åĮł",
+      "åĵªæĢķ æĺ¯",
+      "åıį åĵį",
+      "ç§ ĥ",
+      "åĩº 轨",
+      "æĹ¥ åĨĽ",
+      "åIJį èªī",
+      "æķı éĶIJ",
+      "æľįåĬ¡ æ°´å¹³",
+      "çħ§ å°Ħ",
+      "ä¼Ĭ æĭī",
+      "ä¼Ĭæĭī åħĭ",
+      "åĨħ éĺģ",
+      "èĬĴ æŀľ",
+      "ä¸ĩ åĪĨ",
+      "éĢĢ 款",
+      "缴æĴŃ éĹ´",
+      "æĭ¿ åĪ°äºĨ",
+      "å°İ èĩ´",
+      "空æ°Ķ ä¸Ń",
+      "客æĪ· æľįåĬ¡",
+      "è¿IJ åĬ¿",
+      "ç»ĵ çŁ³",
+      "ä¸į å¿ħè¦ģçļĦ",
+      "èĥ¶ åĽĬ",
+      "çIJĨ ä¼ļ",
+      "æĬ½ åĩº",
+      "空æ°Ķ è´¨éĩı",
+      "æ¯ķ ç«Łæĺ¯",
+      "åĨ· æ¼ł",
+      "ä¸Ģ å¦Ĥ",
+      "ä¸Ģå¦Ĥ æĹ¢",
+      "ä¸Ģå¦ĤæĹ¢ å¾Ģ",
+      "æĤ£ çĹħ",
+      "åĬł æĮģ",
+      "èµŀ åĬ©",
+      "é« ®",
+      "åij½ ä¸Ń",
+      "æĦıä¹ī ä¸Ĭ",
+      "ä¸į èĪį",
+      "åģļ 梦",
+      "æīĵ æī«",
+      "æĺŁ åħī",
+      "æĸŃ è£Ĥ",
+      "åħ¨ å¥Ĺ",
+      "è£ģ å®ļ",
+      "马 åħĭæĢĿ",
+      "骨 骼",
+      "ä¸Ģ è·¯ä¸Ĭ",
+      "å®ļ æŶ",
+      "å·¥ç¨ĭ æĬĢæľ¯",
+      "å½¼ å¾Ĺ",
+      "æ±² åıĸ",
+      "ä¸Ģ è§Ī",
+      "åIJµ æŀ¶",
+      "ä¿Ĺ 称",
+      "æłª æ´²",
+      "åºŁ æŧ",
+      "è¡Į æĺŁ",
+      "åıijçĶŁ åıĺåĮĸ",
+      "é¦ĸ ä»ĺ",
+      "åįģåĪĨ éĩįè¦ģ",
+      "æĬĬ è¿ĻäºĽ",
+      "ç¥ŀ å·ŀ",
+      "æıIJä¾Ľ åķĨ",
+      "æ¥ ·",
+      "å± İ",
+      "çĬ¶ åħĥ",
+      "åŁİ å¢Ļ",
+      "çľĭ ä¸Ģçľĭ",
+      "çĶŁäº§ èĥ½åĬĽ",
+      "åŁºæľ¬ä¸Ĭ éĥ½",
+      "æīĵ æī°",
+      "åĪĿ 次",
+      "åĩº 示",
+      "åħ¶ä¸Ń ä¸Ģ个",
+      "çĶŁæĢģ ç³»ç»Ł",
+      "æīĭ æİĮ",
+      "æµİåįĹ å¸Ĥ",
+      "åľĭ åħ§",
+      "æŃ£ åĢ¼",
+      "å¹¾ ä¹İ",
+      "æݨèįIJ éĺħ读",
+      "è¿Ń 代",
+      "è°ĥ ä¾ĥ",
+      "饮 åĵģ",
+      "å¢Ļ ä½ĵ",
+      "åıĺ çİ°",
+      "äºĨ 好",
+      "äºĨ好 åĩł",
+      "ä¸į çķĻ",
+      "çĪ ²",
+      "å°½ æĹ©",
+      "æŃ£åľ¨ è¿Ľè¡Į",
+      "åĩº éĻ¢",
+      "æĿĢ 害",
+      "æıIJ 款",
+      "åıijå±ķ 空éĹ´",
+      "åīį 身",
+      "ä¸įæĸŃ å¢ŀ强",
+      "æ·± å±Ĥ次",
+      "容 纳",
+      "éĤ£ 份",
+      "å·¥ä½ľ æķĪçİĩ",
+      "æľ¬ åĽ½",
+      "失 èIJ½",
+      "æŃ£ åĽłä¸º",
+      "èĬĤ æ°´",
+      "ä¸ĭ ä¸Ģ代",
+      "çłĶåıij ä¸Ńå¿ĥ",
+      "ä¸į çIJĨ",
+      "å®Į 好",
+      "ä¿ĿæĬ¤ åĮº",
+      "ç»ĵæŀĦ è°ĥæķ´",
+      "å¥ł å®ļ",
+      "宣 称",
+      "éĺ» æĮ¡",
+      "æĴ¤ 离",
+      "ä¸į æĸ¹ä¾¿",
+      "åĴ ķ",
+      "ç¬ijäºĨ ç¬ij",
+      "çݯå¢ĥ 污æŁĵ",
+      "ä½ı æĪ·",
+      "ç»Ŀ ç¼ĺ",
+      "éĻ¤ å°ĺ",
+      "é«ĺ å°ļ",
+      "æĢİä¹Ī åı¯èĥ½",
+      "éĿ¢ èī²",
+      "åķĨ æ¥Ń",
+      "çĸ ¹",
+      "èµĦæºIJ ä¼ĺåĬ¿",
+      "è¾ĸåĮº åĨħ",
+      "èĢĢ çľ¼",
+      "æij§ æ¯ģ",
+      "ä¸ĸçķĮ ç»ıæµİ",
+      "å¼ķ æĿ¥",
+      "ä¸Ģ åĪĻ",
+      "æĭĩ æĮĩ",
+      "æĬµ 御",
+      "éĽ į",
+      "åĩĨå¤ĩ å·¥ä½ľ",
+      "çıł ä¸īè§Ĵ",
+      "ç¨Ģ åľŁ",
+      "èİ·å¾Ĺ æĦŁ",
+      "æĪIJåĬŁ çİĩ",
+      "ç½ij 约",
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+      "综åIJĪ å®ŀåĬĽ",
+      "æł¼ å°ĩ",
+      "åħļåı² åŃ¦ä¹ł",
+      "æľĢ åŁºæľ¬",
+      "æľĢåŁºæľ¬ çļĦ",
+      "çľĭ æľĽ",
+      "åıĹ è´¿",
+      "ä¸įä»ħ èĥ½",
+      "ä½ķ å¿ħ",
+      "ä¸Ģ个 å°ıæŶ",
+      "ç¾ Į",
+      "æĭĽ æĶ¶",
+      "çĤĴ èĤ¡",
+      "æĿij å¹²éĥ¨",
+      "缸 çĪ±",
+      "æ½ľ èĥ½",
+      "ä¹ į",
+      "æŶ è¾°",
+      "欣 æħ°",
+      "éĵ¶ è¡Įä¸ļ",
+      "çĭŃ çªĦ",
+      "éĩįçĤ¹ é¢ĨåŁŁ",
+      "çİ°å®ŀ çĶŁæ´»",
+      "éĮ¯ 誤",
+      "æĸ° è§Ħ",
+      "滥 çĶ¨",
+      "æŶ ä¸į",
+      "æŶä¸į æŶ",
+      "帳 èĻŁ",
+      "ç¨Ģ 缺",
+      "åIJij 举",
+      "ä¿Ŀåģ¥ åĵģ",
+      "çıŃ éķ¿",
+      "äºĴ åĭķ",
+      "笼 罩",
+      "æ½ Ľ",
+      "æļĸ å¿ĥ",
+      "è½° çĤ¸",
+      "åºĨ 幸",
+      "è²Į ä¼¼",
+      "æĵ º",
+      "èĢIJ 磨",
+      "ä¸ĵä¸ļ 人士",
+      "ä¸ĢèĪ¬ éĥ½æĺ¯",
+      "æ¼³ å·ŀ",
+      "åħ¨ èĩªåĬ¨",
+      "å½ķ çĶ¨",
+      "大 è·Į",
+      "æľīæķĪ æĢ§",
+      "èĩª åĭķ",
+      "ä¸ī个 æĸ¹éĿ¢",
+      "港 åĮº",
+      "信 貸",
+      "éĢļ è¯Ŀ",
+      "é«ĺ 涨",
+      "æ³Ħ æ¼ı",
+      "éħį ä¸Ĭ",
+      "åħļ å·¥å§Ķ",
+      "被 认为",
+      "被认为 æĺ¯",
+      "ä¸įä¼ļ åĨį",
+      "è°ĥ åīĤ",
+      "åıĤ èĤ¡",
+      "èĦ± åıij",
+      "å¿ł å®ŀ",
+      "åĨħ åĪĨæ³Į",
+      "ç¹ģ å¿Ļ",
+      "åıĮ åĪĽ",
+      "é©» æĿij",
+      "åĪĴ ç®Ĺ",
+      "éģİ ä¾Ĩ",
+      "åľ£ ç»ı",
+      "èıľ 鸣",
+      "æĭ¼ å¤ļå¤ļ",
+      "ä¸ŃåĽ½ 汽车",
+      "çĥŁ èįī",
+      "缴 æµģ",
+      "äºĨä¸Ģ åı£æ°Ķ",
+      "ä½İ æĪIJæľ¬",
+      "æī¾ åĽŀ",
+      "èĩª åįij",
+      "總 æĺ¯",
+      "æĸĩåĮĸ åĪĽæĦı",
+      "天 河",
+      "樱 æ¡ĥ",
+      "éªij åħµ",
+      "éĩĮéĿ¢ æľī",
+      "çİ ®",
+      "èĥ½ æī¾åĪ°",
+      "éĢĥ è·ij",
+      "åĪĩ å°Ķ",
+      "åĪĩå°Ķ 西",
+      "以ä¸ĭ æĺ¯",
+      "å²³ éĺ³",
+      "çļĦ æ¦Ĥçİĩ",
+      "æĬµ åĪ¶",
+      "å¸Ī äºĭåĬ¡",
+      "å¸ĪäºĭåĬ¡ æīĢ",
+      "åĩĨ æŶ",
+      "屬 æĸ¼",
+      "订 è´Ń",
+      "åįłæį® äºĨ",
+      "ä¸Ń éĢĶ",
+      "å° ĭ",
+      "é»ij 马",
+      "åİ¿ åħ¬å®īå±Ģ",
+      "ä¸ĥ æľĪ",
+      "èī² ç´ł",
+      "å¿ĥèĦı çĹħ",
+      "æŶ éĻIJ",
+      "æ¯į åħ¬åı¸",
+      "å¹ķ åIJİ",
+      "ä¸Ĭ æ¦ľ",
+      "åĢ¾åIJij äºİ",
+      "纸 ä¸Ĭ",
+      "æ¡ ĵ",
+      "éĽĨä½ĵ ç»ıæµİ",
+      "æĥħ å¢ĥ",
+      "è¦ģ åģļåĪ°",
+      "ç©į 極",
+      "åıª æĢķ",
+      "æ¹ĺ 西",
+      "çļ± 纹",
+      "åħ¨ åľĭ",
+      "çĦ¡ è«ĸ",
+      "好 æĦŁ",
+      "åįķ ä»·",
+      "è¿Ľç¨ĭ ä¸Ń",
+      "æĺĨ ä»ij",
+      "åĪĽ 客",
+      "åħħ æĸ¥",
+      "åħĪ æĬĬ",
+      "该 æĢİä¹ĪåĬŀ",
+      "åĵģ å¾·",
+      "åħ¨éĿ¢ åıijå±ķ",
+      "è¨Ī åĬĥ",
+      "æĢ» å·¥ä¼ļ",
+      "ä½Ľå±± å¸Ĥ",
+      "æĬĹ è¡¡",
+      "å¼Ģ åľº",
+      "éĴ± å¸ģ",
+      "åıĭ 们",
+      "å«ī å¦Ĵ",
+      "ç´¢ èµĶ",
+      "è®Ĭ åĮĸ",
+      "æĮ¤ åİĭ",
+      "æĮij è¡ħ",
+      "çŃī ä¸Ģæī¹",
+      "æĿ¨ 欢",
+      "ä¸ĵ家 åѦèĢħ",
+      "èĥ½ è¾¾åĪ°",
+      "èµ° è¿ij",
+      "è´«åĽ° åľ°åĮº",
+      "éĻIJ æľŁ",
+      "ä¸į 平衡",
+      "åĽ½åĨħ å¸Ĥåľº",
+      "èµĽ åľº",
+      "éħį èµĦ",
+      "è¦ģ èĢĥèĻij",
+      "ä¸ĩ åı°",
+      "æľĪ æľ«",
+      "éĶ ¥",
+      "åŃ «",
+      "æݥ触 åĪ°",
+      "åĩº 产",
+      "æķĻ åѸ",
+      "ä½ľ å¼Ĭ",
+      "çļĦ æľĢåIJİä¸Ģ",
+      "ä¿ĥ æĪIJ",
+      "åIJ¸ åıĸ",
+      "æ½ľ èīĩ",
+      "被 éªĹ",
+      "è¾ĵ äºĨ",
+      "çĭIJ çĭ¸",
+      "åįĩ éĻį",
+      "è¿ĻäºĽ ä¸ľè¥¿",
+      "æĬķèµĦ åŁºéĩij",
+      "çĶŁçī© åѦ",
+      "ç½ij绾 èIJ¥éĶĢ",
+      "åIJij è®°èĢħ",
+      "èįī åľ°",
+      "æĢ ¯",
+      "æľįåĬ¡ èĥ½åĬĽ",
+      "éĥģ éĹ·",
+      "åįķ åĵģ",
+      "å¾Ĺ 罪",
+      "æĺĵ äºİ",
+      "个å¤ļ å°ıæŶ",
+      "éĩį ä»»",
+      "ä¸Ĭ å®ĺ",
+      "æľ¬ éĩij",
+      "çı¾ åł´",
+      "溢 价",
+      "æĺŁ è¾°",
+      "æ´»åĬ¨ çİ°åľº",
+      "丹 麦",
+      "å¸Ŀ çİĭ",
+      "æŁ¥ æĺİ",
+      "åŃĺåľ¨ äºİ",
+      "é¦Ļ æ°´",
+      "æĬ½ æ£Ģ",
+      "å®ŀéĻħä¸Ĭ æĺ¯",
+      "æĸ° å¾ģç¨ĭ",
+      "è´¢åĬ¡ 管çIJĨ",
+      "æİ Ľ",
+      "åĨľ åİĨ",
+      "éĥ½ èĥ½å¤Ł",
+      "éĤ¯ éĥ¸",
+      "羣 實",
+      "ç» Ĭ",
+      "åĨµ ä¸Ķ",
+      "置 身",
+      "ç¥Ī 祷",
+      "çĿģ å¼Ģ",
+      "æĮĩ çĤ¹",
+      "å¼Ģ æľº",
+      "西 å®ģ",
+      "åĮĹ çº¦",
+      "积 水",
+      "åĩº åĬ¨",
+      "åıijå±ķ 模å¼ı",
+      "转 æĬĺ",
+      "èĢĥ çĤ¹",
+      "æľī ç½ijåıĭ",
+      "è´«åĽ° æĿij",
+      "æĪij们 çŁ¥éģĵ",
+      "åĪĨ éĶĢ",
+      "å±± èĦī",
+      "æ¯Ķ æĭŁ",
+      "ä¼° ç®Ĺ",
+      "æĶ¹ 建",
+      "壮 è§Ĥ",
+      "ç§ī æĮģ",
+      "æı ª",
+      "ç¦ Ģ",
+      "åĮĸåѦ åĵģ",
+      "ä¸ŃåĽ½ åĪ¶éĢł",
+      "ä¸Ģ æŀ¶",
+      "æīį è¡Į",
+      "æĭĽ å¾ħ",
+      "åıĺ æį¢",
+      "åīį 线",
+      "幸 好",
+      "è¿Ļæł· çļĦè¯Ŀ",
+      "å¿ĥ è¡Ģ管",
+      "æĢ§ çĸ¾çĹħ",
+      "åħ¨ èĥ½",
+      "åĪij 侦",
+      "ä¿¡æģ¯ åıijå¸ĥ",
+      "æĺ¾ çĦ¶æĺ¯",
+      "éĿĴ éĵľ",
+      "åIJĥ ä»Ģä¹Ī",
+      "çĶµ ä»·",
+      "æ³ķå¾ĭ è§Ħå®ļ",
+      "çħ ²",
+      "çĵ· åĻ¨",
+      "èĤī ç±»",
+      "æıĴ åħ¥",
+      "åĹ ľ",
+      "è¿Ł è¿Ł",
+      "ä¸ĢçĤ¹ éĥ½ä¸į",
+      "è¿ĺ åĮħæĭ¬",
+      "èĪį ä¸įå¾Ĺ",
+      "æłĩå¿Ĺ æĢ§",
+      "æľĪ 以æĿ¥",
+      "ç³ĸ æŀľ",
+      "éĥ½ åºĶ该",
+      "çݯå¢ĥ åį«çĶŁ",
+      "èĪª è¡Į",
+      "éĥij éĩį",
+      "ç½ij æĬķ",
+      "åįģ ä½³",
+      "ç§ģ ä¸ĭ",
+      "æļ´ è·Į",
+      "åĬłå¿« åıijå±ķ",
+      "产åĵģ çłĶåıij",
+      "åĪĽéĢł åĩº",
+      "æĢ» è§īå¾Ĺ",
+      "åºķ çĽĺ",
+      "èķ Ĭ",
+      "åĩºå¸Ń ä¼ļè®®",
+      "主 æĿ¿",
+      "æĹ¥æĻļ éĹ´",
+      "å®ĺæĸ¹ å¾®åįļ",
+      "å¼ķçĶ¨ æĹ¥æľŁ",
+      "åī¯ æķĻæİĪ",
+      "çĶµåŃIJ 产åĵģ",
+      "è¡° éĢĢ",
+      "çķĻ åŃĺ",
+      "çģ« åĬĽ",
+      "çĴ §",
+      "çļ Ĥ",
+      "åħ¼ åħ·",
+      "éĩį è¿Ķ",
+      "é¢Ĩ çķ¥",
+      "åĪĩ éĻ¤",
+      "åĨįçĶŁ èĥ½æºIJ",
+      "å®ŀåľ¨ 太",
+      "çIJĨ论 ä¸Ĭ",
+      "ä¸ī å±Ĥ",
+      "ä¸ĸçķĮ åIJĦåĽ½",
+      "å®ľ æĺĮ",
+      "èĢ³ è¾¹",
+      "宽 æķŀ",
+      "æ±ī æĹı",
+      "çĻ½ çĻ½",
+      "è¿ĻéĩĮ éĿ¢",
+      "çĶŁæ´» ä¹łæĥ¯",
+      "èµŀ èµı",
+      "çĶ· 士",
+      "ä¸Ń ä¿Ħ",
+      "车 祸",
+      "åīĤ éĩı",
+      "éĻ¤ åİ»",
+      "å·¦ è¾¹",
+      "çŃij çī¢",
+      "çīĽ å¸Ĥ",
+      "家 åĬ¡",
+      "åķ ĥ",
+      "ç½® æį¢",
+      "ç´« å¤ĸ",
+      "ç´«å¤ĸ 线",
+      "å¾Ģ åīį",
+      "åĬĽ åѦ",
+      "ç´§ è·Ł",
+      "缮çļĦ åľ¨äºİ",
+      "ç» ®",
+      "ç¥ Ĥ",
+      "宣 è¨Ģ",
+      "äºĮ æ°§åĮĸ",
+      "äºĮæ°§åĮĸ 碳",
+      "æĹł ç¼ĺ",
+      "ç²¾ éĢļ",
+      "è¨ º",
+      "å¼ķåıij äºĨ",
+      "æľĢ åħĪ",
+      "æ´¾ é©»",
+      "ä¸į å¿į",
+      "æĪij çĪ¸",
+      "å¹´ ä¸ĭåįĬå¹´",
+      "æ·ĭ å·´",
+      "没 éĹ®é¢ĺ",
+      "åºĹ åĨħ",
+      "è·Ł æĪij说",
+      "çĶŁäº§ çĶŁæ´»",
+      "è§Ĥ æľĽ",
+      "æ¸ į",
+      "被 æī§è¡Į",
+      "被æī§è¡Į 人",
+      "èĪ ľ",
+      "æİ º",
+      "ä¸Ģ ç§Ĵ",
+      "èįī åĿª",
+      "åij¼ åĴĮ",
+      "åij¼åĴĮ 浩",
+      "åij¼åĴĮ浩 çī¹",
+      "人æ°ij éĵ¶è¡Į",
+      "çĦķ åıij",
+      "è¯ģåĪ¸ 交æĺĵ",
+      "çķ Ķ",
+      "æľº èĥ½",
+      "å¦ ¾",
+      "æĻļ å¹´",
+      "å·¥åķĨ èģĶ",
+      "åİŁ åŀĭ",
+      "è§Ĵ度 çľĭ",
+      "æĬ¥ 社",
+      "è¯į æĿ¡",
+      "躲 éģ¿",
+      "éĩį åIJ¯",
+      "å¤ķ éĺ³",
+      "èĤ¡æĿĥ 转让",
+      "åľ¨ ä¸Ģ",
+      "åľ¨ä¸Ģ æĹģ",
+      "社ä¼ļ åĮĸ",
+      "åıijå±ķ åİĨç¨ĭ",
+      "æĭĸ æ¬ł",
+      "使 èĢħ",
+      "ä¸İ åIJ¦",
+      "æĸ° å±ĢéĿ¢",
+      "ä»Ĭ天 æĪij们",
+      "é½IJ èģļ",
+      "对 æĪij说",
+      "éĢĴ 交",
+      "æľª æĽ¾",
+      "èİ Ĭ",
+      "éĸ ī",
+      "亲 æīĭ",
+      "è§Ĵ éĢIJ",
+      "æľī é»ŀ",
+      "ç¨İ çİĩ",
+      "ä½İ 声",
+      "é»ĺ å¥ij",
+      "æĻ® æ³ķ",
+      "大 ä¸ĵ",
+      "第äºĮ 大",
+      "ä½ı åĿĢ",
+      "æĶ¾ è¿Ľ",
+      "äºĮ æĪĺ",
+      "亲 身",
+      "åĽº åĮĸ",
+      "ä¸ĭ 乡",
+      "åħ³éĶ® æĬĢæľ¯",
+      "åĽŀ æĥ³",
+      "æĬ¥ åĪĬ",
+      "æ¶Ĥ æĬ¹",
+      "èĹı çĿĢ",
+      "ç¥Ŀ æĦ¿",
+      "åįĩ 温",
+      "çĶļèĩ³ è¿ŀ",
+      "åħ¬åħĥ åīį",
+      "ç¾İ æĸ¹",
+      "è¯ļ å®ŀ",
+      "æĹł åģ¿",
+      "åīµ æ¥Ń",
+      "å°ıå¿ĥ 翼",
+      "å°ıå¿ĥ翼 翼",
+      "两 æīĭ",
+      "温馨 æıIJ示",
+      "仿 羣",
+      "æĥ ¶",
+      "èĥ¡ åŃIJ",
+      "å·¥ä½ľ ç«Ļ",
+      "硬 çĽĺ",
+      "ç« ¿",
+      "åĤ³ éĢģ",
+      "åħ¨ æł¡",
+      "é²ľ æ´»",
+      "çĴĢ çĴ¨",
+      "ç»ĵ å°¾",
+      "æį¢ æĿ¥",
+      "æĪ Ģ",
+      "ä½İ ä½į",
+      "ä¸ĩåħĥ 以ä¸Ĭ",
+      "åĬł åĪĨ",
+      "æݨä»ĭ ä¼ļ",
+      "çIJĨ èµĶ",
+      "å¾· å°Ķ",
+      "æĬĹ è®®",
+      "æ´ ¼",
+      "åĸ §",
+      "åŁİ éĻħ",
+      "å¾Ī æ£Ĵ",
+      "人 æŃ»äº¡",
+      "ä¼ļå±ķ ä¸Ńå¿ĥ",
+      "äºĴèģĶ äºĴéĢļ",
+      "èĸĦ èĨľ",
+      "éĩį é»ŀ",
+      "ç¦ģ æ¯Ĵ",
+      "åĨ· ç¬ij",
+      "大家 åı¯ä»¥",
+      "é¦ĸ 缸",
+      "è¿ij è·Ŀ离",
+      "æµ® çİ°",
+      "ç§ĺ è¯Ģ",
+      "èµ· é£ŀ",
+      "æIJ ¶",
+      "羣 åģĩ",
+      "æģ ķ",
+      "å°ı åºĹ",
+      "æ°ij çľ¾",
+      "åıijå¸ĥ åħ¬åijĬ",
+      "侧 éĩį",
+      "å¾ĺ å¾Ĭ",
+      "æĢ Ķ",
+      "æª IJ",
+      "æķ° 缮",
+      "åī¯ ç§ĺ书éķ¿",
+      "两 åı¥",
+      "éļIJ çŀĴ",
+      "åıĮ åıĮ",
+      "æīĭ æĦŁ",
+      "èij¡ 京",
+      "éģĹ å¿ĺ",
+      "é¬ ¥",
+      "è¿Ļ个 åľ°æĸ¹",
+      "说 çļĦè¯Ŀ",
+      "å·¡ åĽŀ",
+      "è¿Ŀ ç«ł",
+      "æī¾ å·¥ä½ľ",
+      "æĶ¯ çIJĥéĺŁ",
+      "裡 éĿ¢",
+      "æĺ¾ç¤º åĩº",
+      "èĩ³ å°Ĭ",
+      "两 级",
+      "åīį 段æŶéĹ´",
+      "çĺ¦ èº«",
+      "èĤ¢ ä½ĵ",
+      "æ¯į 親",
+      "æīĭç»Ń è´¹",
+      "汽车 è¡Įä¸ļ",
+      "æİ© çĽĸ",
+      "æݧèĤ¡ éĽĨåĽ¢",
+      "åı£ å¾Ħ",
+      "æĶ¿çŃĸ æݪæĸ½",
+      "海 绵",
+      "åħ¨ éķĩ",
+      "äºĭ åħ³",
+      "å¸Ń æī§è¡Į",
+      "å¸Ńæī§è¡Į å®ĺ",
+      "éĤ£ 次",
+      "åı¯èĥ½ åĩºçİ°",
+      "ä¸Ńå¿ĥ åŁİå¸Ĥ",
+      "翻 身",
+      "ä¹Ł ç®Ĺ",
+      "ä¾µ çķ¥",
+      "åĸĩ åıŃ",
+      "æ¯ı次 éĥ½",
+      "è§ ħ",
+      "éĻ¢ éĻ¢éķ¿",
+      "å§ĭ äºİ",
+      "èѦ åĬ¡",
+      "èį¯ æĿIJ",
+      "å±ł æĿĢ",
+      "æľ¬èº« å°±",
+      "éļıæŶ éļı",
+      "éļıæŶéļı åľ°",
+      "åĶ® åįĸ",
+      "æĹłäºº 驾驶",
+      "é¢ ħ",
+      "åĵģ 質",
+      "åĺ² ç¬ij",
+      "è·ij åİ»",
+      "åħĭ éĩĮæĸ¯",
+      "çķ¸ å½¢",
+      "修 饰",
+      "磩 éĺµ",
+      "éŁ³ä¹IJ ä¼ļ",
+      "æŁ³ å·ŀ",
+      "é½ ¡",
+      "ä¼ļ è°Ī",
+      "æŃ£ çīĪ",
+      "ä¹Ł åIJĮæł·",
+      "æļ§ æĺ§",
+      "è¡ĮæĶ¿ éĥ¨éŨ",
+      "ä¹ĸ ä¹ĸ",
+      "èĤ¤ èī²",
+      "æŶ ä»»",
+      "羣 åĪĩ",
+      "æľĪ ä¸ĭ",
+      "æľĪä¸ĭ æŬ",
+      "举æĸ¹ è´¢å¯Į",
+      "è£ħä¿® åħ¬åı¸",
+      "éĢĢ è¿ĺ",
+      "åĭĺ å¯Ł",
+      "åĵ¥ 伦",
+      "åĵ¥ä¼¦ æ¯Ķäºļ",
+      "çĭ¬ ä¸Ģ",
+      "çĭ¬ä¸Ģ æĹł",
+      "çĭ¬ä¸ĢæĹł äºĮ",
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+      "å¸Ĥ æĶ¿åįı",
+      "äºĭ æ¥Ń",
+      "龸 çİĭ",
+      "çĥŃ æIJľ",
+      "åįģä¹Ŀ 大",
+      "ä¼´ æľī",
+      "ç¾İåĽ½ æĢ»ç»Ł",
+      "åŁİå¸Ĥ 管çIJĨ",
+      "ä¸ĭ 令",
+      "èĥ¸ åı£",
+      "åıª çŁ¥éģĵ",
+      "åij¨ ä¸ī",
+      "çĶ¨ æĪ¶",
+      "éŃ ¯",
+      "å¿ĥ è¡Ģ",
+      "带头 人",
+      "åĮ» åĬ¡",
+      "åĮ»åĬ¡ 人åijĺ",
+      "æݧåĪ¶ åĻ¨",
+      "ä½ľåĵģ åĨħ容",
+      "æĪĺ åıĭ",
+      "åİĨ å¹´",
+      "ä¸į åħĭ",
+      "ä¸įåħĭ ä¸įåıĬ",
+      "æĹ¥ æŃ£å¼ı",
+      "è±IJ å¯Į",
+      "ç¨İ è´¹",
+      "æŶ æķĪ",
+      "å±ķ ä½į",
+      "è¡¡ éĺ³",
+      "æĪ¿ 貸",
+      "çĪĨ 款",
+      "ä¹IJ æĦı",
+      "çĶ· 主",
+      "å¯ ¬",
+      "æľĥ èŃ°",
+      "ä¹ĭ å¤ľ",
+      "åIJĮ 樣",
+      "ä¸įè¦ģ 太",
+      "ä¼Ĭ æĸ¯",
+      "ä¼Ĭæĸ¯ åħ°",
+      "åŁºæľ¬ åİŁåĪĻ",
+      "åİ» æİī",
+      "ä½İ ä¿Ŀ",
+      "个 交æĺĵ",
+      "个交æĺĵ æĹ¥",
+      "èģĬ èģĬ",
+      "åĽĽ ä½į",
+      "åħļç»Ħ æĪIJåijĺ",
+      "主è¦ģ ä»İäºĭ",
+      "å½± éŁ³",
+      "åĨĴ åĩº",
+      "åij¼åIJ¸ éģĵ",
+      "è¾¾ å°Ķ",
+      "æľ¨ åľ°æĿ¿",
+      "诡 å¼Ĥ",
+      "çģ¯ åħ·",
+      "çģ« çĥ§",
+      "解 èĦ±",
+      "æĦĪ åıij",
+      "æ¹ĸ å·ŀ",
+      "é£İ ä¿Ĺ",
+      "æĸ° å½¢åĬ¿",
+      "æĸ°å½¢åĬ¿ ä¸ĭ",
+      "è² Ŀ",
+      "èĦ ĵ",
+      "åĬ¨åĬĽ çĶµæ±ł",
+      "é£ŀ èĪ¹",
+      "飧 æĢ§",
+      "åĪ© çī©",
+      "åĪ©çī© 浦",
+      "ä¸į 认è¯Ĩ",
+      "ç¼ĸ ç»ĩ",
+      "ä½ľ åĿĬ",
+      "èģĮä¸ļ æĬĢèĥ½",
+      "çľĭ è¦ĭ",
+      "åĽ´ æ£ĭ",
+      "æĺı è¿·",
+      "å½Ĵ å±ŀäºİ",
+      "æĤ¬ å´ĸ",
+      "éĨ« çĻĤ",
+      "å®ĭ 代",
+      "åºĦ æĿij",
+      "èĹ ķ",
+      "çĮĽ çĦ¶",
+      "çĩĥæĸĻ çĶµæ±ł",
+      "å®ŀä½ĵ åºĹ",
+      "ä¸į足 以",
+      "æĥħ ç·",
+      "æĥħç· Ĵ",
+      "å»Ĭ åĿĬ",
+      "çĶµ åı°",
+      "åºĶ åĬĽ",
+      "ä¸Ńå°ı åѦçĶŁ",
+      "èĥ¡ åIJĮ",
+      "éī´ åĪ«",
+      "åĨħ ç½®",
+      "乱 象",
+      "æ¬Ĭ çĽĬ",
+      "å¼ĢæĶ¾ å¼ı",
+      "åįļ æĸĩ",
+      "讲 课",
+      "çŃī åİŁåĽł",
+      "穷 人",
+      "交 æĽ¿",
+      "æĬ¤ çħ§",
+      "åıijå±ķ æľºéģĩ",
+      "客 åķĨ",
+      "åıį ä¹ĭ",
+      "ç±³ é¥Ń",
+      "并 åıij",
+      "并åıij çĹĩ",
+      "æ±ī åŃIJ",
+      "æŀľ åĽŃ",
+      "对æĪij æĿ¥è¯´",
+      "åģı åIJij",
+      "æī¹ 示",
+      "读 åIJİ",
+      "读åIJİ æĦŁ",
+      "æĺİ æĻº",
+      "åĽ´ çĿĢ",
+      "åıį 转",
+      "æĿ¨ å¹Ĥ",
+      "ä¸ĵ åįĸ",
+      "ä¸ĵåįĸ åºĹ",
+      "åıĹ éĻIJ",
+      "åºŁ è¯Ŀ",
+      "æŀģ å°ij",
+      "åįĪ åIJİ",
+      "è¿Ľ ä¿®",
+      "åīĬ åĩı",
+      "æľ¬ç§ij çĶŁ",
+      "ä¼ĺ éĢī",
+      "åħī çħ§",
+      "åıĻ äºĭ",
+      "åıĸ æļĸ",
+      "åĮĹ è·¯",
+      "æ¦ ķ",
+      "èİĨ çĶ°",
+      "楼 å±Ĥ",
+      "天 èĬ±",
+      "天èĬ± æĿ¿",
+      "çĤ ľ",
+      "å·²ç»ı æľīäºĨ",
+      "è¶ ¾",
+      "çĶ³ åįļ",
+      "çĶµ éĺ»",
+      "åĬŁ 课",
+      "æŃ¥ æŃ¥",
+      "éĤ£ä¹Ī 容æĺĵ",
+      "æѤ æĸĩ",
+      "ä½ °",
+      "计 è¾ĥ",
+      "çīĩ éĿ¢",
+      "çĶµå½± éĻ¢",
+      "ä¸į åħ¬å¹³",
+      "ä¸ī æľŁ",
+      "æĹħ游 èµĦæºIJ",
+      "å¤ļç§į å½¢å¼ı",
+      "è£Ĥ ç¼Ŀ",
+      "åIJİ æİĴ",
+      "硬 度",
+      "åĽŀ æļĸ",
+      "éģĵ æķĻ",
+      "è´« è¡Ģ",
+      "æ¸ħ é¦Ļ",
+      "伤 çĹħ",
+      "æĦı 義",
+      "çļĦ ç¼ĺ",
+      "çļĦç¼ĺ æķħ",
+      "åºĦ 严",
+      "åıªæĺ¯ ä¸ºäºĨ",
+      "æīĵ æĬĺ",
+      "以 ä¾Ĩ",
+      "滿 足",
+      "çİĽ 丽",
+      "風 éļª",
+      "æĸĩ ç§ij",
+      "éħįå¤ĩ äºĨ",
+      "è¿Ľ é£Ł",
+      "æ¶ ¡",
+      "è·¯ ç¨ĭ",
+      "åı« 声",
+      "ä¸Ńå¿ĥ åŁİåĮº",
+      "æľīæīĢ ä¸įåIJĮ",
+      "å¼µ è²¼",
+      "é¢Ħ æĬ¥",
+      "æľīå¤ļ ä¹Ī",
+      "è¿Ľè¡Į åħ¨éĿ¢",
+      "æĽ¾ ç¶ĵ",
+      "ä¸ī 代",
+      "å®ı 大",
+      "æ¸ħ æī«",
+      "éĢī åĩº",
+      "åĵª ä¸Ģ个",
+      "主 義",
+      "ä¾Ŀ æĵļ",
+      "çļ® éĿ©",
+      "赶 æĿ¥",
+      "çŃĽ æŁ¥",
+      "æ¨ Ł",
+      "ä¿Ŀ èįIJ",
+      "åIJĥ æĥĬ",
+      "æľĭåıĭ们 对",
+      "ä»ĸ æĺ¯ä¸Ģ个",
+      "åºŁ æ°Ķ",
+      "æ» ħ",
+      "è´¢ ç¨İ",
+      "æĿij æĿijæ°ij",
+      "èµĦ产 è´ŁåĢº",
+      "å®ī å¨ľ",
+      "缮åīį åĽ½åĨħ",
+      "æĦŁè§ī èĩªå·±",
+      "çµIJ åIJĪ",
+      "éĶ¦ æłĩ",
+      "éĶ¦æłĩ èµĽ",
+      "æĽ´ æ·±",
+      "åŁº æķ°",
+      "éħ¿ éħĴ",
+      "çī¹èī² 产ä¸ļ",
+      "åİĭ å®ŀ",
+      "ä¾Ŀæ³ķ 追究",
+      "æ·¡ å®ļ",
+      "ç®Ģ缴 å°±æĺ¯",
+      "å£ĵ åĬĽ",
+      "æ°ij å¿ĥ",
+      "ä¸į åIJĪéĢĤ",
+      "çĶ±æѤ åı¯è§ģ",
+      "èµŀ èªī",
+      "æ¾ ¤",
+      "åĩłå¹´ åīį",
+      "åIJī ä»ĸ",
+      "çł´ æįŁ",
+      "轻轻 åľ°",
+      "å²Ľ 屿",
+      "æĦı å¢ĥ",
+      "ä»Ģä¹Ī åı«",
+      "åģĩ è£ħ",
+      "éĢģ è´§",
+      "å¹ķ å¢Ļ",
+      "妥 åįı",
+      "åĽ½ æĹĹ",
+      "äºĨ å¾Īä¹ħ",
+      "åĪĨ辨 çİĩ",
+      "ç´ Ķ",
+      "éĺ³ åĮº",
+      "åĩŃ çĿĢ",
+      "åģľè½¦ ä½į",
+      "京 éĥ½",
+      "éĶ £",
+      "æĵ ¾",
+      "è¿Ľ éŨ",
+      "åĪĺ æµ·",
+      "åĽĽ 级",
+      "女 足",
+      "è¡ĮæĶ¿ 审æī¹",
+      "éģ¥ æݧ",
+      "ä¸į éĮ¯",
+      "å¾Ĺ å¾Ī好",
+      "为 缮çļĦ",
+      "ä»į æľª",
+      "ç²¾ è£ħ",
+      "éĢį éģ¥",
+      "尽 头",
+      "çºł ç¼ł",
+      "éłĺ å°İ",
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+      "åı® åĺ±",
+      "åģĩ åĨĴ",
+      "æļĸ æ°Ķ",
+      "çĽIJ åŁİ",
+      "被 è§Ĩ为",
+      "诺 è´Ŀå°Ķ",
+      "ç»ĻäºĨ æĪij",
+      "è¿ij åįĥ",
+      "éĩį åĽŀ",
+      "éĨĴ äºĨ",
+      "çĶµ 解",
+      "忽çķ¥ äºĨ",
+      "èĥĮ éĥ¨",
+      "æĸĩæĺİ åŁİå¸Ĥ",
+      "æº ħ",
+      "è² ĵ",
+      "æĬµ æĮ¡",
+      "åĸľæ¬¢ åIJĥ",
+      "éĿĻéĿĻ åľ°",
+      "å¾Ī æ·±",
+      "åŁºç¡Ģ çŁ¥è¯Ĩ",
+      "è¿ĩ éĶĻ",
+      "çIJĨ ç§ij",
+      "交æµģ åIJĪä½ľ",
+      "èĪ Ķ",
+      "調 æŁ¥",
+      "æħĪ æĤ²",
+      "éĴ °",
+      "èĩ´ çĶµ",
+      "å®£ä¼ł æ´»åĬ¨",
+      "åıĺ éĩı",
+      "çļĦ人 æĿ¥è¯´",
+      "æŶ éļĶ",
+      "ä¸į管 ä½ł",
+      "缸 è¿ij",
+      "è´µ éĩijå±ŀ",
+      "ä¹Łä¸į åı¯èĥ½",
+      "ç²ī æľ«",
+      "åįĹ çĵľ",
+      "çĻ½ 马",
+      "åħī æºIJ",
+      "éĩij å¥ĸ",
+      "çĭ¬ è§Ĵ",
+      "çĭ¬è§Ĵ åħ½",
+      "妨 ç¢į",
+      "ç»Ļ åĬĽ",
+      "ä½Ĩ ä»į",
+      "å¼łå®¶ åı£",
+      "èIJ¬ åħĥ",
+      "渲 æŁĵ",
+      "éķ¿å¤§ äºĨ",
+      "è®°èĢħ äºĨ解",
+      "æĢĢ çĿĢ",
+      "è¦ģ åѦä¼ļ",
+      "游æĪı 代",
+      "游æĪı代 ç»ĥ",
+      "äºĮ çĻ¾",
+      "æĦıè¯Ĩ å½¢æĢģ",
+      "çİ º",
+      "计åĪĴ çĶŁèĤ²",
+      "æī¾ åĩĨ",
+      "åħ° èĬ±",
+      "è¿Ļ座 åŁİå¸Ĥ",
+      "污 泥",
+      "å®ĺæĸ¹ 微信",
+      "å½Ĵ å±ŀ",
+      "æ°§ æ°Ķ",
+      "éģİç¨ĭ ä¸Ń",
+      "åį°è±¡ æ·±åĪ»",
+      "稳 妥",
+      "çµIJ æĿŁ",
+      "åŃķ æľŁ",
+      "çī¹ æĿĥ",
+      "åĿļ åĽº",
+      "顺 åĬ¿",
+      "æŀľ èĶ¬",
+      "éĨ« 師",
+      "åİ ®",
+      "ä¹Łæĺ¯ å¦ĤæѤ",
+      "é¦Ĵ 头",
+      "缸 åĬ©",
+      "干 线",
+      "ä¸Ģ æľ¬ä¹¦",
+      "ç» ¥",
+      "æĮ¯ å¥ĭ",
+      "èĤ¾ èĦı",
+      "åĭķ çī©",
+      "é£ŀ è·ĥ",
+      "èıľ åĵģ",
+      "å¤ļ ä½Ļ",
+      "å¤ļä½Ļ çļĦ",
+      "éĢĿ ä¸ĸ",
+      "æģĭ 人",
+      "å¼Ģåıij åĪ©çĶ¨",
+      "顺 丰",
+      "éĩİ å¿ĥ",
+      "æł¡ å¤ĸ",
+      "æģIJ é¾Ļ",
+      "éĿ¢ åħ·",
+      "éķ¿ è¾Ī",
+      "éļı å¤Ħ",
+      "éļıå¤Ħ åı¯è§ģ",
+      "紧 缺",
+      "éĩį ä¸Ń",
+      "éĩįä¸Ń ä¹ĭ",
+      "éĩįä¸Ńä¹ĭ éĩį",
+      "奥 æĸ¯",
+      "奥æĸ¯ åį¡",
+      "ä¸Ģ个 å¤ļ",
+      "ä¸Ģ个å¤ļ æľĪ",
+      "ä¸įåı¯ 缺å°ij",
+      "æĸ° æł¼å±Ģ",
+      "æıIJ æĮ¯",
+      "è¡Į è´¿",
+      "æ¼Ĥ æµģ",
+      "èģĬ åŁİ",
+      "åħ´ 建",
+      "è´¨ æ£Ģ",
+      "ç§ģæľį 游æĪı",
+      "æĽ´ éĩįè¦ģ",
+      "è´ ®",
+      "çħ ľ",
+      "转åıĺ 为",
+      "è¿Ļ 两年",
+      "ä¿Ŀ é²ľ",
+      "æī§ æķĻ",
+      "çĥ ¨",
+      "å¼Ģåıij 建设",
+      "è¿IJèIJ¥ 管çIJĨ",
+      "误 差",
+      "京 åī§",
+      "å¸IJ åı·",
+      "å·¥ä½ľ ä½ľé£İ",
+      "ä¸ĸ ä¿Ĺ",
+      "çĻ½ 宫",
+      "天 åĽ½",
+      "å¤©åĽ½ 继ç»Ń",
+      "å·´ æĸ¯",
+      "èIJ¥ åĪ©",
+      "åĵģ æł¼",
+      "æĿijæ°ij 们",
+      "æĪ¿ 车",
+      "çŃī çĹĩçĬ¶",
+      "å¦Ĥ å®ŀ",
+      "å® ¸",
+      "å±Ĥ 级",
+      "éĶĻ è¿ĩäºĨ",
+      "ç»ĵ å®ŀ",
+      "ç¬ij èĦ¸",
+      "羣å®ŀ æĢ§",
+      "éĥ½å¸Ĥ æĬ¥",
+      "é¥Ń èıľ",
+      "åºĶ 注æĦı",
+      "æĬ½ çĥŁ",
+      "伪 éĢł",
+      "åīį ä¸Ģ天",
+      "éŃĶ é¾Ļ",
+      "éŃĶé¾Ļ 令çīĮ",
+      "约 è°Ī",
+      "绣çŃ¹ æİ¨è¿Ľ",
+      "让 çĶ¨æĪ·",
+      "åħ¨éĿ¢ èIJ½å®ŀ",
+      "å¼Ħ å¾Ĺ",
+      "è°Ī æģĭçĪ±",
+      "鸣 æĪIJéķ¿",
+      "鸣æĪIJéķ¿ è®°",
+      "æ´ĭ æ´ĭ",
+      "çĸı æķ£",
+      "éĿ¢ç§¯ 约",
+      "æµĵ 缩",
+      "æĸ¯ é¡¿",
+      "çĶŁæĢģ åľĪ",
+      "æī§ 导",
+      "移 éĢģ",
+      "齿 轮",
+      "æł¹æľ¬ å°±ä¸į",
+      "缩 åĩı",
+      "èµ° ä¸ĭåİ»",
+      "çĿ« æ¯Ľ",
+      "ä¹Łä¸į éĶĻ",
+      "åıįæĺł åĩº",
+      "èĭ¦ æģ¼",
+      "缸åħ³ æĶ¿çŃĸ",
+      "é«ĺ 楼",
+      "ç²ī èī²",
+      "æĬķèµĦ é¢Ŀ",
+      "ä¸į ç»ı",
+      "ä¸įç»ı æĦı",
+      "å®ģ æĦ¿",
+      "èĪĮ 头",
+      "æ»ĭ çĶŁ",
+      "å®ģ åİ¿",
+      "åīįåĪĹ èħº",
+      "åĩ ³",
+      "é£Ł 欲",
+      "åıĸ èĥľ",
+      "éĻ¢ åŃIJ",
+      "ç´łè´¨ æķĻèĤ²",
+      "滨 å·ŀ",
+      "æĬ¢ æĬĵ",
+      "å¼Ĥ åij³",
+      "åĴ ļ",
+      "åĬ į",
+      "宽 éĺĶ",
+      "æļ´ 涨",
+      "æĥł åıĬ",
+      "è§Ħ ç¨ĭ",
+      "ä¾Ľ åħ»",
+      "éĢģ å¾Ģ",
+      "å±± åºĦ",
+      "举 äºļ",
+      "å±ķ é¦Ĩ",
+      "解 éĶģ",
+      "æĹł è§Ĩ",
+      "éĻį èIJ½",
+      "è¿ŀ äºij",
+      "è¿ŀäºij 港",
+      "åıĤ è°ĭ",
+      "çİ ĸ",
+      "ç¬ ĥ",
+      "èĢĹ è´¹",
+      "æī¿ å¾·",
+      "社ä¼ļ æķĪçĽĬ",
+      "åįĹæµ· ç½ij",
+      "åĪĽ 伤",
+      "èIJ ±",
+      "åħħ æ²Ľ",
+      "ç½ijç«Ļ 建设",
+      "大 åºĨ",
+      "åĨį éĢł",
+      "åŃĹ æł·",
+      "åħ¨æ°ij åģ¥èº«",
+      "èĮ« èĮ«",
+      "æµ® åĬ¨",
+      "åīį åı°",
+      "å¢ŀ 设",
+      "éĢĽ è¡Ĺ",
+      "åĢĴ éĹŃ",
+      "æ³ķå¾ĭ 顾éĹ®",
+      "çĸ ®",
+      "çĹħ çĹĩ",
+      "空 åīį",
+      "请 æķĻ",
+      "èĥľ ä»»",
+      "æĿĢ èıĮ",
+      "æĪĺæĸĹ æľº",
+      "ç»ĺ åĪ¶",
+      "å¤Ħ æĸ¹",
+      "çªģ åĽ´",
+      "çĮ« åĴª",
+      "æĬ¥åijĬ æĺ¾ç¤º",
+      "ç¿ Ł",
+      "çķ¶ åľ°",
+      "æľĢ éļ¾",
+      "纪 å§Ķ书记",
+      "ä½İ åİĭ",
+      "èĻļ 空",
+      "è¿Ļéĥ¨ çĶµå½±",
+      "产ä¸ļ åįĩ级",
+      "è°· çĪ±",
+      "è°·çĪ± åĩĮ",
+      "æĬ¼ éĩij",
+      "女 æĸ¹",
+      "éĴ» çłĶ",
+      "æļĹ æļĹ",
+      "è¿· ä½ł",
+      "æīĢ è¬Ĥ",
+      "å¨ģ å»ī",
+      "å¼Ģ æľĹ",
+      "å² Ķ",
+      "çģ« çĤ¬",
+      "åIJĪçIJĨ æĢ§",
+      "åħ¬ åĬŀ",
+      "ä¼ļ ä¼ļéķ¿",
+      "éĺ´ è°ĭ",
+      "å¼Ģ å±Ģ",
+      "æĻ®éĢļ è¯Ŀ",
+      "åį¡ æĭī",
+      "å°ij åIJĥ",
+      "éĹª èĢĢ",
+      "æŀľ æ±ģ",
+      "æī§è¡Į åĬĽ",
+      "è° Ľ",
+      "æĬ¢ åĬ«",
+      "é«ĺéĢŁ åıijå±ķ",
+      "éŁ ¬",
+      "åįĹ æ²Ļ",
+      "é«ĺçŃī åŃ¦æł¡",
+      "æį¢ 个",
+      "åı¯èĥ½ åŃĺåľ¨",
+      "æĬ Ĵ",
+      "è°± åĨĻ",
+      "被 æĬĵ",
+      "æĿ¯ åŃIJ",
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+      "æ°ĶåĢĻ åıĺåĮĸ",
+      "åĪĨ åĪ¥",
+      "ä¸Ń æŀ¢",
+      "欢 åij¼",
+      "åħī 纤",
+      "è¿Ļ 群",
+      "çľ¼ çķĮ",
+      "åħ±åIJĮ åıijå±ķ",
+      "çİ° ä»Ĭ",
+      "éĹ» è¨Ģ",
+      "çī¹èī² å°ıéķĩ",
+      "æķij 人",
+      "éĻį æ°´",
+      "ä¸ĸçķĮ ä¸Ģæµģ",
+      "å°± é¤IJ",
+      "çŀ ¥",
+      "å¤į ä»ĩ",
+      "ç¾½ æ¯Ľ",
+      "ç¾½æ¯Ľ çIJĥ",
+      "è´© åįĸ",
+      "æºIJ æ³ī",
+      "æĢ»ä½ĵ è§ĦåĪĴ",
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+      "ä¸Ģ 审",
+      "åĢŁ éĴ±",
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+      "èĬ± èįī",
+      "åIJĮ ä¸ļ",
+      "æŁ¥ è©¢",
+      "åĽ½éĻħ åIJĪä½ľ",
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+      "åģ ´",
+      "æł ĵ",
+      "缸 éĢļ",
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+      "è¿ĩç¨ĭ å½ĵä¸Ń",
+      "é¦Ļ èıĩ",
+      "åįģåĽĽ æĿ¡",
+      "ä¸Ģå¼Ģå§ĭ å°±",
+      "ä¸ĵ åijĺ",
+      "æĺİ é¡¯",
+      "æīĵéĢł åĩº",
+      "ä¸ĭéĿ¢ æĪij们",
+      "æľº æ²¹",
+      "åı° è¯į",
+      "åŃIJ å¼Ł",
+      "æľĢ 常è§ģçļĦ",
+      "æĪij è®°å¾Ĺ",
+      "ç» °",
+      "æĤ¬ æµ®",
+      "è¿ĺ 羣æĺ¯",
+      "æĮĤ åı·",
+      "åıĭ åĸĦ",
+      "éĩį 伤",
+      "çħ§ 亮",
+      "æѦ èѦ",
+      "åĩºçİ° éĹ®é¢ĺ",
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+      "åľ°çIJĥ ä¸Ĭ",
+      "å¸Ĥ 人大",
+      "åıĹ害 人",
+      "å² IJ",
+      "åIJĮ åѸ",
+      "éĩijèŀį å¸Ĥåľº",
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+      "å¸Ĥ æķĻèĤ²",
+      "å¸ĤæķĻèĤ² å±Ģ",
+      "åIJĦ å¼Ĥ",
+      "ç·ļ ä¸Ĭ",
+      "æģ º",
+      "æľī 大éĩıçļĦ",
+      "åķĨ æĬ¥",
+      "åįķ åįķ",
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+      "好 åĩłä¸ª",
+      "åĸ µ",
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+      "çĶŁæ´» è´¨éĩı",
+      "æİ¢ 访",
+      "åį° èĬ±",
+      "缼 è¡Į",
+      "å¾® è§Ĥ",
+      "èĪį å¾Ĺ",
+      "åºŁå¼ĥ çī©",
+      "积 èĵĦ",
+      "å®ļ å±ħ",
+      "æĤ ¼",
+      "èĮ ¸",
+      "çļĦ 帮åĬ©",
+      "çļĦ帮åĬ© ä¸ĭ",
+      "亿 åIJ¨",
+      "åŃĶ éĽĢ",
+      "è¿ĻæĿ¡ è·¯",
+      "é¥ µ",
+      "æĦĪ åĬł",
+      "éķ į",
+      "ä½ľ æ¡Ī",
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+      "太 å°ij",
+      "跻 身",
+      "åħ¬çĽĬ æ´»åĬ¨",
+      "çĻ½ æĸij",
+      "æĬĢæľ¯ æ°´å¹³",
+      "å¸ §",
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+      "éĢĢ å¸Ĥ",
+      "æ¸ Ń",
+      "åħ» çĮª",
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+      "群 å²Ľ",
+      "大 åį«",
+      "ä¹ĺ çĶ¨è½¦",
+      "èı² å°Ķ",
+      "è´´ åIJ§",
+      "åģľ ä¸ĭæĿ¥",
+      "æľīæľº ç»ĵåIJĪ",
+      "åĪ» èĭ¦",
+      "çļĦ åľ°",
+      "çļĦåľ° æŃ¥",
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+      "çŃ¹ çłģ",
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+      "楼 æĪ¿",
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+      "åħĴ åŃIJ",
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+      "大 æ´ĭ",
+      "æĭ¼ éŁ³",
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+      "æ² ¼",
+      "ç©¿ æIJŃ",
+      "éĤ£ ä¸Ģ天",
+      "çł´ éŨ",
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+      "赢 家",
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+      "æ¿ ĥ",
+      "å®ī æ£Ģ",
+      "客 家",
+      "çĭ¬ç«ĭ èij£äºĭ",
+      "æīĭ åĬ¿",
+      "åīµ éĢł",
+      "åľĨ满 å®ĮæĪIJ",
+      "为主 线",
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+      "头 æĻķ",
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+      "éĻįä½İ æĪIJæľ¬",
+      "æĶ¾ æīĭ",
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+      "修 士",
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+      "羣 çĪ±",
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+      "ä¸Ģ群 人",
+      "ç¾ ¯",
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+      "åģ ī",
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+      "大éĥ¨åĪĨ 人",
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+      "ç¸ ®",
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+      "使çĶ¨ 網路",
+      "é¢Ħ çķĻ",
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+      "åıijæĺİ ä¸ĵåĪ©",
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+      "äºĶ åĽĽ",
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+      "æł¹ åºķ",
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+      "顾 èĻij",
+      "éĦ Ń",
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+      "è´¢ è¿IJ",
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+      "åij¼ åĶ¤",
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+      "龸 éģĵ",
+      "å±± åĿ¡",
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+      "主 é¡Į",
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+      "å§Ķç»Ħç»ĩ éĥ¨",
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+      "室 åıĭ",
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+      "çģµ æķı",
+      "审 è§Ĩ",
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+      "山 寨",
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+      "é©° æı´",
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+      "好 似",
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+      "åľ¨æĪij çľĭæĿ¥",
+      "åħ³æ³¨ 度",
+      "éĻĪ æŁIJ",
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+      "ç²¾ åŃIJ",
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+      "æ±Ł æ·®",
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+      "è¼ ©",
+      "åѦ åłĤ",
+      "æĤ¨ åIJĮæĦı",
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+      "éĸ ĥ",
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+      "ä¿ ĺ",
+      "æ±Ł åİ¿",
+      "æ³ ¾",
+      "ç§ij æķĻ",
+      "æīĵ è¿Ľ",
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+      "å¯Ĵ åĨ¬",
+      "æ¸Ķ æ°ij",
+      "鼷 æĸ¯",
+      "主 宰",
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+      "æ±Ĥ å©ļ",
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+      "åģ¥èº« æĪ¿",
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+      "äºĭæķħ åıijçĶŁ",
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+      "åŃĺ æ´»",
+      "æĸ½ èĤ¥",
+      "èľľ èľĤ",
+      "åµ ©",
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+      "æĬĹ æĭĴ",
+      "ä¼ł 导",
+      "æĺ¯ä»Ģä¹Ī åij¢",
+      "ä¸Ĭå¹´ åIJĮæľŁ",
+      "建 åħļ",
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+      "ä¿Ŀ ä½ı",
+      "款 车åŀĭ",
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+      "éļIJ èĶ½",
+      "失 æķĪ",
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+      "ç®Ģ 便",
+      "谢谢 ä½ł",
+      "å®Ī ä½ı",
+      "æĶ¾ æĺł",
+      "è¨Ī çķ«",
+      "çݰ代 çī©æµģ",
+      "é¤IJ 廳",
+      "æķħ å±ħ",
+      "大 大å°ı",
+      "大大å°ı å°ı",
+      "çī¹åĪ« 声æĺİ",
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+      "å¿ĥçIJĨ åĴ¨è¯¢",
+      "è³ ´",
+      "çĮ® è¡Ģ",
+      "å·²ç»ı è¾¾åĪ°",
+      "æīĵ æĭĽåij¼",
+      "åıĮ è¾¹",
+      "ä¸Ģæĸ¹éĿ¢ æĺ¯",
+      "å´ĩ å°ļ",
+      "éĺ¿ å¯Į",
+      "éĺ¿å¯Į æ±Ĺ",
+      "æĮģ æľī人",
+      "è± ģ",
+      "é£İ çŃĿ",
+      "åĬ¨ èį¡",
+      "äºĨä¸Ģ ä¼ļ",
+      "äºĨä¸Ģä¼ļ åĦ¿",
+      "ä¸ĩ 象",
+      "çľĭ çĶµè§Ĩ",
+      "åįģä¸ī æĿ¡",
+      "çĮĽ çĥĪ",
+      "è¦ģ ä¸įçĦ¶",
+      "太æŀģ æĭ³",
+      "å¼ķ çĪĨ",
+      "ç»ıè¿ĩ å¤ļå¹´",
+      "游æĪı éĩĮçļĦ",
+      "é¾Ļ æ³ī",
+      "æłĩ éħį",
+      "è®ĵ ä»ĸåĢij",
+      "éĢł æŀĹ",
+      "åĮºåŁŁ æĢ§",
+      "亿 ä¸ĩ",
+      "æĪĺçķ¥ å¸ĥå±Ģ",
+      "éķĩ æĶ¿åºľ",
+      "åĶ® 票",
+      "çĶŁäº§ å·¥èīº",
+      "éķĩ åħļå§Ķ",
+      "ä¸Ńå°ı åŀĭ",
+      "æľ¨ èĢ³",
+      "æ²³ è¾¹",
+      "èĦ¾ èĥĥ",
+      "欢è¿İ æĤ¨",
+      "åıĺ å¼Ĥ",
+      "缤 纷",
+      "åŀĥåľ¾ 桶",
+      "辩 è¯ģ",
+      "车 åºĵ",
+      "æ¯Ķ çİĩ",
+      "åħ´ æĹº",
+      "详ç»Ĩ äºĨ解",
+      "å®ī å±ħ",
+      "çħ§ æĸĻ",
+      "æĸ¹ æīį",
+      "èµ ¦",
+      "åĨ ķ",
+      "å¥Ķ èµ´",
+      "å®Ŀ 鸡",
+      "åľº åĿĩ",
+      "缮åīį æŃ£åľ¨",
+      "åIJŀ åĻ¬",
+      "è¿° èģĮ",
+      "æĩ µ",
+      "å¥ĩ çijŀ",
+      "ä»į å°Ĩ",
+      "èĪī 辦",
+      "å·¥åķĨ å±Ģ",
+      "å¡ij èĥ¶",
+      "åĬŀ å®ŀäºĭ",
+      "æĸ¹ æĸ¹éĿ¢",
+      "æĸ¹æĸ¹éĿ¢ éĿ¢",
+      "æĸĩåĮĸ èĬĤ",
+      "åħ¥ èģĮ",
+      "é¸ ¥",
+      "ç©¿ éĢı",
+      "以 ä¹łè¿ijå¹³",
+      "åį± éļª",
+      "æľ¦ èĥ§",
+      "åİĨåı² æĢ§",
+      "æķŀ å¼Ģ",
+      "ä¼Ļä¼´ åħ³ç³»",
+      "çŁ¿ åĮº",
+      "åĽ½éĻħ åľ¨çº¿",
+      "ä¼łå¥ĩ éĩĮéĿ¢",
+      "è¿ij äºĽ",
+      "è¿ijäºĽ å¹´",
+      "åĬ£ åĬ¿",
+      "æĶ»åĩ» åĬĽ",
+      "æĻº éĢł",
+      "ç¦ §",
+      "çİĭ åħĪçĶŁ",
+      "éĨ« çĶŁ",
+      "åĽĽ 项",
+      "å®ŀ æĻ¯",
+      "åĪĿ åĪĽ",
+      "å¿ĥ 裡",
+      "æĻ¶ ä½ĵ",
+      "交 éĻħ",
+      "让 æ¶Īè´¹èĢħ",
+      "课 æĸĩ",
+      "æİĴ æ°Ķ",
+      "并ä¸į æĦıåij³",
+      "缸 声",
+      "第ä¸Ģ å±Ĭ",
+      "åİŁ èijĹ",
+      "éĽ ľ",
+      "没æľī 太大",
+      "è¡¥ æ°´",
+      "çī©æµģ ä¼ģä¸ļ",
+      "第äºĮ æī¹",
+      "åħ¶å®ĥ éĹ®é¢ĺ",
+      "æİĮ éŨ",
+      "责任 å¿ĥ",
+      "é¤IJ åħ·",
+      "ç¾Ĭ æ¯Ľ",
+      "没æľī å¿ħè¦ģ",
+      "ä¹IJ åĽ¢",
+      "è¿Ľ åŁİ",
+      "ä¸ĢçĤ¹ åĦ¿",
+      "身 形",
+      "çļ®èĤ¤ çĹħ",
+      "æĺ ±",
+      "å¢ŀ èĩ³",
+      "èģ² æĺİ",
+      "æıIJ è´¨",
+      "ä½ĵèĤ² åľº",
+      "çŃ¹ 建",
+      "é¬ Ĩ",
+      "车 çīĮ",
+      "éļĶ éŁ³",
+      "è´Łè´£ åIJĮå¿Ĺ",
+      "丰 ç¡ķ",
+      "ä½Ľ éĻĢ",
+      "äºī åIJµ",
+      "åº ¶",
+      "æ·¡ æ°´",
+      "å°ı çĶ·åŃ©",
+      "ç§ģ èĩª",
+      "åĮĸ è¿Ľç¨ĭ",
+      "æĪĺ士 æĿ¥è¯´",
+      "æ²¹ èħ»",
+      "èĦ±è´« èĩ´å¯Į",
+      "æĹ¥å¸¸ å·¥ä½ľ",
+      "交 èŀį",
+      "åĨľ è´¸",
+      "åĨľè´¸ å¸Ĥåľº",
+      "åĵĪ çĻ»",
+      "çĶµ è´¹",
+      "èµ ĺ",
+      "åıĮ èħ¿",
+      "æĵĶ å¿ĥ",
+      "æĿ¥ 形容",
+      "使åij½ æĦŁ",
+      "éĤ£ä¹Ī ç®Ģåįķ",
+      "èĬĻ èĵī",
+      "åĢŁæ¬¾ 人",
+      "ç§Ģ 丽",
+      "è®ĵ ä»ĸ",
+      "严åİī æīĵåĩ»",
+      "è³ ŀ",
+      "æļ «",
+      "çħ¤ æ°Ķ",
+      "çĪ¬ ä¸Ĭ",
+      "æ½ĩ æ´Ĵ",
+      "太 ä¹ħ",
+      "åij½ åIJį为",
+      "è·¯ çĶ±",
+      "è·¯çĶ± åĻ¨",
+      "é© ¯",
+      "æıIJ æĹ©",
+      "æĬĹåĩ» çĸ«æĥħ",
+      "åĩ Ľ",
+      "交 åıĭ",
+      "éĶĢåĶ® æ¸łéģĵ",
+      "毫ä¸į çĬ¹è±«",
+      "èIJ¥ åľ°",
+      "çłĶ究 表æĺİ",
+      "é±¼ ç±»",
+      "æį¢ å±Ĭ",
+      "æİ¡ åıĸ",
+      "çī Ĩ",
+      "缼 å¼Ģ",
+      "沧 æ¡ij",
+      "åºŃ 审",
+      "ç»ı æŁ¥",
+      "åĬł å¼·",
+      "缸æ¯Ķ äºİ",
+      "ä¸ĵ çıŃ",
+      "ä½ĵ åŀĭ",
+      "被 害",
+      "被害 人",
+      "æĶ¶ 款",
+      "åħ·æľī èī¯å¥½",
+      "é«ĺå³° æľŁ",
+      "åģı ä½İ",
+      "åĦ Ł",
+      "åĨľä¸ļ ç§ijæĬĢ",
+      "çī¹æ®Ĭ æĥħåĨµ",
+      "å¦Ĥæŀľ çݩ家",
+      "éķ¿ 约",
+      "第åħŃ å±Ĭ",
+      "åħ¬å¼Ģ æĭĽèģĺ",
+      "åĪĩ æĸŃ",
+      "迫 使",
+      "çĸĹ ç¨ĭ",
+      "第äºĮ ç§į",
+      "ä¸į åħį",
+      "å¹² èѦ",
+      "çŁ³ 榴",
+      "åĹ £",
+      "两 类",
+      "çĪµ 士",
+      "åŁİ乡 å±ħæ°ij",
+      "æѤ 项",
+      "缴 è¾ĸ",
+      "缴è¾ĸ å¸Ĥ",
+      "åij¼ åºĶ",
+      "éĴ ¯",
+      "ç¦ı å¾·",
+      "æľº 身",
+      "æĵį åľº",
+      "æ¿Ĵ 临",
+      "人群 ä¸Ń",
+      "èĤ¡ æ°ij",
+      "åŃ ½",
+      "æ³ķ åħ°",
+      "é¨ İ",
+      "糯 米",
+      "æĢ» çļĦ",
+      "æĢ»çļĦ æĿ¥è¯´",
+      "åħ¸ éĽħ",
+      "æĸ° éĻĪ",
+      "æĸ°éĻĪ 代谢",
+      "缮 çĿ¹",
+      "é¢Ħ è¨Ģ",
+      "è·Į çł´",
+      "æĸ° ç¯ĩç«ł",
+      "æ¯Ĵ æĢ§",
+      "åĸĿ èĮ¶",
+      "æŁ¥ èİ·",
+      "亮 丽",
+      "çĶŁäº§ åķĨ",
+      "æĶ¹ æĪIJ",
+      "为äºĨ æĽ´å¥½",
+      "深 交",
+      "深交 æīĢ",
+      "æİ ĥ",
+      "ä¹Ļ èĤĿ",
+      "泸 å·ŀ",
+      "åħĪè¿Ľ æĬĢæľ¯",
+      "è¾ĵ ç»Ļ",
+      "æķ£ æĪ·",
+      "æĢĿç»´ æĸ¹å¼ı",
+      "åºĹ 主",
+      "è°ĭ æ±Ĥ",
+      "游æĪı æĬĢå·§",
+      "ä¸Ģå¹´ 级",
+      "çľ¼ è§Ĵ",
+      "ä¸Ńä»ĭ æľºæŀĦ",
+      "å·§ åIJĪ",
+      "éĺ² çĽĹ",
+      "导 è´Ń",
+      "æĪ Ĭ",
+      "æĽ´ éĢĤåIJĪ",
+      "åŁºæľ¬ ä¿¡æģ¯",
+      "马 ä¸ģ",
+      "åħ»æ®ĸ åľº",
+      "åıį è¿ĩæĿ¥",
+      "æݨ å´ĩ",
+      "å¯ĨåĪĩ åħ³æ³¨",
+      "åŁºéĩij ç»ıçIJĨ",
+      "æĮī éĶ®",
+      "åĨħéĥ¨ æݧåĪ¶",
+      "æĪIJåijĺ åįķä½į",
+      "æľ¯ è¯Ń",
+      "åĪ¶ æľį",
+      "åĪļ éľĢ",
+      "æ£Ģ ç´¢",
+      "大大 æıIJé«ĺ",
+      "åģ¥åº· 管çIJĨ",
+      "èĩª æѤ",
+      "客æĪ· éľĢæ±Ĥ",
+      "丰 èĥ¸",
+      "èµ· éĩį",
+      "èµ·éĩį æľº",
+      "æ¬ł 缺",
+      "æ¡Ī åŃIJ",
+      "æĥħ人 èĬĤ",
+      "åħļ æł¡",
+      "è¢ ľ",
+      "该 åī§",
+      "迷失 ä¼łå¥ĩ",
+      "ç»ļ 丽",
+      "åķ ª",
+      "æĹł ç§ģ",
+      "éĢ² ä¸ĢæŃ¥",
+      "第ä¸Ģ ç«ł",
+      "åĻ¨ åħ·",
+      "åĨľ èµĦ",
+      "確 實",
+      "åºı åĪĹ",
+      "娱ä¹IJ å¹³åı°",
+      "èŀįèµĦ 秣èµģ",
+      "èµĦæºIJ åħ±äº«",
+      "èģ½ åĪ°",
+      "æIJŀ å¾Ĺ",
+      "继ç»Ń ä¿ĿæĮģ",
+      "åIJ¯ èĴĻ",
+      "çľ º",
+      "ä¸Ŀ è·¯",
+      "设æĸ½ 建设",
+      "æİ¥ åľ°",
+      "æİ¥åľ° æ°Ķ",
+      "第ä¸ī åŃ£åº¦",
+      "åŁº è°ĥ",
+      "åıij éŁ³",
+      "社ä¼ļ èµĦæľ¬",
+      "éĽĩ 主",
+      "è¿ŀ èĥľ",
+      "没 åķ¥",
+      "å» ¢",
+      "赶 赴",
+      "æ¼Ķ åĮĸ",
+      "åı¤ æĢª",
+      "çİĭ çĪ·",
+      "é¢Ħ åħĪ",
+      "å¼Ģ åħ·",
+      "åĽŀ é¦ĸ",
+      "åľ°ä¸ĭ æ°´",
+      "å°ıç¼ĸ ä¸Ģèµ·",
+      "èµİ åĽŀ",
+      "åľ° è²Į",
+      "åĪĿ ä¸ī",
+      "åı¯ çĶ¨äºİ",
+      "éģĹ è¿¹",
+      "è¿Ļ æī¹",
+      "èĸª æ°´",
+      "å¿ħçĦ¶ ä¼ļ",
+      "æ² ½",
+      "éį ĭ",
+      "第ä¸Ģ éĥ¨",
+      "åĪĬ çī©",
+      "å®ŀ ä¾ĭ",
+      "æ¸ħ åĩĢ",
+      "ä¸Ĭ èµĽåŃ£",
+      "åĽ¾ 表",
+      "éĤ® è½®",
+      "åĵª 裡",
+      "缸 è§ģ",
+      "æī° ä¹±",
+      "æ¯ı æ¯ı",
+      "è¿Ļ è¾ĪåŃIJ",
+      "ç¡« éħ¸",
+      "äºī 缸",
+      "溯 æºIJ",
+      "åĩº ä¼Ĺ",
+      "çİī çŁ³",
+      "åħ± çĶŁ",
+      "æŶéĹ´ 段",
+      "éĩįè¦ģ æĮĩ示",
+      "æ¶Īè´¹ éľĢæ±Ĥ",
+      "éķ¿ éķ¿",
+      "éķ¿éķ¿ çļĦ",
+      "å®ī æĬļ",
+      "å¢ŀ é«ĺ",
+      "æľ¬ è½®",
+      "亲 çľ¼",
+      "é£İ æ³¢",
+      "èĢģ å¦Ī",
+      "æĶ¶è´¹ æłĩåĩĨ",
+      "åĨħ éĻĨ",
+      "æĮ¥ åıij",
+      "åįĩ åѦ",
+      "èĥ¸ åīį",
+      "åģı è¿ľ",
+      "纯 æ´ģ",
+      "æĸ½å·¥ åįķä½į",
+      "身 价",
+      "è´¢ åĬĽ",
+      "çº ¶",
+      "è£ħ çĶ²",
+      "æĺ¾ç¤º åĻ¨",
+      "毫 åįĩ",
+      "æ·± çŁ¥",
+      "èĢ¶ ç©",
+      "èĢ¶ç© Į",
+      "è¾ĥ éĩı",
+      "åľ¨ è¿ĩ渡",
+      "åľ¨è¿ĩ渡 æľŁ",
+      "èĮ Ĺ",
+      "ä¸Ģ个 æĺŁæľŁ",
+      "èĬ ·",
+      "è´¿ èµĤ",
+      "æ¿ ķ",
+      "æĩĤ äºĭ",
+      "ç§ §",
+      "åħħ å½ĵ",
+      "åĽ½ ç«ĭ",
+      "èĬ± çĵ£",
+      "éĤĦ è¦ģ",
+      "åħ¬ åľĴ",
+      "触 åĬ¨",
+      "æ³° å·ŀ",
+      "ä»Ģä¹Ī æł·",
+      "æ»ĭ åħ»",
+      "è¯Ħ åĪ¤",
+      "æĮ¥ æīĭ",
+      "èĦ Ī",
+      "姥 姥",
+      "è¿IJ è´¹",
+      "æ¯ħ åĬĽ",
+      "å¿ĥ æĻº",
+      "ä¸į æİĴéĻ¤",
+      "第ä¸ī 代",
+      "éĢĢ è´§",
+      "æĺŁ éĻħ",
+      "æ°¸ åĪ©",
+      "æĬ¤ åį«",
+      "çıŃ è½¦",
+      "è¨Ģ è¡Į",
+      "ç¹ ª",
+      "主åĬ¨ æĢ§",
+      "å·¥ç¨ĭ è´¨éĩı",
+      "éĥĬ åĮº",
+      "ä¸Ģ æłĭ",
+      "ä½Ĩ å®ŀéĻħä¸Ĭ",
+      "ä¸ī大 èģĮä¸ļ",
+      "åij¼ åı«",
+      "女 åħĴ",
+      "è¯ģåĪ¸ æĬķèµĦ",
+      "èĢĥ æħ®",
+      "çĤ« èĢĢ",
+      "治 好",
+      "åĺ ¶",
+      "èĥ ¤",
+      "åħīä¼ı åıijçĶµ",
+      "åĩł æŃ¥",
+      "æīĢ æīĢ",
+      "æīĢæīĢ éķ¿",
+      "çħ§ æł·",
+      "åĵ¥ 们",
+      "è¯ Ľ",
+      "è¿Ļä¸Ģ åĪ»",
+      "çŁ¿ çī©è´¨",
+      "ä¸įå¾Ĺ å·²",
+      "åIJĮ 缣",
+      "ç»Ĩ å¾®",
+      "è·¯ èĻİ",
+      "çĻ¾ èĬ±",
+      "æ·· æ²Į",
+      "ä¸Ĭæµ· è¯ģåĪ¸",
+      "éĢĢ ç¨İ",
+      "èµŀ åı¹",
+      "æī®æ¼Ķ 游æĪı",
+      "åIJį åĪĹ",
+      "åIJįåĪĹ åīį",
+      "åIJįåĪĹåīį èĮħ",
+      "ç±³ å°Ķ",
+      "ä»Ģä¹Ī åİŁåĽł",
+      "å®īåħ¨ ä¿Ŀéļľ",
+      "ä¸Ģåıª æīĭ",
+      "ä¹³ ä¸ļ",
+      "ä¸į çĶĺ",
+      "æĥħ åķĨ",
+      "æĮ¡ ä½ı",
+      "åİŁåĽł ä¹ĭä¸Ģ",
+      "è¿Ļ 两天",
+      "çĥĺ çĦĻ",
+      "è± ¬",
+      "ä½ł 以为",
+      "没 è§ģè¿ĩ",
+      "åĵªå®¶ 好",
+      "åīį ä»»",
+      "è¿Ľ è´§",
+      "éĢĢ åĽŀ",
+      "串 èģĶ",
+      "èĩ³ æĸ¼",
+      "åĨ° æ·ĩ",
+      "åĨ°æ·ĩ æ·ĭ",
+      "æŁ¥çľĭ 详æĥħ",
+      "çı¾ 實",
+      "æݨ æµĭ",
+      "æİ¥ æīĭ",
+      "éļ¶ å±ŀäºİ",
+      "åŁİå¸Ĥ 群",
+      "æĿİ åħĪçĶŁ",
+      "çŁ¿ æ³īæ°´",
+      "çī¹ ä»·",
+      "æĽ´å¤ļ 精彩",
+      "ç¨ĭ å¼ı",
+      "读 æĩĤ",
+      "å±ı èĶ½",
+      "奥 æŀĹ",
+      "奥æŀĹ åĮ¹",
+      "奥æŀĹåĮ¹ åħĭ",
+      "红 èĸ¯",
+      "å¥ ®",
+      "å®Ŀ çİī",
+      "網 絡",
+      "è² §",
+      "欧 å¼ı",
+      "çĻ½ ç³ĸ",
+      "èĩªçĦ¶ çģ¾å®³",
+      "åijĬè¯ī 她",
+      "å» ļ",
+      "çĤ¹åĩ» æŁ¥çľĭ",
+      "é£İ 湿",
+      "èµĦ产 éĩįç»Ħ",
+      "ä¹Łä¸į ä¾ĭå¤ĸ",
+      "åįĬ 个å°ıæŶ",
+      "åIJ¸å¼ķ æĽ´å¤ļ",
+      "æŶéĹ´ èĬĤçĤ¹",
+      "æĶ¶ 纳",
+      "åIJ¸ æ¯Ĵ",
+      "èĢģ 乡",
+      "çIJ ħ",
+      "æľĢ çµĤ",
+      "åıį æĦŁ",
+      "çĶ¨ 微信",
+      "çĶ¨å¾®ä¿¡ æī«",
+      "éĢŁ çİĩ",
+      "大 çĨĬçĮ«",
+      "åı¯ æĥ³",
+      "åı¯æĥ³ èĢĮ",
+      "åı¯æĥ³èĢĮ çŁ¥",
+      "åĴ §",
+      "èµ° åħ¥",
+      "碳 éħ¸",
+      "èĮĥ åĨ°",
+      "èĮĥåĨ° åĨ°",
+      "被 åĪ¤",
+      "积æŀģ æݨåĬ¨",
+      "足 足",
+      "ç²Ĵ åŃIJ",
+      "大 å®Ĺ",
+      "大å®Ĺ åķĨåĵģ",
+      "ç½ij绾 ç§ijæĬĢ",
+      "æĽ¼ åŁİ",
+      "å·² ä¹ħ",
+      "å·²ä¹ħ çļĦ",
+      "秦 çļĩ",
+      "秦çļĩ å²Ľ",
+      "ä»» æķĻ",
+      "åĶ¯ ç¾İ",
+      "æ·¡ åĮĸ",
+      "æ¡Ĥ èĬ±",
+      "çŁ¥è¯Ĩ åĪĨåŃIJ",
+      "æĩĴ å¾Ĺ",
+      "主 åħ¬",
+      "设计 çIJĨ念",
+      "è³ º",
+      "æīĢ æıIJä¾Ľ",
+      "æīĢæıIJä¾Ľ ä¹ĭ",
+      "æĶ» åħĭ",
+      "åĤ ¾",
+      "è¯Ń æ³ķ",
+      "åįĥ åı¤",
+      "éĸĭ æĶ¾",
+      "第ä¸Ģ èĬĤ",
+      "éĤĦ æ²Ĵ",
+      "éĢĥ çĶŁ",
+      "æ³ Ĺ",
+      "åİ¿ å§Ķ书记",
+      "ä½ľèĢħ æīĢæľī",
+      "çħ ½",
+      "ç» ħ",
+      "æł ħ",
+      "æľ´ ç´ł",
+      "çijķ çĸµ",
+      "åĮħ åĮħ",
+      "æ°ij主 åħļ",
+      "ä¸į è¿ľå¤Ħ",
+      "å¥ĩ å¼Ĥ",
+      "åĺ» åĺ»",
+      "æī ¼",
+      "ç¿» å¼Ģ",
+      "æĢİ èĥ½",
+      "éģ´ éĢī",
+      "解 éĩĭ",
+      "å¹¼ ç¨ļ",
+      "è¦ģ 好好",
+      "趴 åľ¨",
+      "ç´¢ åıĸ",
+      "ç»Ī çĶŁ",
+      "åħ¨ æµģç¨ĭ",
+      "éģ© çķ¶",
+      "åįıè°ĥ åıijå±ķ",
+      "æĬ¥ ä»ĩ",
+      "ç§ijæĬĢ åĽŃ",
+      "ä»Ģä¹Ī éĥ½ä¸į",
+      "æľĢåIJİ ä¸Ģ次",
+      "ç»Ļ人 ä¸Ģç§į",
+      "æł¸ å®ļ",
+      "被 åĪĹåħ¥",
+      "æĦı æĥ³ä¸įåĪ°",
+      "èĢĥ æŁ¥",
+      "åľ¨æѤ ä¹ĭåīį",
+      "æīĵ çIJĥ",
+      "è¶ĬæĿ¥è¶Ĭ å°ij",
+      "å®ļ å¾ĭ",
+      "è¡ĮæĶ¿ æľºåħ³",
+      "ä½ıæĪ¿ åħ¬ç§¯",
+      "å°ıå§IJ å§IJ",
+      "ä¸ī èı±",
+      "ä¿® è¡¥",
+      "èŀĥ èŁ¹",
+      "西 çĶ²",
+      "æĢ ł",
+      "çŃī å¤ļ项",
+      "产ä¸ļ éĽĨèģļ",
+      "ä»·æł¼ ä¸Ĭ涨",
+      "åħ¬åħ± åľºæīĢ",
+      "è¢ĭ åŃIJ",
+      "æĨ§ æĨ¬",
+      "çļĦæĸ¹å¼ı æĿ¥",
+      "åĪ° è´¦",
+      "çģ ½",
+      "å·´ èı²",
+      "å·´èı² çī¹",
+      "æ¼Ķ ä¹ł",
+      "èŃ¦ç¤º æķĻèĤ²",
+      "çķı æĥ§",
+      "å¼ķ æµģ",
+      "æĶ¶ æĶ¯",
+      "å±Ĥ åĩº",
+      "å±Ĥåĩº ä¸į",
+      "å±Ĥåĩºä¸į ç©·",
+      "æijĩ æ»ļ",
+      "辦 çIJĨ",
+      "纵 è§Ĥ",
+      "æķij æµİ",
+      "家 éĥ½çŁ¥éģĵ",
+      "åĮ ¯",
+      "å°ı 鸣",
+      "ä»» åĭĻ",
+      "计 åħ¥",
+      "ç«ŀ éĢī",
+      "å¼ĢèįĴ æĹ¶æľŁ",
+      "åij¨ æģ©",
+      "åij¨æģ© æĿ¥",
+      "交 ç»ĩ",
+      "çķ¢ æ¥Ń",
+      "æł¹æį® èĩªå·±",
+      "æĸ°äºº çݩ家",
+      "åѵåĮĸ åĻ¨",
+      "éĩĩ æļĸ",
+      "å¹³åĿĩ æ°´å¹³",
+      "åħ¬å¼Ģ 课",
+      "失 åĪ©",
+      "伺 æľį",
+      "çĬ ģ",
+      "忽 æĤł",
+      "主è¦ģ éĽĨä¸Ń",
+      "æ¤į æłij",
+      "æ¯Ĺ éĤ»",
+      "èĩº çģ£",
+      "åĩºåĽ½ çķĻåѦ",
+      "æĬĹ éľĩ",
+      "æĥ© æĪĴ",
+      "å¹´åºķ åīį",
+      "åĴ¸ éĺ³",
+      "æ°ij å±ħ",
+      "大çIJĨ çŁ³",
+      "éĿ ³",
+      "éķ ĸ",
+      "æ¸ħ è¿ľ",
+      "è£ħ è½½",
+      "èĩ Ģ",
+      "å½± ä¸ļ",
+      "å¼Ł åħĦ",
+      "æĤ² è§Ĥ",
+      "çĿĢçľ¼ äºİ",
+      "æįį åį«",
+      "åī¥ 夺",
+      "ç¯ Ĩ",
+      "å¾Ī éķ¿æŶéĹ´",
+      "è¥ Ł",
+      "第ä¸Ģ çĻ¾",
+      "ä¸ĢåĪĨ éĴ±",
+      "æĸ°éĹ» è®°èĢħ",
+      "éķ· æľŁ",
+      "æ³ķ æĪĺç»ĦåIJĪ",
+      "è°ģ çŁ¥éģĵ",
+      "èħ° éĥ¨",
+      "æ±ī åł¡",
+      "åħ¥ çĿ¡",
+      "åįĸ æİī",
+      "æ¶Īè²» èĢħ",
+      "æĥ¯ ä¾ĭ",
+      "æĥ³ äºĨ",
+      "æĥ³äºĨ æĥ³",
+      "èĢģæŧ å°ıåĮº",
+      "ä¼ł è¨Ģ",
+      "åĪĨæķ° 线",
+      "æµģ 泪",
+      "ç»Ħç»ĩ é¢Ĩ导",
+      "äºļ åĨĽ",
+      "å¢ŀåĢ¼ æľįåĬ¡",
+      "å¾ ¹",
+      "ä¼ ¶",
+      "äºĽ 许",
+      "å¸ĥ èݱ",
+      "强 æĤį",
+      "宫 廷",
+      "绿 èĮ¶",
+      "åĮ ¡",
+      "å¾Ī æŃ£å¸¸",
+      "æĺ¥ å¤ı",
+      "æ¯ Ļ",
+      "è¯Ħ æ¯Ķ",
+      "åĩ¡ äºĭ",
+      "æĬī æĭ©",
+      "åĢĴ éľī",
+      "éĩį 度",
+      "åįıä¼ļ ä¼ļéķ¿",
+      "忧 èĻij",
+      "ä¸ĭ ä¸Ģç¯ĩ",
+      "沪 深",
+      "æĪ İ",
+      "æīĵ ä»Ĺ",
+      "åįĪ é¥Ń",
+      "å¹´é¾Ħ 段",
+      "ä¸ŃåĽ½ 足çIJĥ",
+      "设计 æĸ¹æ¡Ī",
+      "åºĶçĶ¨ æŁ¥çľĭ",
+      "é¢Ħ æĸĻ",
+      "åĹ ¡",
+      "ç¥ĸ çĪ¶",
+      "çļĦä¸Ģ åijĺ",
+      "æ´Ĺ å¹²åĩĢ",
+      "åİĨåı² æĸ°",
+      "åİĨåı²æĸ° é«ĺ",
+      "çĭ¬ åħ·",
+      "æħĭ 度",
+      "æīĵ 交",
+      "æīĵ交 éģĵ",
+      "é»Ħ çŁ³",
+      "çĽ¼ æľĽ",
+      "çī§ åľº",
+      "转 弯",
+      "åįĩ åįİ",
+      "åĨį ä¹Łæ²¡æľī",
+      "èĭ± æīį",
+      "æĽ´ åIJį为",
+      "åĢŁ çĶ¨",
+      "çºł éĶĻ",
+      "ç»Ŀ对 ä¸įä¼ļ",
+      "çİĭ çīĮ",
+      "çĽĨ åľ°",
+      "失 è°ĥ",
+      "好 象",
+      "é³ ¥",
+      "ä¿Ŀ ä¿®",
+      "åĽĽä¸ª èĩªä¿¡",
+      "头 çļ®",
+      "åİŁ åīĩ",
+      "æĬ¥ æ¡Ī",
+      "奴 éļ¶",
+      "å³ Ļ",
+      "è°ĥ æĸĻ",
+      "ä¹Ł 許",
+      "èIJ½ åĪ°",
+      "èIJ½åĪ° å®ŀ",
+      "èIJ½åĪ°å®ŀ å¤Ħ",
+      "çĦļ çĥ§",
+      "çĶŁæ´» çݯå¢ĥ",
+      "åºĶ åıĬæŶ",
+      "è¶Ĭ è¿ĩ",
+      "æĦŁ è¬Ŀ",
+      "æĻ¯ å¾·",
+      "æĻ¯å¾· éķĩ",
+      "çĬ Ģ",
+      "身 éĤĬ",
+      "ç¨İåĬ¡ æĢ»å±Ģ",
+      "åĩĢ åľŁ",
+      "ä¾µ åįł",
+      "åĬ¨ å·¥",
+      "å¹´ ä¹ĭ",
+      "å¹´ä¹ĭ ä¹ħ",
+      "第äºĮ èĬĤ",
+      "åĬ¨çī© åĽŃ",
+      "第ä¸Ģ 书记",
+      "éħ ļ",
+      "çĶŁäº§ 设å¤ĩ",
+      "æŁIJç§į ç¨ĭ度",
+      "åľ Ń",
+      "åĩŃåĢŁ çĿĢ",
+      "éĺħ è§Ī",
+      "çĻ½ æ²Ļ",
+      "æ²¹ çĥŁ",
+      "çªģçł´ åı£",
+      "åıĹ å½±åĵį",
+      "åı¯ä»¥ æĽ´å¥½",
+      "å³° åĢ¼",
+      "æĿĤ è´¨",
+      "宿 è¿ģ",
+      "çĽĺ æ´»",
+      "æ¿Ģ èµ·",
+      "åĦ¿ ç§ij",
+      "åĿIJ èIJ½åľ¨",
+      "æĮª å¨ģ",
+      "æµ· å²Ľ",
+      "绣 绣",
+      "éĻ ¨",
+      "ä¼ĺ äºİ",
+      "å°Ī 家",
+      "ä¸Ģ éĤĬ",
+      "èIJ Ĭ",
+      "äºĨä¸Ģ åı£",
+      "æ²ĥå°Ķ æ²ĥ",
+      "æŃ£å¸¸ 使çĶ¨",
+      "æĻ®éģį åŃĺåľ¨",
+      "丰 满",
+      "çĶ» åį·",
+      "åºĶ æĶ¶",
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+      "åºĶæĶ¶è´¦ 款",
+      "å®Įæķ´ çĥŃ",
+      "å®Įæķ´çĥŃ æ¦ľ",
+      "注 è§Ĩ",
+      "çĨ Ħ",
+      "èº ¬",
+      "éĶĢåĶ® 人åijĺ",
+      "è¶ĭ åIJij",
+      "çĦ¦ æĢ¥",
+      "åįģå¹´ åīį",
+      "ä¼łç»Ł 产ä¸ļ",
+      "質 éĩı",
+      "åĩ¤åĩ° ç½ij",
+      "èµĦæºIJ æķ´åIJĪ",
+      "æ¶Į åħ¥",
+      "æĸĩåĮĸ ä¼łæĴŃ",
+      "çķĮ 第ä¸Ģ",
+      "æ°´ æ³µ",
+      "宫 殿",
+      "æİ¢ 寻",
+      "ä¿® åīª",
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+      "ç´Ĭ ä¹±",
+      "æĽ ī",
+      "çĻ½ è¡£",
+      "èĻİ åį«",
+      "ç´§ æī£",
+      "å¤Ħå¤Ħ éķ¿",
+      "åĪĽå»º å·¥ä½ľ",
+      "红 æŀ£",
+      "饼 干",
+      "äºĨ åįĬ天",
+      "ä¼ļå½±åĵį åĪ°",
+      "çĽ¸ä¿¡ 大家",
+      "èħ¾ é£ŀ",
+      "å°± å¦ĤåIJĮ",
+      "ä¸ĭéĿ¢ å°ıç¼ĸ",
+      "æ°ijèIJ¥ ç»ıæµİ",
+      "æĻ ¦",
+      "è£ħ æī®",
+      "é»ij å¤ľ",
+      "常 德",
+      "å·¥ä¸ļ 大åѦ",
+      "æĺİ çŁ¥",
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+      "åIJ¬ 课",
+      "æ¯ı éļĶ",
+      "羣æĺ¯ å¤ª",
+      "åIJĪä½ľ åħ±èµ¢",
+      "çIJĨ åıij",
+      "æīį å¹²",
+      "çľĭ èµ·ä¾Ĩ",
+      "殿 ä¸ĭ",
+      "å®ī éĺ³",
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+      "æį® æĬ¥éģĵ",
+      "éļĨéĩį 举è¡Į",
+      "交 éĶĻ",
+      "è¶ħ é¢Ŀ",
+      "åĮĸ çĸĹ",
+      "é¡ Ĩ",
+      "纵 深",
+      "çĪ±åĽ½ 主ä¹ī",
+      "éĻ¢ åī¯éĻ¢éķ¿",
+      "è® ³",
+      "羣æŃ£ åģļåĪ°",
+      "åѤ åįķ",
+      "èĩªçĦ¶ èĢĮ",
+      "èĩªçĦ¶èĢĮ çĦ¶",
+      "修 身",
+      "èĬ ¹",
+      "æģ¯ æģ¯",
+      "æģ¯æģ¯ 缸åħ³",
+      "驾 æł¡",
+      "æİ© 饰",
+      "æ³½ è¿ŀ",
+      "æ³½è¿ŀ æĸ¯åŁº",
+      "举 æŃ¢",
+      "管çIJĨ ä½ĵåĪ¶",
+      "åħ¶ä¸Ń ä¹ĭä¸Ģ",
+      "æĿ¾ å¼Ľ",
+      "æĭ¦ æĪª",
+      "åį« åģ¥",
+      "åį«åģ¥ å§Ķ",
+      "ä»İ åݻ年",
+      "åĤ ¢",
+      "è´Ń 票",
+      "åĽ¾ æłĩ",
+      "河 西",
+      "æ°ijæĶ¿ å±Ģ",
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+      "åľ° ä¸Ń",
+      "åľ°ä¸Ń æµ·",
+      "æµĵ æµĵ",
+      "æµĵæµĵ çļĦ",
+      "å§ĭ 建",
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+      "ç¶ĵ æŃ·",
+      "è·¯ æ¼Ķ",
+      "æļ´ é£İ",
+      "åŁº è¾ħ",
+      "æī¶è´« å·¥ä½ľ",
+      "ä¸Ģ缴 å¤Ħäºİ",
+      "æĥħ 趣",
+      "äºĮ åŃ£åº¦",
+      "åİĮ æģ¶",
+      "顺åĪ© å®ĮæĪIJ",
+      "æŁ¥ å°ģ",
+      "顶 端",
+      "ä¸į åŃķ",
+      "ä¸Ģ大 åłĨ",
+      "被 æ·ĺæ±°",
+      "æĺ¯ çĶ¨æĿ¥",
+      "æľĢ åIJĪéĢĤ",
+      "亮 çľ¼",
+      "并ä¸įæĺ¯ å¾Ī",
+      "ç§ijçłĶ éĻ¢",
+      "ç§ijçłĶéĻ¢ æīĢ",
+      "ç² Ł",
+      "é¢Ī éĥ¨",
+      "é»ĺé»ĺ åľ°",
+      "é«ĺä¸Ń çĶŁ",
+      "æĹıèĩªæ²» åİ¿",
+      "æķĻåѦ è´¨éĩı",
+      "æĪĺ çģ«",
+      "åĿİ åĿ·",
+      "æIJŃ ä¹ĺ",
+      "è¯Ĺ æĦı",
+      "åĪij èѦ",
+      "åĩº æ±Ĺ",
+      "åįģåħŃ æĿ¡",
+      "请 åıĬæŶ",
+      "åĨľä¸ļ 大åѦ",
+      "èIJ½ åı¶",
+      "æĢ» èĢĮè¨Ģ",
+      "æĢ»èĢĮè¨Ģ ä¹ĭ",
+      "æĿľ åħ°",
+      "æĿľåħ° çī¹",
+      "éĻª ä½ł",
+      "åħ¬ æĬ¥",
+      "çķĻè¨Ģ æĿ¿",
+      "éĺħ åİĨ",
+      "競 çĪŃ",
+      "ç»Ļ åĪ«äºº",
+      "æĹ¥æĬ¥ 社",
+      "åĿIJ èIJ½",
+      "åĿIJèIJ½ äºİ",
+      "éĩij åŃĹ",
+      "éĩijåŃĹ å¡Ķ",
+      "åĽ ¤",
+      "è¯Ŀ åī§",
+      "æĮģç»Ń æİ¨è¿Ľ",
+      "æ¼ı æ°´",
+      "詳 細",
+      "æĢĢ æĬ±",
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+      "饥 饿",
+      "éļIJ 身",
+      "个 èµĽåŃ£",
+      "åĵ¡ å·¥",
+      "æģ¢å¤į æŃ£å¸¸",
+      "äºĨ 好å¤ļ",
+      "æĺŁ å·´",
+      "æĺŁå·´ åħĭ",
+      "åħī çݯ",
+      "å¸ħ åĵ¥",
+      "çĻ½ éĽª",
+      "ç¨į ç¨į",
+      "计 æıIJ",
+      "æĦĽ æĥħ",
+      "éİ ĸ",
+      "ä¿¡ éĺ³",
+      "è§Ģ å¯Ł",
+      "å¦Ĥæŀľä½ł æĥ³",
+      "缸æ¯Ķ ä¹ĭä¸ĭ",
+      "解 å¼Ģ",
+      "æīĵåį° æľº",
+      "身 躯",
+      "ç²¾ç¥ŀ æĸĩæĺİ",
+      "èĤ¡ æĮĩ",
+      "å¾® åĪĽ",
+      "红 èĮ¶",
+      "èĩ´ çĻĮ",
+      "æģ© æĸ½",
+      "èħ¿ éĥ¨",
+      "大åŀĭ å¤ļ人",
+      "å®ī åĢį",
+      "è¾ħ导 åijĺ",
+      "èĪª éģĵ",
+      "å¸ĥ å°Ķ",
+      "åįĹå®ģ å¸Ĥ",
+      "ä¸ĬçıŃ æĹı",
+      "侧 ç»ĵæŀĦæĢ§",
+      "追 éļı",
+      "å½ĵåľ° æĶ¿åºľ",
+      "èµ° åĩºæĿ¥",
+      "éĩijèŀį ä¸ļ",
+      "丼 书",
+      "é¡¹çĽ® ç»ıçIJĨ",
+      "è¿ĩ æĪ·",
+      "骨 æŀ¶",
+      "è¡ Ļ",
+      "ä»Ģ 麽",
+      "èħ ĭ",
+      "è¦ģ 害",
+      "åľ¨ åºĬä¸Ĭ",
+      "代è¨Ģ 人",
+      "並 å°ĩ",
+      "åIJĦ个 æĸ¹éĿ¢",
+      "è°´ è´£",
+      "åħ± æĮ¯",
+      "åį³å°Ĩ åĪ°æĿ¥",
+      "èĤº çĻĮ",
+      "ä¾Ľ éĶĢ",
+      "丼 æŀĹ",
+      "èµ ĥ",
+      "åįģä½Ļ å¹´",
+      "åĭĺ æİ¢",
+      "飵 åij³",
+      "èĭ¦ ç¬ij",
+      "æľĢ大 ç¨ĭ度",
+      "éĩįçĤ¹ åħ³æ³¨",
+      "ä¹ĭ 举",
+      "满 æĢĢ",
+      "åıĹåĪ° å½±åĵį",
+      "æĭĽ æĬķæłĩ",
+      "è¡¥ é½IJ",
+      "西 红",
+      "西红 æŁ¿",
+      "é¬ §",
+      "è£ħ åį¸",
+      "éĤ» éĩĮ",
+      "èĤĩ äºĭ",
+      "æİĴ æ¯Ĵ",
+      "åѤ åĦ¿",
+      "鼶 è·Ŀ离",
+      "å®ŀ å¹²",
+      "çľĭ æŁ¥çľĭ",
+      "æĶ¶è´¹ ç«Ļ",
+      "ç» ·",
+      "åħ¬çĽĬ æĢ§",
+      "éĢĴ ç»Ļ",
+      "æĶ» æīĵ",
+      "æĺŁçº§ éħĴåºĹ",
+      "æĺİ åªļ",
+      "çį¨ ç«ĭ",
+      "è¯Ŀè¯Ń æĿĥ",
+      "ä¸ĢæŃ¥ ä¸ĢæŃ¥",
+      "书æ³ķ 家",
+      "æľªç»ı æİĪæĿĥ",
+      "çŁ³ èĨı",
+      "åĩŃ ä»Ģä¹Ī",
+      "çļĦ æĹ¥",
+      "çļĦæĹ¥ åŃIJéĩĮ",
+      "诱 人",
+      "çĻ¾åĪĨ çĻ¾",
+      "èĪĪ 趣",
+      "å¼ł åħĪçĶŁ",
+      "èĢģçĪ· åŃIJ",
+      "æ³¢ çī¹",
+      "åŁºéĩij 份é¢Ŀ",
+      "æ²Ļåıij ä¸Ĭ",
+      "å¥ĭæĸŠ缮æłĩ",
+      "æ°¢ èĥ½",
+      "æ²ĥå°Ķ çİĽ",
+      "義 åĭĻ",
+      "éŁ³ ç®±",
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+      "å¤į æŁ¥",
+      "åĭĥ åĭĥ",
+      "åij¼ 声",
+      "給 äºĪ",
+      "åIJĮäºĭ 们",
+      "ç½ °",
+      "è¯ķ æİ¢",
+      "åħ³éĶ® åŃĹ",
+      "æįIJ çĮ®",
+      "ç»Łè®¡ æķ°æį®",
+      "åĪĽ ä½ľèĢħ",
+      "ä¸ĭ åįĬ",
+      "ä¸ĭåįĬ åľº",
+      "æī¿æĭħ 责任",
+      "端 æŃ£",
+      "ç©¿ è¡£",
+      "ä¼ł çIJĥ",
+      "åĬ© éķ¿",
+      "åĩ ±",
+      "éķ¶ åµĮ",
+      "é£ŀ ç¿Ķ",
+      "è¾ĵ åįµ",
+      "è¾ĵåįµ 管",
+      "ä¸ĩ åħ¬éĩĮ",
+      "æݨ广 åºĶçĶ¨",
+      "å¿« æ¨Ĥ",
+      "ç§ ½",
+      "èī° å·¨",
+      "åIJ¬ å®Į",
+      "åĿļ 硬",
+      "奥 åľ°",
+      "å¥¥åľ° åĪ©",
+      "é¢ ĵ",
+      "èĻIJ å¾ħ",
+      "ä¾Ľ æ±Ĥ",
+      "éľī ç´ł",
+      "伪 è£ħ",
+      "乡 åľŁ",
+      "åĩ¡ æľ¬ç½ij",
+      "åĩ¡æľ¬ç½ij 注",
+      "ä¼Ĭ åĪ©",
+      "è¡¡ æ°´",
+      "æĽ´ åĥıæĺ¯",
+      "åĪĨéĴŁ å·¦åı³",
+      "è¦ı 模",
+      "äºĶ åĪĨéĴŁ",
+      "åºĹ åĬłçĽŁ",
+      "åĽ° éĽ£",
+      "åħ³ åģľ",
+      "æĢĿ 绪",
+      "åĴ½ åĸī",
+      "缸 符",
+      "çĥ¦ èºģ",
+      "æĻĤ æľŁ",
+      "åijĪ çı¾",
+      "解 æķ£",
+      "诱 导",
+      "éļĶ çĥŃ",
+      "çĮ ¶",
+      "åįĹ å®ĭ",
+      "æ·±åħ¥ äºĨ解",
+      "çŃĶ çĸij",
+      "æĺ¼ å¤ľ",
+      "åįĥ ä¼ı",
+      "åĬ³åĬ¡ æ´¾éģ£",
+      "红 è±Ĩ",
+      "åĿı äºĭ",
+      "çĤ¹ æ»´",
+      "å°±ä¸ļ å²Ĺä½į",
+      "约 åIJĪ",
+      "åħį éĻ¤",
+      "éĢĨ åĬ¿",
+      "éĩį éĩijå±ŀ",
+      "å®ĺ 宣",
+      "ä½İ å»ī",
+      "æģ¨ ä¸įå¾Ĺ",
+      "å¾Ĺ 天",
+      "å¾Ĺ天 çĭ¬",
+      "å¾Ĺ天çĭ¬ åİļ",
+      "ä¸Ģå°ģ ä¿¡",
+      "æĬ½ å¥ĸ",
+      "è¾Ĺ 转",
+      "çķĻ å®Ī",
+      "çķĻå®Ī åĦ¿ç«¥",
+      "çŃĶ åį·",
+      "å·¨ åŀĭ",
+      "æľĢ好 ä¸įè¦ģ",
+      "æµĻæ±Ł 大åѦ",
+      "æĨ ¨",
+      "æı¡ æīĭ",
+      "éĴĪ ç»ĩ",
+      "æİĴ 骨",
+      "çĤ ½",
+      "å°ģ è£ħ",
+      "åįĢ åŁŁ",
+      "空æ°Ķ åĩĢåĮĸ",
+      "åħī å½±",
+      "åĢĴ å¡Į",
+      "å§ļ æĺİ",
+      "æ¤į 被",
+      "åѦ åīį",
+      "åѦåīį æķĻèĤ²",
+      "èĬĿ åĬł",
+      "èĬĿåĬł åĵ¥",
+      "缩 水",
+      "ä½ Ł",
+      "åľ¨çº¿ åĴ¨è¯¢",
+      "èµı æŀIJ",
+      "éĿĴ èĽĻ",
+      "æĬ± ä½ı",
+      "èĮĤ åIJį",
+      "åħ¨åĬĽ æīĵéĢł",
+      "åįļ士 åѦä½į",
+      "沧 å·ŀ",
+      "åĻ ¢",
+      "æĿĤ çī©",
+      "åĪ» çĶ»",
+      "æį ħ",
+      "å¾® éĩı",
+      "å¾®éĩı åħĥç´ł",
+      "ä¸Ģ åĽŀäºĭ",
+      "鸡 èĤī",
+      "åĪ©æ¶¦ çİĩ",
+      "æīį ç®Ĺ",
+      "å¾® å¦Ļ",
+      "棵 æłij",
+      "贪 婪",
+      "åĩı åĢ¼",
+      "梦 å¢ĥ",
+      "åı¯ è§Ĩ",
+      "åı¯è§Ĩ åĮĸ",
+      "广大 å¸Ĥæ°ij",
+      "ä¸ĵä¸ļ ä»İäºĭ",
+      "ç»ı 纬",
+      "ç´§ çĽ¯",
+      "çŁ¥ å·±",
+      "è¤ ļ",
+      "æĸĩåĮĸ åºķèķ´",
+      "åݦéŨ å¸Ĥ",
+      "临 港",
+      "对åħ¶ 羣å®ŀ",
+      "岸 边",
+      "è¦ĸ çĤº",
+      "æĬĹ çĻĮ",
+      "åĶIJ å®ĩ",
+      "ä¸įå¾Ĺ è¶ħè¿ĩ",
+      "å¨ģ æħij",
+      "æ¡Ĩæŀ¶ åįıè®®",
+      "èµ° ç§ģ",
+      "åĽ¢ å§Ķ",
+      "夸 大",
+      "æ¬ Ħ",
+      "ç¥ŀç»ı ç³»ç»Ł",
+      "æijĦå½± ä½ľåĵģ",
+      "èĬ ¥",
+      "å®ī åºĨ",
+      "海 滨",
+      "æŀĦ æĢĿ",
+      "çīµ æĮĤ",
+      "åı ©",
+      "éĺIJ æĺİ",
+      "éģ ģ",
+      "ç²¾ æ²¹",
+      "ç©´ ä½į",
+      "æĬ¤ 身",
+      "æĬ¤èº« 符",
+      "æĮĩ å°İ",
+      "åŃĺåľ¨ ä¸Ģå®ļ",
+      "å¯Ĥ éĿĻ",
+      "æµ·å¤ĸ å¸Ĥåľº",
+      "éĿ ¡",
+      "综åIJĪ å¾ģ",
+      "ä¿ IJ",
+      "è¨Ī ç®Ĺ",
+      "æĺİ æľĹ",
+      "äºļ è¿IJ",
+      "äºļè¿IJ ä¼ļ",
+      "åīįçŀ» æĢ§",
+      "åĮ® ä¹ı",
+      "产ä¸ļ æī¶è´«",
+      "èĦij æµ·",
+      "èĦijæµ· ä¸Ń",
+      "åħļçļĦ é¢Ĩ导",
+      "åĪĺ éĤ¦",
+      "æµģ æĺŁ",
+      "æĵ Ĥ",
+      "æĶĢ çĻ»",
+      "åĴ Ķ",
+      "ä¸Ģä¸ĭåŃIJ å°±",
+      "è¯Ĭ æ²»",
+      "使 åĬ²",
+      "åīµ ä½ľ",
+      "éĵŃ è®°",
+      "éĴ± è´¢",
+      "æĹ¥æĬ¥ è®°èĢħ",
+      "çĥŁ çģ«",
+      "èĥľ è´Ł",
+      "åįļ 主",
+      "ä¸ŃåĽ½ èģĶéĢļ",
+      "ç½ijç«Ļ é¦ĸ页",
+      "å°± å¤Ł",
+      "å°±å¤Ł äºĨ",
+      "æīij åħĭ",
+      "å±ħ å§Ķä¼ļ",
+      "è° ¬",
+      "å®īåħ¨ äºĭæķħ",
+      "åķĨ çĶ¨è½¦",
+      "循çݯ ç»ıæµİ",
+      "æ· ¤",
+      "èĢĥ è¯ģ",
+      "å®Ŀ èĹı",
+      "å®Į ç»ĵ",
+      "çłĶåıij æĬķåħ¥",
+      "å² ij",
+      "æģŃ æķ¬",
+      "离 éĢĢä¼ij",
+      "水 墨",
+      "å© ¶",
+      "è¯Ĺ åı¥",
+      "å®ģæ³¢ å¸Ĥ",
+      "å¼± çĤ¹",
+      "åģľ çīĮ",
+      "奶 油",
+      "å¥ĩ纳 æ²³",
+      "æĨ Ĥ",
+      "社ä¼ļ å®ŀè·µ",
+      "è´Ŀ 壳",
+      "çłĤ æµĨ",
+      "èĪ¹ åıª",
+      "宣 æī¬",
+      "综åIJĪ æķ´æ²»",
+      "åĤ ij",
+      "æ°ijæĹı æĸĩåĮĸ",
+      "éĩį çİ°",
+      "积 æ·Ģ",
+      "åħ¬ çĦ¶",
+      "çħ ī",
+      "缸 èģļ",
+      "æ± ¾",
+      "纹 çIJĨ",
+      "çĩĥ çħ¤",
+      "æѤ ç§į",
+      "ç¾İ å¦Ĩ",
+      "åįĥ çĵ¦",
+      "çIJ Ľ",
+      "驾驶 è¯ģ",
+      "éĺ¶ æ¢¯",
+      "ä¸Ŀ ä¸Ŀ",
+      "å¾Īå¤ļ äºĭæĥħ",
+      "åħī éĺ´",
+      "èijĹä½ľ æ¬Ĭ",
+      "åħ§ éĥ¨",
+      "çĽ¸å¯¹ æĿ¥è¯´",
+      "éĸ Ĵ",
+      "éľĩ æħij",
+      "說 話",
+      "æĨ ij",
+      "ç«¥ è£ħ",
+      "ä½ıæĪ¿ åĴĮ",
+      "ä½ıæĪ¿åĴĮ åŁİ",
+      "å·²ç»ı è¶ħè¿ĩ",
+      "侦 å¯Ł",
+      "çŁ¿ çī©",
+      "ä¾Ľ 大家",
+      "çī¹ éĤĢ",
+      "ç¨ĭåºı åijĺ",
+      "çķľçī§ ä¸ļ",
+      "æ° ª",
+      "çij ª",
+      "åĢĴ åľ¨",
+      "åĢĴåľ¨ åľ°",
+      "æ¯ Ģ",
+      "梯 éĺŁ",
+      "æİ¥ èijĹ",
+      "æĬĹ èıĮ",
+      "è¤ ĩ",
+      "ç¬ Ļ",
+      "æ¯Ķ ä¸Ĭå¹´",
+      "鸡 汤",
+      "åŃ¦ä¹ł æĪIJ绩",
+      "æĸij æĸĵ",
+      "åħĪ 导",
+      "åĪĹ ä¸¾",
+      "è°ĥæŁ¥ æĺ¾ç¤º",
+      "æ© «",
+      "ä¹Ŀ åįģ",
+      "è°¢ 飵",
+      "è·¨è¶Ĭ å¼ı",
+      "女æĢ§ æľĭåıĭ",
+      "èIJ¥åħ» ä»·åĢ¼",
+      "å®ŀè·µ ç»ıéªĮ",
+      "èĭı å·ŀå¸Ĥ",
+      "çĵ¶ åŃIJ",
+      "æĸ° çļĦä¸Ģ",
+      "æĸ°çļĦä¸Ģ å¹´",
+      "æĺİ æĻ°",
+      "å®ł çĪ±",
+      "åŃŠ第",
+      "æľĹ 诵",
+      "纳 æĸ¯",
+      "éĢĨ è¡Į",
+      "è«ĭ æĤ¨",
+      "è«ĭæĤ¨ æıIJä¾Ľ",
+      "èĥ¸ æĢĢ",
+      "第ä¸ĥ å±Ĭ",
+      "强 壮",
+      "代 åŃķ",
+      "汶 å·Ŀ",
+      "家 åĸ»",
+      "家åĸ» æĪ·",
+      "家åĸ»æĪ· æĻĵ",
+      "èħ ®",
+      "åIJ¯ 迪",
+      "æĹł éļľç¢į",
+      "èĻķçIJĨ åıĬ",
+      "æĿ¥ åİĨ",
+      "å®ŀ åĬ¡",
+      "ä¹Ł éļıä¹ĭ",
+      "æĬĢèĥ½ åŁ¹è®Ń",
+      "åѤ ç«ĭ",
+      "åī ģ",
+      "éĥ´ å·ŀ",
+      "æĶ¶ æķĽ",
+      "éł» éģĵ",
+      "èį£ 幸",
+      "èİ« è¿ĩäºİ",
+      "æѤ æĻĤ",
+      "纪å§Ķ çĽij",
+      "纪å§ĶçĽij å§Ķ",
+      "缸 éĤ»",
+      "åı¦ä¸Ģ è¾¹",
+      "çªĴ æģ¯",
+      "æľīå¾Īå¤ļ ç§į",
+      "æ¯ı éĢ¢",
+      "éĹ® ä¸ĸ",
+      "ç´¯ ç´¯",
+      "éĿĴæĺ¥ æľŁ",
+      "è·¯ åĨµ",
+      "åħĭ èݱ",
+      "è¿Ħä»Ĭ 为æŃ¢",
+      "æĥĬ å¥ĩ",
+      "跨 度",
+      "éħ¿ éĢł",
+      "åĩ ĭ",
+      "è¿ij ä¸īå¹´",
+      "åĨħ 马",
+      "åĨħ马 å°Ķ",
+      "æı į",
+      "è¿Ľå±ķ æĥħåĨµ",
+      "èĮ §",
+      "æľīåºı æİ¨è¿Ľ",
+      "æĢ» åĨłåĨĽ",
+      "æĪIJ绩 åįķ",
+      "éĽ»è©± åıĬ",
+      "ç´§å¯Ĩ ç»ĵåIJĪ",
+      "åºĬ ä½į",
+      "é¹ Ĭ",
+      "æķ£åıij çĿĢ",
+      "åĭŁ èµĦ",
+      "æ°¨ éħ¸",
+      "彩 ç¥ŀ",
+      "è®Ģ åıĸ",
+      "éĩį 温",
+      "ä¸Ń åŃĺåľ¨çļĦ",
+      "ç¾İ éºĹ",
+      "ä¸įæĸŃ å¢ŀåĬł",
+      "è½® æµģ",
+      "æİ¥ åIJ¬",
+      "å¹´ 产åĢ¼",
+      "åįĥ åħĭ",
+      "æĪĺåľº ä¸Ĭ",
+      "çħ§ 顧",
+      "å¹²éĥ¨ éĺŁä¼į",
+      "åį° ç«ł",
+      "ä¸Ģèĩ´ æĢ§",
+      "è¿ŀ å¤ľ",
+      "åħħ è£ķ",
+      "é»ij åIJįåįķ",
+      "åĩĢ æ°´",
+      "ä¸Ģ大 æĹ©",
+      "åĮħ 袱",
+      "çĬ¯ è§Ħ",
+      "çIJĨ è«ĸ",
+      "æŀģ æĺĵ",
+      "éª ¸",
+      "å¨ĺ å¨ĺ",
+      "åĽ¢ åľĨ",
+      "亿åħĥ 以ä¸Ĭ",
+      "åĪ©çĶ¨ æĤ¨çļĦ",
+      "带æĿ¥ æĽ´å¤ļ",
+      "ä¸Ń央 空è°ĥ",
+      "æľĪ èĸª",
+      "çĮľ æĥ³",
+      "åĪº 客",
+      "ä½ľ æģ¯",
+      "åįķ è°ĥ",
+      "äºĴ åĪ©",
+      "å¦Ĥæľī ä¾µæĿĥ",
+      "å°ı å·§",
+      "åįģ åł°",
+      "åĵĪåĵĪ åĵĪåĵĪ",
+      "è¾¹ éĻħ",
+      "æłĩ è¯Ń",
+      "åĪĩåħ¥ çĤ¹",
+      "éĢĨ è¢Ń",
+      "è¯ķ åīĤ",
+      "绿 è±Ĩ",
+      "è® ļ",
+      "åŁºçĿ£ å¾Ĵ",
+      "å£ ¬",
+      "åħ¨ æĺİæĺŁ",
+      "éĢī ç§Ģ",
+      "èĪĮ å°ĸ",
+      "ä¸įåIJĮ ç±»åŀĭ",
+      "çĥŁ åĽ±",
+      "çģµ æ°Ķ",
+      "åĮº 管å§Ķä¼ļ",
+      "åĨľ åī¯",
+      "åĨľåī¯ 产åĵģ",
+      "èĶļ æĿ¥",
+      "沪 æĮĩ",
+      "åħ»æ®ĸ æĪ·",
+      "æĸĹ å¿Ĺ",
+      "é¦ĸ é¢Ĩ",
+      "è¡Ģ èħ¥",
+      "åĬł ç´§",
+      "ä¸Ģèĩ´ 好è¯Ħ",
+      "第ä¸ī èĬĤ",
+      "æī¬ å°ĺ",
+      "交éĢļ æŀ¢çº½",
+      "鼶 ç¢İ",
+      "é»ij æ´ŀ",
+      "çľĭ ä¸įæĩĤ",
+      "å±ŀ å®ŀ",
+      "主 åŁİåĮº",
+      "å¨ Ľ",
+      "å¨Ľ æ¨Ĥ",
+      "ç¬ij æĦı",
+      "èĻ¹ æ¡¥",
+      "åIJĦ个 çݯèĬĤ",
+      "çķ¥ å¾®",
+      "èĢķ èĢĺ",
+      "æľ¬ åľºæ¯ĶèµĽ",
+      "æĪIJ è´¥",
+      "éĢī èĤ¡",
+      "èªŀ è¨Ģ",
+      "çŃĶ 辩",
+      "èĩª ä¹ł",
+      "æ£ º",
+      "ä¸ĩ 欧åħĥ",
+      "åģľ å·¥",
+      "对åħ¶ è¿Ľè¡Į",
+      "积æŀģ éħįåIJĪ",
+      "ä¹¾ åĿ¤",
+      "å¦ĸ æĢª",
+      "èļĮ åŁł",
+      "èµĦ产 è¯Ħä¼°",
+      "è°ĥ çļ®",
+      "éĻ¤ å¤ķ",
+      "åĽ´ å¢Ļ",
+      "æľį å½¹",
+      "æ·± æ¸Ĭ",
+      "é¢Ħ åĪ¶",
+      "ç ĥ½",
+      "å®ī 稳",
+      "建 æŀĦ",
+      "çĭĻ åĩ»",
+      "主åĭķ 註åĨĬ",
+      "éĥ½æľī èĩªå·±",
+      "æİĴåIJį 第ä¸Ģ",
+      "麻 辣",
+      "çĢ ļ",
+      "çĥŁèĬ± çĪĨ",
+      "çĥŁèĬ±çĪĨ 竹",
+      "èĩªçĦ¶ ä¿ĿæĬ¤",
+      "ä»Ļ å¢ĥ",
+      "为äºĨ éģ¿åħį",
+      "åĨ· åºĵ",
+      "解æĶ¾ æĢĿæĥ³",
+      "åĪĿ äºĮ",
+      "ä½ĵ è´´",
+      "é¦ĸ å¯Į",
+      "迪 æĭľ",
+      "æļĤ ç¼ĵ",
+      "æĶ¯æĮģ åĬĽåº¦",
+      "侦 æİ¢",
+      "马 åĪº",
+      "åĮĹ æ±½",
+      "ç¹ ŀ",
+      "è°İ è¨Ģ",
+      "éĢ£ çºĮ",
+      "å· ³",
+      "ä»»ä½ķ æŶåĢĻ",
+      "车 èģĶç½ij",
+      "åįķ 项",
+      "å¸Ń åį·",
+      "建çŃij æĿIJæĸĻ",
+      "ä¸Ńç§ĭ èĬĤ",
+      "ç¡ķ士 çłĶ究",
+      "ç§ģ ç«ĭ",
+      "åħļåĴĮ æĶ¿åºľ",
+      "æľ¬æ¬¡ 交æĺĵ",
+      "èººåľ¨ åºĬä¸Ĭ",
+      "ç½ijåıĭ è¯Ħ论",
+      "å¦ Ŀ",
+      "害 ç¾ŀ",
+      "åħ¬ç«ĭ åĮ»éĻ¢",
+      "ä¸ ŀ",
+      "çĶŁçī© è´¨",
+      "åºĶ éĤĢ",
+      "æĬ½ åıĸ",
+      "åĩł å¼ł",
+      "æijĺ ç¼ĸ",
+      "ç»ĺ æľ¬",
+      "详 解",
+      "强 硬",
+      "æľĢ åħĪè¿ĽçļĦ",
+      "æĭĽ èĤ¡",
+      "æĭĽèĤ¡ 书",
+      "åįĥ æĸ¹",
+      "åįĥæĸ¹ çĻ¾",
+      "åįĥæĸ¹çĻ¾ 计",
+      "éħį éŁ³",
+      "驾 çħ§",
+      "å¾ģ æĪĺ",
+      "èªĵ è¨Ģ",
+      "æĭľ å¸Ī",
+      "æĭľå¸Ī åѦ",
+      "æĭľå¸ĪåѦ èīº",
+      "æĬ± åĽ¢",
+      "ç±³ ç²ī",
+      "éĿŀ常 éĢĤåIJĪ",
+      "èĪª æµ·",
+      "履 约",
+      "åįģåħ« æĿ¡",
+      "éĶ» éĢł",
+      "éĩįè¦ģ 举æݪ",
+      "åıijæĮ¥ ä½ľçĶ¨",
+      "æ· ļ",
+      "人 社",
+      "人社 å±Ģ",
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+      "èĸ ¢",
+      "èķ ¹",
+      "æ© ŀ",
+      "æ© ij",
+      "æ© ¦",
+      "éĨ ij",
+      "è§ ±",
+      "ç£ ¡",
+      "ð¥ ķ",
+      "ð¥ķ ¢",
+      "ç£ ľ",
+      "è± ®",
+      "ð«Ł ¦",
+      "𬺠Ī",
+      "ð«ł ľ",
+      "é¹ ¾",
+      "èĻ ¤",
+      "æļ ¿",
+      "æĽ Į",
+      "æĽ Ī",
+      "㬠ļ",
+      "è¹ ħ",
+      "è¸ ¶",
+      "äĹ Ľ",
+      "èŀ Ĺ",
+      "çĸ ģ",
+      "ãł ĵ",
+      "å¹ ª",
+      "𪠩",
+      "𪩠ĺ",
+      "å¶ ¦",
+      "ð¬Ń ¬",
+      "𨱠ij",
+      "ð¬Ń ¯",
+      "é¦ ŀ",
+      "ç© Ħ",
+      "ç¯ ļ",
+      "ç¯ ¯",
+      "ç° ī",
+      "é¼ ½",
+      "è¡ ł",
+      "çĽ ¦",
+      "èŀ £",
+      "ç¸ ¢",
+      "é² Ń",
+      "é² ¯",
+      "é² °",
+      "é² º",
+      "é² ¹",
+      "ð«Ĺ ´",
+      "äº ¸",
+      "çĻ Ģ",
+      "çĺ Ń",
+      "𬸠¦",
+      "ç¾ ±",
+      "ç³ Ĵ",
+      "çĩ ĭ",
+      "çĨ »",
+      "çĩ Ĭ",
+      "çĩ ļ",
+      "çĩ ı",
+      "æ¿ ©",
+      "æ¿ ĭ",
+      "æ¾ ª",
+      "æ¾ ½",
+      "æ¾ ´",
+      "æ¾ Ń",
+      "æ¾ ¼",
+      "æĨ ·",
+      "æĨ º",
+      "æĩ Ķ",
+      "é» ī",
+      "å¬ Ľ",
+      "é¹ ¨",
+      "ç¿ ¯",
+      "ð«Ħ ·",
+      "çĴ ±",
+      "𤠩½",
+      "çĴ ¬",
+      "çĴ ®",
+      "é« ½",
+      "æĵ ¿",
+      "èĸ ¿",
+      "èĸ ¸",
+      "æª ij",
+      "æ« Ĩ",
+      "æª ŀ",
+      "éĨ ¨",
+      "ç ¹Ħ",
+      "ç£ ¹",
+      "ç£ »",
+      "çŀ «",
+      "çŀ µ",
+      "è¹ IJ",
+      "èŁ ı",
+      "ã ĺ",
+      "ãĺ İ",
+      "ð¬Ń ³",
+      "éķ ¤",
+      "ð¬Ń ¶",
+      "ð«Ķ į",
+      "éķ ¥",
+      "éķ ¨",
+      "ð¬Ń ¸",
+      "𨱠Ķ",
+      "ð¬Ń ¼",
+      "ð«Ķ İ",
+      "çŁ °",
+      "ç© Ļ",
+      "ç© ľ",
+      "ç© Ł",
+      "ç° ķ",
+      "ç° ĥ",
+      "ç° ı",
+      "åĦ ¦",
+      "éŃ ĭ",
+      "æĸ ¶",
+      "èī ļ",
+      "𬸠ª",
+      "è° ¿",
+      "ä² ł",
+      "𬶠Ł",
+      "é² ¾",
+      "𬶠ł",
+      "é² ¿",
+      "é³ ģ",
+      "é³ Ĥ",
+      "é³ Ī",
+      "é³ ī",
+      "çį ¯",
+      "äĹ ª",
+      "é¦ ĺ",
+      "è¥ ķ",
+      "è¥ ļ",
+      "𬶠¨",
+      "èŀ ±",
+      "çĶ ĵ",
+      "å¬ ¬",
+      "å¬ ¥",
+      "ð¦ Ī",
+      "ð¦Ī ¡",
+      "ð«Ħ ¸",
+      "çĵ Ģ",
+      "éĩ IJ",
+      "é¬ ¶",
+      "çĪ ĩ",
+      "éŀ ³",
+      "éŀ ®",
+      "ð¬Ł ģ",
+      "èĹ Ł",
+      "èĹ ¦",
+      "èĹ ¨",
+      "é¹ ²",
+      "æª «",
+      "é» ¡",
+      "ç¤ ŀ",
+      "ç¤ Į",
+      "ð¥ ĸ",
+      "ð¥ĸ ¨",
+      "è¹ ¢",
+      "è¹ ľ",
+      "èŁ «",
+      "äĹ ´",
+      "åļ ļ",
+      "é« ĥ",
+      "éķ ®",
+      "éķ ±",
+      "éħ Ĥ",
+      "é¦ §",
+      "ç° ł",
+      "ç° Ŀ",
+      "ç° °",
+      "é¼ «",
+      "é¼ ©",
+      "çļ ¦",
+      "èĩ ij",
+      "ä² ¢",
+      "é³ ij",
+      "é³ Ĵ",
+      "é¹ ±",
+      "é¹ ¯",
+      "çĻ Ĺ",
+      "ð¦ Ĵ",
+      "ð¦Ĵ į",
+      "æĹ ŀ",
+      "ç¿ ·",
+      "åĨ ģ",
+      "äİ ĸ",
+      "çĢ Ķ",
+      "çĢ į",
+      "çĢ Į",
+      "è¥ ľ",
+      "ä´ Ļ",
+      "ð¬Ļ Ĭ",
+      "åļ Ń",
+      "ã °",
+      "ã° Ģ",
+      "é¬ ·",
+      "éĨ Ń",
+      "è¹ ¯",
+      "èł ĭ",
+      "ç¿ ¾",
+      "é³ ĺ",
+      "åĦ ³",
+      "åĦ ´",
+      "é¼ Ĺ",
+      "𬶠Ń",
+      "𩾠Į",
+      "é³ ļ",
+      "é³ Ľ",
+      "éº ij",
+      "éº ĸ",
+      "èł ĥ",
+      "å½ Ł",
+      "å¬ ¿",
+      "é¬ Ĵ",
+      "èĺ ĺ",
+      "æ¬ Ĥ",
+      "é Ĩµ",
+      "é¢ ¥",
+      "çĶ Ĺ",
+      "ð¨ Ł",
+      "ð¨Ł ł",
+      "å· ĩ",
+      "éħ ħ",
+      "é« İ",
+      "çĬ ¨",
+      "𬶠®",
+      "ð¨ Ń",
+      "ð¨Ń ī",
+      "㸠Į",
+      "çĪ Ķ",
+      "çĢ ±",
+      "çĢ ¹",
+      "çĢ ¼",
+      "çĢ µ",
+      "è¥ «",
+      "åŃ ħ",
+      "éª ¦",
+      "ð¬Ļ ĭ",
+      "èĢ °",
+      "𤠫",
+      "𤫠ī",
+      "çĵ ĸ",
+      "é¬ ĺ",
+      "è¶ ¯",
+      "𬺠ĵ",
+      "ç½ į",
+      "é¼ ±",
+      "é³ ł",
+      "é³ ¡",
+      "é³ £",
+      "çĪ Ł",
+      "çĪ ļ",
+      "çģ Ī",
+      "éŁ Ĥ",
+      "ç³ µ",
+      "èĺ ¼",
+      "ç¤ µ",
+      "é¹ ´",
+      "èº Ķ",
+      "çļ Ń",
+      "é¾ ¢",
+      "é³ ¤",
+      "äº ¹",
+      "ç± ¥",
+      "é¼ ·",
+      "ð«ļ Ń",
+      "çİ ĥ",
+      "éĨ ¾",
+      "é½ ĩ",
+      "è§ ¿",
+      "èł ¼",
+      "× §",
+      "× ¤",
+      "× Ľ",
+      "×ķ× ª",
+      "× ¡",
+      "×Ļ× Ŀ",
+      "× ¦",
+      "× Ĵ",
+      "× ĺ",
+      "×ķ× ¨",
+      "× Ŀ",
+      "×ķ× ľ",
+      "× ĸ",
+      "๠Ĥ",
+      "ï º",
+      "ðŁ į",
+      "ðŁ IJ",
+      "×Ļ× ¨",
+      "ï »",
+      "ðŁ ij",
+      "ðĿ IJ",
+      "ðŁ ı",
+      "ðŁ Ķ",
+      "ðŁ Į",
+      "ðŁ İ",
+      "ðŁ ĵ",
+      "× Ł",
+      "ðĿ ij",
+      "×ķ× ĵ",
+      "ï ¦",
+      "Ġ× ķ",
+      "×ķ× ij",
+      "à¸Ń à¸ĩ",
+      "ðĿ ĺ",
+      "×Ļ× ª",
+      "ðĿ ķ",
+      "à¸Ĺ ีà¹Ī",
+      "Ø§Ø ¦",
+      "ðŁ ¤",
+      "×ķ× Ł",
+      "ر ÙĬ",
+      "×Ļ× ľ",
+      "ร ะ",
+      "า ย",
+      "ï ¯",
+      "ï ®",
+      "า ม",
+      "â ĩ",
+      "ðŁ ¥",
+      "ï Ń",
+      "ðĿ Ļ",
+      "×ķ× ł",
+      "á ½",
+      "Ġ× Ľ",
+      "ðŁ ļ",
+      "â ļ",
+      "ï §",
+      "×ij ר",
+      "×Ļ× ł",
+      "á ´",
+      "Ġ× Ĺ",
+      "á ¼",
+      "ðĿ Ĺ",
+      "Ġ× ¢",
+      "×Ļ× Ķ",
+      "ãģ£ ãģŁ",
+      "ãģĵ ãģ¨",
+      "á ¸",
+      "ÙĬ ÙĨ",
+      "ãģª ãģĦ",
+      "ا ع",
+      "ภ¨",
+      "à¹Ī à¸ĩ",
+      "×Ļ× ĵ",
+      "×ŀ ש",
+      "á Ī",
+      "׳ ×Ļ",
+      "×Ļ× ij",
+      "ï ¥",
+      "ðĿ ĵ",
+      "Ġ× Ļ",
+      "× ļ",
+      "ั à¸ĩ",
+      "â ĵ",
+      "ï ¤",
+      "ĠاÙĦ Ø£",
+      "า à¸ģ",
+      "à¹ī à¸Ļ",
+      "à¹Ģ ร",
+      "×ķ× Ŀ",
+      "á ¹",
+      "ภ¶",
+      "×Ļ× §",
+      "ภĭ",
+      "à¸Ħ ร",
+      "ภĺ",
+      "ั à¸ģ",
+      "ðŁ ķ",
+      "ÙĪ ÙĨ",
+      "à¸Ń ย",
+      "â Ĭ",
+      "ðĿ Ĵ",
+      "ĠاÙĦ ع",
+      "า à¸Ļ",
+      "×Ļ× Ł",
+      "ÙĦ ÙĬ",
+      "×Ļ× ©",
+      "à¸Ľ ระ",
+      "à¹Ģ à¸Ľ",
+      "Ġ× ł",
+      "×ķ× ¡",
+      "ภł",
+      "Ùħ ÙĨ",
+      "×ķ× ¢",
+      "×ķ× ŀ",
+      "â Į",
+      "ðŁ §",
+      "à¹ĩ à¸Ļ",
+      "ภį",
+      "ã İ",
+      "á µ",
+      "ĠاÙĦ س",
+      "×ķ× §",
+      "ห ล",
+      "ðŁ ĩ",
+      "â ı",
+      "ðŁ ¦",
+      "Ġ×Ķ ×ŀ",
+      "ÙĪ ا",
+      "Ġ× ª",
+      "ר ×IJ",
+      "à¸Ń à¸Ļ",
+      "ภ©",
+      "à¹Ī ว",
+      "×ķ× ¦",
+      "í Ĺ",
+      "ã Ħ",
+      "ï ¨",
+      "ï ¹",
+      "â İ",
+      "ï ²",
+      "ðĿ ļ",
+      "ð IJ",
+      "à¸Ħ ว",
+      "ห à¸Ļ",
+      "Ġ× ¨",
+      "ب ÙĬ",
+      "ร à¹Į",
+      "ر ا",
+      "ش ر",
+      "×ķ× Ĺ",
+      "×ķ× ¤",
+      "×ķ× ©",
+      "×ķ× Ĵ",
+      "í Ŀ",
+      "â Ľ",
+      "à¸ķ ิ",
+      "à¹Ģ à¸ģ",
+      "ï ³",
+      "ï ±",
+      "à¸Ķ à¹ī",
+      "ë ¹",
+      "ï ¬",
+      "á ¿",
+      "ðŁ Ľ",
+      "ðĿ ĸ",
+      "à¹Īา à¸ĩ",
+      "ู à¹ī",
+      "Ġ×Ķ ×IJ",
+      "ĠاÙĦ ØŃ",
+      "פ ר",
+      "ÙĪ Ùħ",
+      "à¹Ģ ล",
+      "í ĸ",
+      "×Ļ× ¢",
+      "ì Ī",
+      "í ĵ",
+      "ðŁ ħ",
+      "á ł",
+      "à¸Ħว าม",
+      "à¸Ī ะ",
+      "׳ ×Ķ",
+      "Ġ× §",
+      "ภŁ",
+      "à¹ī à¸ĩ",
+      "ห ม",
+      "ت Ùħ",
+      "׾ ×Ļ",
+      "ÙĬ د",
+      "à¹Ī à¸Ļ",
+      "׊ר",
+      "ש ר",
+      "à¹Ģ à¸Ĺ",
+      "×ŀ ר",
+      "ë ĸ",
+      "ع ÙĦ",
+      "×ŀ ×¢",
+      "â ²",
+      "׾ ×Ķ",
+      "Ġ× ¤",
+      "à¸Ń à¸ģ",
+      "س ÙĦ",
+      "×Ļ× ŀ",
+      "ÙĤ ÙĬ",
+      "í İ",
+      "ت ØŃ",
+      "×Ļ× ¡",
+      "×Ļ× Ĺ",
+      "í Ľ",
+      "ï °",
+      "â ½",
+      "á ī",
+      "á Ĭ",
+      "á ¨",
+      "Ùĩ ا",
+      "Ġ׾ ×Ķ",
+      "×ķ× IJ",
+      "Ùħ ا",
+      "à¹īà¸Ń à¸ĩ",
+      "ر ب",
+      "ĠاÙĦ ج",
+      "×ŀ ×ĵ",
+      "Ùħ ÙĦ",
+      "ت ر",
+      "à¹Ģ à¸Ķ",
+      "ק ר",
+      "í ħ",
+      "ì ¼",
+      "ê ¿",
+      "ã Ī",
+      "á IJ",
+      "ðŁ Ĺ",
+      "ê ¦",
+      "á ĭ",
+      "ðĿ Ķ",
+      "à¹Ģà¸Ľ à¹ĩà¸Ļ",
+      "à¹ĥ ห",
+      "ม า",
+      "ว à¹Īา",
+      "ม ี",
+      "ี à¹ī",
+      "à¹Ħม à¹Ī",
+      "ÙĨ ÙĬ",
+      "Ø ¤",
+      "ร า",
+      "×ķ ×Ļ",
+      "ãĤĪ ãģĨ",
+      "ิ à¸Ķ",
+      "×Ļ× ¤",
+      "׊׾",
+      "ÙĤ د",
+      "à¹Ģ ส",
+      "×Ļ× ĺ",
+      "à¸ģ ล",
+      "ר ׼",
+      "×ķ× Ľ",
+      "×Ļ× Ľ",
+      "ë Ī",
+      "ë ĥ",
+      "ðŁ ĸ",
+      "á ħ",
+      "â ¼",
+      "ã ī",
+      "à¹Ħ à¸Ķà¹ī",
+      "ת ×Ļ",
+      "×Ļ× IJ",
+      "ĠاÙĦ Ø¥",
+      "à¸ł า",
+      "ร ิ",
+      "ÙĤ Ø©",
+      "ØŃ Ø¯",
+      "ê »",
+      "ì ±",
+      "ת ×Ĺ",
+      "ì º",
+      "â ĭ",
+      "á Ħ",
+      "á ¾",
+      "â µ",
+      "â ¾",
+      "ĠÙĪ اÙĦ",
+      "׳ ×ķ",
+      "Ù Ģ",
+      "ÙĬ ا",
+      "à¸ģ à¹ĩ",
+      "×ŀ ×Ķ",
+      "ãģĦ ãĤĭ",
+      "ع د",
+      "ĠاÙĦ ÙĨ",
+      "Ġ×Ķ ש",
+      "Ø ¦",
+      "ั à¹īà¸ĩ",
+      "ร ัà¸ļ",
+      "ÙĪ ÙĤ",
+      "ãģ§ ãģį",
+      "à¹Ģ à¸ŀ",
+      "׼ ׾",
+      "×ĺ ר",
+      "ั à¸Ķ",
+      "à¸Ń า",
+      "ì ¢",
+      "à¸Ń à¸ļ",
+      "à¸ķ ร",
+      "à¹Ģ à¸Ĭ",
+      "ì Ķ",
+      "ãģĹ ãģ¾",
+      "ë ģ",
+      "ë ķ",
+      "ðŁ Ļ",
+      "â Ĵ",
+      "á ¶",
+      "à¹ģ ล",
+      "ÙĨ ا",
+      "à¹ĥห à¹ī",
+      "à¹Ħ à¸Ľ",
+      "× £",
+      "ั ว",
+      "า à¸ĩ",
+      "×ĵ ר",
+      "×ij ׾",
+      "פ ×Ļ",
+      "Ġ× ĵ",
+      "ĠاÙĦ Ùģ",
+      "à¹Ģ à¸Ĥ",
+      "ש ×Ķ",
+      "×IJ ר",
+      "ë ¬",
+      "ãģ« ãģª",
+      "ÑĢ о",
+      "ว ิ",
+      "Ùħ ر",
+      "×IJ ת",
+      "Ùĥ ر",
+      "س ب",
+      "ÙĨ ت",
+      "ãģĹ ãģĦ",
+      "ا ج",
+      "à¸Ń รà¹Į",
+      "Ùĥ ÙĦ",
+      "س Ùħ",
+      "ส ิ",
+      "×Ļ× ¦",
+      "ë Ŀ",
+      "í ľ",
+      "ì ī",
+      "á Ĩ",
+      "Ùĩ Ùħ",
+      "à¸Ļ ีà¹ī",
+      "ãģĤ ãĤĭ",
+      "ãģĦ ãģ¦",
+      "س ÙĬ",
+      "׾ ×IJ",
+      "د ر",
+      "ãģ ļ",
+      "ÙĪ ج",
+      "ĠاÙĦ Ø®",
+      "ص ر",
+      "í ı",
+      "à¹īา à¸ĩ",
+      "ุ à¸Ķ",
+      "×ķ× ĺ",
+      "×ij ×¢",
+      "í Ĩ",
+      "à¸Ĭ า",
+      "ร ม",
+      "ש ×ŀ",
+      "×ŀ ס",
+      "ê ´",
+      "ì ´",
+      "ë ľ",
+      "ì ¿",
+      "ì ©",
+      "ë »",
+      "â ¤",
+      "ðŁ Ĩ",
+      "á Į",
+      "á ķ",
+      "ذ ا",
+      "à¸Ĺ ำ",
+      "à¸ķ à¹Ī",
+      "ĠاÙĦ ÙĤ",
+      "ÙĦ Ùĥ",
+      "ู à¹Ī",
+      "à¸Ħ ุ",
+      "ÙĬ Ùħ",
+      "׳ ×Ļ×Ŀ",
+      "ืà¹Ī à¸Ń",
+      "ÙĪ ع",
+      "ãĤ ĩ",
+      "ا ÙĤ",
+      "Ġ×ij ×¢",
+      "à¹Ģ ม",
+      "ج Ùħ",
+      "á» «",
+      "ãģĵãģ¨ ãģĮ",
+      "ب د",
+      "×ķ× Ķ",
+      "ש ׾",
+      "Ùĩ ر",
+      "à¹Ģ à¸Ļ",
+      "ãģ ¹",
+      "í ĭ",
+      "ì »",
+      "ì ½",
+      "ë Ń",
+      "ì Į",
+      "í Ģ",
+      "ë Į",
+      "ë º",
+      "ã Ĭ",
+      "à¹ĥ à¸Ļ",
+      "Ġ× Ĵ",
+      "๠Ĩ",
+      "à¸Ī าà¸ģ",
+      "ว ย",
+      "à¹ĥ à¸Ĭ",
+      "à¸ĩ าà¸Ļ",
+      "ĠاÙĦ Ø´",
+      "ا ØŃ",
+      "à¹īา à¸Ļ",
+      "ืà¹Ī à¸Ńà¸ĩ",
+      "×IJ ×Ļ",
+      "ب ÙĦ",
+      "ãģ¨ æĢĿ",
+      "׳ ס",
+      "ãģ¾ ãģĽ",
+      "Ùĥ ÙĨ",
+      "ע ר",
+      "ĠاÙĦ د",
+      "ש ת",
+      "í ŀ",
+      "Ùħ س",
+      "ص ÙĦ",
+      "×ķ׳ ×Ķ",
+      "ار ة",
+      "ÙĦ Ùħ",
+      "ส ม",
+      "Ø£ ÙĨ",
+      "ת ר",
+      "×IJ ×ŀ",
+      "ع ب",
+      "خ ت",
+      "ãĤ ĥ",
+      "ì ¡",
+      "ì £",
+      "ив а",
+      "ส ั",
+      "ึ à¸ģ",
+      "ì ¸",
+      "ë Ĩ",
+      "алÑĮ н",
+      "ì ³",
+      "ì į",
+      "ê ¼",
+      "ê ½",
+      "ì ı",
+      "ã Į",
+      "ã ı",
+      "ï ©",
+      "ê ª",
+      "á İ",
+      "Ġ× ĸ",
+      "à¸ģ ัà¸Ļ",
+      "×Ļ ×ķ",
+      "à¸Ħ à¸Ļ",
+      "׳ ×ķת",
+      "à¸ľ ูà¹ī",
+      "à¹ĥ à¸Ī",
+      "ãģĦ ãģŁ",
+      "Ùģ ر",
+      "×ĺ ×Ļ",
+      "צ ×Ļ",
+      "ãĤĤ ãģ®",
+      "ĠاÙĦ ص",
+      "ãģ¾ãģĽ ãĤĵ",
+      "د ة",
+      "×ij ×Ļ",
+      "ĠاÙĦ ر",
+      "Ġ×ŀ ×IJ",
+      "ส ำ",
+      "à¹Ģ ห",
+      "ع ر",
+      "ãģª ãģı",
+      "à¸ģร ะ",
+      "×ij ×ĵ",
+      "à¹Ģ à¸Ī",
+      "×Ļ× ļ",
+      "×Ĺ ×Ļ",
+      "ÙĬ ع",
+      "ש ×ij",
+      "ÙĨ Ø©",
+      "ÙĪ ض",
+      "ÙĦ Ùģ",
+      "ÙĢ ÙĢ",
+      "פ ע",
+      "í Ī",
+      "×ŀ ק",
+      "ภIJ",
+      "ØŃ Ø©",
+      "ا ص",
+      "Ñĭв а",
+      "à¸Ħ ม",
+      "ว ั",
+      "à¸Ľ ล",
+      "ì Ł",
+      "í ļ",
+      "ë ´",
+      "ë ij",
+      "ë ī",
+      "ë ĩ",
+      "ì ¨",
+      "ë ±",
+      "ë İ",
+      "â ¬",
+      "á ¥",
+      "á Ĺ",
+      "á Ľ",
+      "á į",
+      "Å ©",
+      "à¸Ķ ี",
+      "ô i",
+      "Ġ× ¡",
+      "׾ ×ķ",
+      "á»Ŀ i",
+      "à¸Ħุ à¸ĵ",
+      "â y",
+      "à¸Ļ า",
+      "×Ĺ ×ĵ",
+      "×ĵ ×Ļ",
+      "ห า",
+      "ج ÙĦ",
+      "à¹Ģ ว",
+      "ãĤĩ ãģĨ",
+      "Ùħ Ø©",
+      "ĠاÙĦ Ùĥ",
+      "Ġ×Ķ ×¢",
+      "ج ر",
+      "×ĸ ר",
+      "ا ط",
+      "׼ ת",
+      "×ķ׳ ×Ļ×Ŀ",
+      "ØŃ Ùħ",
+      "ê ¶",
+      "ر Ùĥ",
+      "Ġ׾ ×¢",
+      "×ķ× ĸ",
+      "ส ร",
+      "צ ׾",
+      "Ø ¢",
+      "ا ست",
+      "à¹Ī ม",
+      "خ ر",
+      "צ ע",
+      "×Ļר ×ķת",
+      "اد ة",
+      "ش ار",
+      "×ŀ ×Ĺ",
+      "í Ĵ",
+      "à¹Ģร ีย",
+      "׊ק",
+      "Ø§Ø «",
+      "ร à¸ĩ",
+      "à¹Ģ à¸ķ",
+      "à¸Ī ำ",
+      "ภĿ",
+      "à¹Īา ย",
+      "à¸Ħ ล",
+      "ÙĤ ÙĪ",
+      "иÑĩеÑģ к",
+      "à¸ĵ à¹Į",
+      "ั ย",
+      "Ùħ ع",
+      "ë ¨",
+      "ë ¿",
+      "ë ®",
+      "ï ´",
+      "ì ¥",
+      "ì «",
+      "ë µ",
+      "á ¡",
+      "â į",
+      "ð ĵ",
+      "â °",
+      "à¸Ĥ à¸Ńà¸ĩ",
+      "Ù ĭ",
+      "à¸ģ ัà¸ļ",
+      "ãģ® ãģ§",
+      "à¹ī ว",
+      "à¸Ńย à¹Īาà¸ĩ",
+      "ãģ Ń",
+      "á»ĩ t",
+      "à¸ķ à¹īà¸Ńà¸ĩ",
+      "×ŀ ×Ļ",
+      "à¹ģ à¸ļ",
+      "×Ĵ ר",
+      "ÙĪ Ùģ",
+      "ÙĤ ÙĦ",
+      "à¸łà¸² à¸ŀ",
+      "ר ×Ļ",
+      "ล า",
+      "ÙĬ س",
+      "Ġ× ¦",
+      "ÙĬ Ùģ",
+      "Ġ× ĺ",
+      "à¸ľ ล",
+      "á ng",
+      "ร ว",
+      "Ġ×ŀ ש",
+      "×IJ ×ķת",
+      "×ĸ ×Ķ",
+      "ู à¸ģ",
+      "à¸Ļ ัà¸ģ",
+      "اÙĨ ÙĬ",
+      "د ا",
+      "ãģ ³",
+      "׼ ף",
+      "ãĤī ãĤĮ",
+      "ãĤĮ ãģ°",
+      "ת ק",
+      "ú c",
+      "ÙĪ ز",
+      "×Ļר ×Ķ",
+      "Ġn gh",
+      "án h",
+      "Ġ×ķ ×IJ",
+      "á» ħ",
+      "ส ุà¸Ķ",
+      "ë į°",
+      "ا ض",
+      "اÙĦ ÙĬ",
+      "ب ار",
+      "ع Ùħ",
+      "à¸ļ า",
+      "ت ج",
+      "à¸ŀ ร",
+      "×ķר ×Ķ",
+      "ả ng",
+      "Ø® ÙĦ",
+      "ภī",
+      "ắ c",
+      "ש ×Ļ×Ŀ",
+      "í Ķ",
+      "Ùģ س",
+      "×Ļ× Ĵ",
+      "п ÑĢ",
+      "ĠاÙĦ Ø«",
+      "س ط",
+      "ร ูà¹ī",
+      "ีà¹Ī ย",
+      "à¸Ń à¸Ķ",
+      "ãģª ãĤĬ",
+      "×Ĵ ×ĵ",
+      "ãģĦ ãģ¾ãģĹãģŁ",
+      "ס ק",
+      "خ ص",
+      "la ÅŁ",
+      "ен но",
+      "ب ØŃ",
+      "ส à¸Ļ",
+      "ภ®",
+      "ר×IJ ש",
+      "Ùħ ÙĪ",
+      "دÙĬ د",
+      "ษ า",
+      "×ķ× ļ",
+      "ãĥ§ ãĥ³",
+      "à¸ķ ุ",
+      "Ġê µ",
+      "ĠÑģв о",
+      "צ ×ij",
+      "à¸Ń ม",
+      "à¸Ľ ร",
+      "ت ع",
+      "×Ķ ת",
+      "اÙħ ÙĦ",
+      "×ŀ ׳",
+      "ç ¶ļ",
+      "ภ¤",
+      "í į",
+      "ë ĺ",
+      "ë ¤",
+      "ì ij",
+      "â ´",
+      "ã ĭ",
+      "Ġب اÙĦ",
+      "á»ģ u",
+      "ĠاÙĦ ÙĦ",
+      "à¸ķ ัว",
+      "Ø° Ùĩ",
+      "ึ à¸ĩ",
+      "à¹ĥà¸Ĭ à¹ī",
+      "á»ĵ ng",
+      "à¸Ļ ั",
+      "ม าà¸ģ",
+      "ãĥ Ł",
+      "×ŀ ×ķ",
+      "à¸Ĺ ย",
+      "á»Ļ i",
+      "Ạ±",
+      "ả o",
+      "à¹Ĥ à¸Ķ",
+      "×IJ ׾",
+      "ส าม",
+      "ÙĪ ب",
+      "à¸Ĺ ุ",
+      "ย ัà¸ĩ",
+      "ע ת",
+      "×ķ׳ ×ķת",
+      "à¸Ĥ ึ",
+      "à¸Ĥึ à¹īà¸Ļ",
+      "à¸ģ à¹Ī",
+      "Ạ«",
+      "á»ij c",
+      "ãģĹ ãĤĩãģĨ",
+      "á»ĭ ch",
+      "Ġ×IJ ×ķת",
+      "Ġש ×IJ",
+      "׼ ×ķ׾",
+      "á»Ļ c",
+      "ع ة",
+      "à¸Ĺ ี",
+      "à¹Ģ à¸Ń",
+      "Ùĥ ت",
+      "ãģ »",
+      "Ạ»",
+      "ìĹ ħ",
+      "à¸Ń à¸Ńà¸ģ",
+      "اÙĨ ت",
+      "à¹Ħ ร",
+      "Ġ×IJ ×Ĺר",
+      "ط ر",
+      "ÙĨ د",
+      "ื à¹īà¸Ń",
+      "Ø· ÙĦ",
+      "×IJ ×Ķ",
+      "uy ên",
+      "í ĸī",
+      "×ij ×Ķ",
+      "à¸Ħ à¹Ī",
+      "à¸Ĭ à¹Īว",
+      "ãģĤãĤĬ ãģ¾ãģĻ",
+      "ÙĬ ب",
+      "ק ׾",
+      "ãĥ Ļ",
+      "Ä ©",
+      "س ر",
+      "า ว",
+      "ãĤ ±",
+      "à¸ļ ริ",
+      "ר ×Ĵ",
+      "á»ĥ u",
+      "ØŃ Øª",
+      "×ķ×ŀ ×Ļ",
+      "ب ÙĨ",
+      "êµ IJ",
+      "ÄŁ u",
+      "ãģª ãĤĵ",
+      "×ij ק",
+      "Ġפ ר",
+      "ắ n",
+      "ØŃ ÙĦ",
+      "×ij ×Ĺ",
+      "ấ u",
+      "×ij ×ķ×ĵ",
+      "ãĥ ¯",
+      "Ġ׾ ק",
+      "ั à¸į",
+      "à¸ŀ ิ",
+      "×Ĺ ×Ķ",
+      "×ĸ ׼",
+      "ãĥ¼ãĥ ł",
+      "ÑĤ елÑĮ",
+      "×ŀ ×Ļ×ĵ",
+      "ÙĬ Ø®",
+      "Ạ³",
+      "ت ص",
+      "à¸ĺ ิ",
+      "è¾ ¼",
+      "ì ĵ",
+      "Ùĥ Ø©",
+      "ÙĤ ب",
+      "à¸Ħ à¹Į",
+      "à¹īา ย",
+      "à¸ĵ ะ",
+      "า ะ",
+      "ë Ĵ",
+      "ê ¾",
+      "ë ·",
+      "ì ĩ",
+      "ê º",
+      "ì ģ",
+      "ë Ģ",
+      "ì ¾",
+      "ë ½",
+      "ë ļ",
+      "ì Ń",
+      "ì İ",
+      "á ij",
+      "ë Ĺ",
+      "ê Ĵ",
+      "à ¡",
+      "à ¬",
+      "ðIJ Į",
+      "ã ĩ",
+      "ðĿ Ħ",
+      "Ġ׾ ×IJ",
+      "ãģ¨ ãģĦãģĨ",
+      "Ġn hi",
+      "×Ļ ×ķת",
+      "Ġש ×Ķ",
+      "à¹ģล à¹īว",
+      "Æ°á»Ľ c",
+      "à¸Ķà¹ī วย",
+      "à¸Ĺ าà¸ĩ",
+      "׳ ת",
+      "פ ת",
+      "à¹ģ à¸ķà¹Ī",
+      "Æ° ng",
+      "à¸Ńย ูà¹Ī",
+      "à¹ī ำ",
+      "Ġ×IJ ׾",
+      "Ùĥ Ùħ",
+      "ấ p",
+      "ล à¸ĩ",
+      "ãģŁ ãĤģ",
+      "×Ĵ ׾",
+      "ห ร",
+      "ĠÑĢ е",
+      "à¹Ģà¸Ĥ à¹īา",
+      "ÙĤ ر",
+      "Ġ×Ķ ס",
+      "ÙĪ ÙĬ",
+      "สาม าร",
+      "สามาร à¸ĸ",
+      "Äĥ n",
+      "à¸Ń ี",
+      "פ ×ķ",
+      "×Ļ׳ ×ķ",
+      "ว ัà¸Ļ",
+      "ặ c",
+      "íķ Ļ",
+      "×ŀ ת",
+      "ê u",
+      "Ạ¹",
+      "Ùģ ÙĬ",
+      "×ŀ צ",
+      "à¸Ħ า",
+      "ãģĿ ãģĨ",
+      "ãĢ ħ",
+      "ا ز",
+      "ا Ùĩ",
+      "ר ×Ļ×Ŀ",
+      "ấ n",
+      "ห าร",
+      "ạ t",
+      "ÙĨ Ùĩ",
+      "à¹Ģ à¸Ħร",
+      "ج Ùĩ",
+      "׼ ×Ļ",
+      "ắ t",
+      "à¸Ħ à¹īา",
+      "ر ة",
+      "ãĥ ı",
+      "Ùĥ ÙĪÙĨ",
+      "ứ ng",
+      "Ġìļ °",
+      "ย à¹Į",
+      "à¹Īว à¸Ļ",
+      "à¸ģ ำ",
+      "ث ر",
+      "Ñģ и",
+      "ĠاÙĦ Ø·",
+      "Ġ×Ķ צ",
+      "ĠØ ·",
+      "ĠاÙĦ ÙĪ",
+      "ê¹ Į",
+      "ØŃ ÙĬ",
+      "ار ات",
+      "à¹Ģ à¸ĭ",
+      "ب ا",
+      "г ÑĢ",
+      "ร ี",
+      "ืà¸Ń à¸Ļ",
+      "ع ت",
+      "ÙĤ اÙĦ",
+      "د Ùħ",
+      "Ø ¡",
+      "Ġ×ŀ ק",
+      "×ĵ ×Ļ×Ŀ",
+      "×¢ ׾",
+      "ãģ Ĵ",
+      "ëĭ ĺ",
+      "×¢ ×Ķ",
+      "Ġìĸ ´",
+      "Ñģ ÑĮ",
+      "ÙĤ Ø·",
+      "ãĥ Ľ",
+      "èĢĥ ãģĪ",
+      "à¹ģ à¸Ļ",
+      "ÙĪ ات",
+      "â u",
+      "ĠìĤ¬ ëŀ",
+      "ห ว",
+      "ĠاÙĦØ£ Ùħ",
+      "Ġ×Ķ ×ŀש",
+      "ب ÙĪ",
+      "à¸Ĭ à¸Ļ",
+      "ãĤĵ ãģ§ãģĻ",
+      "ว à¸Ļ",
+      "à¸ģร รม",
+      "×ŀ ×ķ×ĵ",
+      "Ùĥ اÙĨ",
+      "×ķ× £",
+      "ол ог",
+      "ت ÙĨ",
+      "à¸ķ à¹Į",
+      "ê² ĥ",
+      "ר ×ĺ",
+      "ừ ng",
+      "×ķ×ij ×Ķ",
+      "Ùħ ØŃ",
+      "ĠÐ §",
+      "פ ×Ĵ",
+      "ส à¸ĸ",
+      "ãģĭ ãĤĬ",
+      "ını z",
+      "à¹Ģ ย",
+      "ãĥ¼ ãĥ³",
+      "ãģĬ ãĤĬ",
+      "פ ש",
+      "ิ à¸ķ",
+      "Ø· ÙĨ",
+      "×Ļת ×Ļ",
+      "×IJ ׳",
+      "ç ek",
+      "ì ª",
+      "×ŀ ×ij",
+      "ศ า",
+      "ãĤ¹ ãĤ¿",
+      "à¸ļ ุ",
+      "×ĵ ×ijר",
+      "ãģĦ ãģı",
+      "ส ะ",
+      "à¹Ģ หล",
+      "ิ à¸ĩ",
+      "à¸ŀ ัà¸Ļ",
+      "ãģĦ ãģŁãģł",
+      "ãĤĤ ãĤī",
+      "à¹ī ม",
+      "ãģĵãģ¨ãģĮ ãģ§ãģį",
+      "าร à¹Į",
+      "ุ à¸ĩ",
+      "í ij",
+      "ì ¯",
+      "ë ¼",
+      "í Ĥ",
+      "ì ·",
+      "ê ¡",
+      "á ı",
+      "á Ĵ",
+      "ðĿ ľ",
+      "á ©",
+      "ðŁ Ħ",
+      "ðIJ ¤",
+      "Ġש ׾",
+      "Ġ×ŀ ×Ķ",
+      "à¹ģล ะ",
+      "Ġ׼ ׾",
+      "Ạ½",
+      "á»Ļ ng",
+      "Ø° ÙĬ",
+      "л е",
+      "× ¥",
+      "ãģª ãģ©",
+      "ĠÙĪ Ø£",
+      "หà¸Ļ à¹īา",
+      "ãģ¾ ãģ§",
+      "à¸ķà¹Ī à¸Ń",
+      "à¸Ĺ ัà¹īà¸ĩ",
+      "ãģł ãģij",
+      "à¹ģà¸ļ à¸ļ",
+      "à¹Ģร า",
+      "פ ׾",
+      "ãģŁ ãģĦ",
+      "à¹Ģล ย",
+      "ãģ£ãģ¦ ãģĦãĤĭ",
+      "ế p",
+      "ึ à¹Īà¸ĩ",
+      "ê ´Ģ",
+      "ê³ Ħ",
+      "׼ ×ķ",
+      "à¹Ģร ืà¹Īà¸Ńà¸ĩ",
+      "ק ×Ļ",
+      "êµ Ń",
+      "פ ס",
+      "ت ÙĬ",
+      "ãĥ Ħ",
+      "Ġ×Ķ ×Ĺ",
+      "г и",
+      "ר×IJ ׾",
+      "×ŀ ׾",
+      "ĠØ£ ÙĬ",
+      "Ġع ÙĦÙĬ",
+      "ãģĭ ãģ£ãģŁ",
+      "ש ×Ļ",
+      "д Ñĥ",
+      "×ŀ ף",
+      "׳ ×ĺ",
+      "׳ ×Ļת",
+      "mi ÅŁ",
+      "׼ ×Ŀ",
+      "Ġ×ij ר",
+      "Ġ׾ ×ij",
+      "ĠÐ Ľ",
+      "ç e",
+      "×ķ׳ ×Ļ",
+      "ãĤĪãģĨ ãģ«",
+      "פ ×ķר",
+      "ãĥ į",
+      "Ùĥ ÙĬ",
+      "×Ĺ ×ª",
+      "Ùģ ÙĦ",
+      "Ġ×Ķ ק",
+      "Ġ×Ķ ×ij",
+      "Ġ×ŀ ס",
+      "à¹Īา à¸Ļ",
+      "п еÑĢ",
+      "à¹Īา ว",
+      "Ġ×ij ×IJ",
+      "ĠÙĪ Ùĩ",
+      "à¸Ļ ำ",
+      "Ġ×ij ש",
+      "׳ ק",
+      "ãģ© ãģĨ",
+      "ש ×ķת",
+      "×ĵ ×Ķ",
+      "à¹Ģ à¸ļ",
+      "ÙĨ س",
+      "Ġìļ° 리",
+      "ส à¹Īวà¸Ļ",
+      "ล ัà¸ĩ",
+      "ج ز",
+      "Ġ×Ĺ ×Ļ",
+      "Ùĥ ثر",
+      "ล ะ",
+      "Ùĩ د",
+      "ĠÙĪ ب",
+      "اÙĦ Ùħ",
+      "à¹ģ ม",
+      "Æ¡ i",
+      "Ġ×ij ×Ĺ",
+      "ữ a",
+      "à¹Ģà¸Ĺ ศ",
+      "à¸ķ ัà¹īà¸ĩ",
+      "ог да",
+      "׾ ק",
+      "د د",
+      "สร à¹īาà¸ĩ",
+      "à¸Ĭ ี",
+      "Ùģ ض",
+      "à¹ģ ห",
+      "uy á»ĩn",
+      "ร ัà¸ģ",
+      "á»ĩ m",
+      "ส า",
+      "פ ק",
+      "ีย à¸ĩ",
+      "à¸ķ à¹Īาà¸ĩ",
+      "à¸Ħร ัà¹īà¸ĩ",
+      "ØŃ ÙĤ",
+      "à¹Ģ à¸Ńà¸ĩ",
+      "ائ ÙĬ",
+      "×ĺ ×¢",
+      "اÙĦ Ø©",
+      "ิ à¹Īม",
+      "ãĤ ½",
+      "د Ùī",
+      "Ġר ×IJ",
+      "ãģ£ ãģ¨",
+      "ãĥĥ ãĥĹ",
+      "ÙĬر Ø©",
+      "ê± ´",
+      "×ŀ ×IJ",
+      "×ķ ×ķ",
+      "ب ع",
+      "ãģ ²",
+      "ร าย",
+      "×ĵ ×Ŀ",
+      "ت Ùģ",
+      "à¸ķ à¸ģ",
+      "ạ ng",
+      "ãĤĴ è¦ĭ",
+      "à¸Ĭ ั",
+      "Æ°á» Ł",
+      "Æ°á»Ł ng",
+      "ج ب",
+      "×ķ×ŀ ר",
+      "ĠìĤ¬ëŀ Į",
+      "ó ng",
+      "ร ั",
+      "Ġ×Ķ ×ĸ",
+      "ר צ",
+      "Ġ×Ĺ ×ĵ",
+      "Ø° ÙĦÙĥ",
+      "×ķר ×Ļ",
+      "ãģ¡ ãĤĥ",
+      "Ùģ ع",
+      "Ġ׾ צ",
+      "á i",
+      "à¹ĩ à¸ļ",
+      "ãģ İ",
+      "à¸ģ ิ",
+      "ạ c",
+      "ë© °",
+      "ãģª ãĤĭ",
+      "×ķ׾ ×Ŀ",
+      "à¹ģ à¸Ĺ",
+      "×ķ× ¥",
+      "м еÑĤ",
+      "ü ÅŁ",
+      "ÑĢ Ñı",
+      "ภĴ",
+      "ÑģÑĤ оÑı",
+      "ع ÙĪد",
+      "Ùħ ار",
+      "Ø· Ø©",
+      "à¸ŀ ื",
+      "к ÑĢ",
+      "à¹ģ à¸ģ",
+      "à¹Ĥ รà¸ĩ",
+      "×ij ×Ļ×ĺ",
+      "ê² ł",
+      "×ķ׾ ×Ķ",
+      "ØŃ Ø±",
+      "ืà¹Ī à¸Ńà¸Ļ",
+      "×ķ×ij ר",
+      "׊ש",
+      "ãĥķãĤ ¡",
+      "×ŀ ×ĺ",
+      "ú t",
+      "Ġd ön",
+      "ắ ng",
+      "ëł ĩ",
+      "ẳ ng",
+      "ว à¸ģ",
+      "ص د",
+      "Ø® Ø·",
+      "à¸Ń ั",
+      "ãĤı ãĤĮ",
+      "سÙĦ اÙħ",
+      "à¹Ģร à¹ĩ",
+      "×Ļש ×Ļ",
+      "ج اÙĦ",
+      "ãģij ãĤĭ",
+      "à¸Ĭา à¸ķิ",
+      "ÙĪا ÙĤ",
+      "à¹Ĥ à¸Ļ",
+      "ãģ¦ ãģĹãģ¾",
+      "اع ة",
+      "ãĤŃ ãĥ£",
+      "à¸į า",
+      "ÙĦا ÙĤ",
+      "ิ à¸ģ",
+      "ĠÑģ ов",
+      "ÑĢаРº",
+      "×Ļ׳ ×Ļ",
+      "ü ÄŁ",
+      "Ã¼ÄŁ ü",
+      "ק ×ij",
+      "à¹Ī à¸Ńà¸ĩ",
+      "Ġger çek",
+      "à¸Ĺ ั",
+      "ов аниÑı",
+      "×ŀ ׼",
+      "س ة",
+      "×Ļ× £",
+      "le ÅŁ",
+      "Ùħ ؤ",
+      "ĠìĿ ĺ",
+      "à¸IJ าà¸Ļ",
+      "ĠÑģ об",
+      "Ġêµ Ń",
+      "ע צ",
+      "з в",
+      "ส à¸ĩ",
+      "ز ÙĦ",
+      "ãģı ãĤĮ",
+      "и ÑĢÑĥ",
+      "ت أ",
+      "п олн",
+      "ìĺ Ģ",
+      "ÙĨ Ø´",
+      "׼ ×IJ",
+      "Ùħ Ø´",
+      "à¸Ķ à¹Į",
+      "ÙĪ ÙĬÙĦ",
+      "à¹ģ à¸Ĥ",
+      "ãģ£ãģ¦ ãģĹãģ¾",
+      "но ÑģÑĤ",
+      "в л",
+      "Ùħ ÙĤ",
+      "را ج",
+      "å¤ ī",
+      "ë Ľ",
+      "â ¸",
+      "ì IJ",
+      "à »",
+      "á ļ",
+      "â »",
+      "ê Ļ",
+      "â §",
+      "ð Ĵ",
+      "ðĿ ĩ",
+      "Ġ×IJ ת",
+      "ĠÙĦ ÙĦ",
+      "ĠØ£ ÙĨ",
+      "Ġ×ķ ×Ķ",
+      "ãģ« ãģ¯",
+      "Ġ×Ļ ש",
+      "ت Ùĩ",
+      "ÃŃ nh",
+      "ÙĬ ات",
+      "Ġ×ij ×ŀ",
+      "à¸Ļั à¹īà¸Ļ",
+      "à¸Ļ à¹īำ",
+      "Ãł o",
+      "à¸ķ าม",
+      "ãģ® ãģ¯",
+      "d ır",
+      "Ġn ghi",
+      "ặ t",
+      "×ŀ ×Ļ×Ŀ",
+      "ãģ¦ ãģĦãĤĭ",
+      "Ġ×ij ת",
+      "หร ืà¸Ń",
+      "Ġس ÙĬ",
+      "ãģª ãĤī",
+      "à¹Ĥà¸Ķ ย",
+      "ı yor",
+      "à¸Ńี à¸ģ",
+      "á»ĩ nh",
+      "Ñĭ м",
+      "à¸Ĺุ à¸ģ",
+      "Ġ׾ ×Ĺ",
+      "Ġ×Ķ ר",
+      "Ġ×Ķ ×Ļ",
+      "à¸ŀ ระ",
+      "à¹Ģว ลา",
+      "ĠØ º",
+      "ẫ n",
+      "m Ä±ÅŁ",
+      "׼ ×Ķ",
+      "á»ij n",
+      "ãģ§ ãģĹãĤĩãģĨ",
+      "ãĥ ¢",
+      "à¸Ľ ี",
+      "ס ×Ļ",
+      "ãģĵ ãĤį",
+      "Ġ׾ פ",
+      "ร à¸ĸ",
+      "ê¸ Ī",
+      "à¸ģ วà¹Īา",
+      "ë ¬´",
+      "á»į ng",
+      "ãĤĵ ãģ§",
+      "ãĤĪãģĨ ãģª",
+      "á»ĵ i",
+      "ãĤ ¬",
+      "ส à¹Īà¸ĩ",
+      "×Ļ׳ ×Ķ",
+      "à¸ĸ ูà¸ģ",
+      "à¸Ī ัà¸Ķ",
+      "Ġ×Ķ ×Ĵ",
+      "ãĥ ľ",
+      "×ŀ ×ķת",
+      "ÙĪ Ùĥ",
+      "ëĭ ¨",
+      "ĠØ «",
+      "ãģ® ãģĮ",
+      "à¹Ģห à¹ĩà¸Ļ",
+      "ع ا",
+      "à¸Ļ ิ",
+      "Å ŀ",
+      "à¸Ń ะ",
+      "ãģĪ ãĤĭ",
+      "Ø« ÙĦ",
+      "ØŃÙħ د",
+      "à¹Ģà¸ģ ิà¸Ķ",
+      "פ שר",
+      "פ ×Ķ",
+      "ม ิ",
+      "ئ ÙĬس",
+      "à¸Ĺำ à¹ĥหà¹ī",
+      "×¢ ×ĵ",
+      "ìĭ ¤",
+      "à¸Ĭà¹Īว ย",
+      "ĠاÙĦÙħ ÙĨ",
+      "ز ÙĬ",
+      "ع ÙĬ",
+      "Ġ׼ ×IJ",
+      "ạ nh",
+      "á» ¹",
+      "ãĤĵ ãģª",
+      "ส ู",
+      "צ ר",
+      "Æ°á»Ľ ng",
+      "×ķ ×ķ×Ķ",
+      "à¹Ĥ ล",
+      "ĠاÙĦ Ùĩ",
+      "ว า",
+      "หล าย",
+      "Ñī е",
+      "à¸Ĥ à¹īà¸Ń",
+      "à¹īà¸Ń ย",
+      "ب ط",
+      "ка Ñı",
+      "ĠØ ¢",
+      "Ġи Ñģ",
+      "ĠاÙĦ غ",
+      "à¸ģ า",
+      "à¸Ļ à¹Īา",
+      "ÙĬ ÙĪ",
+      "×ij ×ķר",
+      "á»ħ n",
+      "ว à¸ĩ",
+      "×Ļ× ĸ",
+      "ì² Ń",
+      "н им",
+      "ëŁ °",
+      "×Ĵ ×ķר",
+      "ص ØŃ",
+      "ÙĦ ÙĪ",
+      "×Ĺ ×ķת",
+      "ส ุ",
+      "رÙĬ ÙĤ",
+      "ס ×ĺ",
+      "Ġ×ŀ ×¢",
+      "ãĥĨ ãĤ£",
+      "à¸Ħ ิà¸Ķ",
+      "ãĤį ãģĨ",
+      "à¹Ħ ล",
+      "à¸Ļ à¹Į",
+      "á»ı i",
+      "ÑģÑĤÑĢ о",
+      "ส à¸Ķ",
+      "ส าร",
+      "ÙĪÙĦ Ø©",
+      "ầ m",
+      "ร à¹Īว",
+      "รà¹Īว ม",
+      "ร ุ",
+      "ĠاÙĦس ÙĬ",
+      "ìĺ ģ",
+      "Ġ×ŀ ×ij",
+      "פ ×ĺ",
+      "à¸ķิ à¸Ķ",
+      "×ĺ ×Ļ×Ŀ",
+      "Ġë ¬´",
+      "ÙĤد Ùħ",
+      "Ġdü ÅŁ",
+      "ائ ÙĦ",
+      "м Ñĭ",
+      "ØŃ Ø³",
+      "ÙĪ ص",
+      "×Ļק ×Ķ",
+      "ãģ§ãģ¯ ãģªãģĦ",
+      "à¹Ģ หม",
+      "оÑĢ ÑĤ",
+      "í Ĩµ",
+      "ãģ IJ",
+      "к ÑĢа",
+      "ีย ว",
+      "ع ار",
+      "ئ ة",
+      "íĥ Ģ",
+      "ãģ«ãģª ãĤĬ",
+      "ج ة",
+      "ÙĪÙĤ ع",
+      "ÑĮ Ñı",
+      "×ķצ ×Ķ",
+      "ש ×Ŀ",
+      "ب ÙĤ",
+      "Ġ×Ļ ×Ķ",
+      "ÙĬ Ø·",
+      "ım ız",
+      "д еÑĢж",
+      "×Ļש ר×IJ׾",
+      "غ ÙĬر",
+      "ร à¸Ńà¸ĩ",
+      "à¹Ģรีย à¸Ļ",
+      "Ġ×Ķ ×ĺ",
+      "หม าย",
+      "Ùħ Ùĩ",
+      "اÙģ Ø©",
+      "Ġо ÑĢг",
+      "ÙĪ Ùī",
+      "ãĥ© ãĤ¤",
+      "×ŀ ׳×Ķ",
+      "ĠÄij o",
+      "Ġг оÑĢ",
+      "اÙħ Ø©",
+      "æ¥ ½",
+      "Ø« ÙĬر",
+      "à¸ģิ à¸Ī",
+      "á»ĵ n",
+      "ÙĨ ب",
+      "ÑĢÑĥ д",
+      "ìĹ Ī",
+      "Ġ×Ĺ ×ijר",
+      "ÑĢаР¶",
+      "ạ ch",
+      "ت ÙĪ",
+      "à¹Ĥ ม",
+      "×ij ×Ļ×ij",
+      "Ġí Ĩµ",
+      "aca ģı",
+      "جÙĦ س",
+      "à¹Ģà¸Ľ ล",
+      "ว à¸Ķ",
+      "à¸Ń ล",
+      "ãģŁ ãĤĬ",
+      "à¸Ľ ัà¸į",
+      "Ġìķ Į",
+      "عر Ùģ",
+      "à¹Ħ à¸Ł",
+      "Ø£ Ø®",
+      "å¤ļ ãģĦ",
+      "à¸Ķ ัà¸ĩ",
+      "Ø´ Ùģ",
+      "ãģ£ãģ¦ ãģĦãģ¾ãģĻ",
+      "׼ ×ł×¡",
+      "ÑĨ е",
+      "еÑģ п",
+      "Ùħ اÙħ",
+      "à¸ŀื à¹īà¸Ļ",
+      "иÑĩеÑģ ки",
+      "خ د",
+      "Ùĥ ÙĪÙħ",
+      "Ġ×Ķ ר×IJש",
+      "ت اب",
+      "é£Ł ãģ¹",
+      "ื à¸Ļ",
+      "оÑĢ о",
+      "Ġb öl",
+      "×ķ×Ĺ ×ĵ",
+      "دÙĬ ر",
+      "ắ m",
+      "د ع",
+      "ãģķ ãģĽ",
+      "à¸ĺ ร",
+      "à¸ĺร รม",
+      "ãģĭ ãĤĤ",
+      "å¤ļ ãģı",
+      "r ä",
+      "س ع",
+      "×Ļ׾ ×Ķ",
+      "ض ر",
+      "ĠاÙĦ شر",
+      "×ĸ ×ķר",
+      "×¢ ×ijר",
+      "ạ m",
+      "алÑĮ но",
+      "ر ÙĨ",
+      "اÙħ ج",
+      "׼ ×ļ",
+      "d ıģ",
+      "д ен",
+      "ض ا",
+      "ÙĦÙĬ Ùħ",
+      "Ġê·¸ 룬",
+      "تÙħ اع",
+      "ار ÙĬØ®",
+      "à¹Ĥ à¸ķ",
+      "ĠÑģ ÑĢед",
+      "Ġ׳ ×ķס",
+      "ÙĤ بÙĦ",
+      "оÑĤ ов",
+      "le ÅŁtir",
+      "Ġм еÑģÑĤ",
+      "سÙĦ Ùħ",
+      "Ġ×¢ צ",
+      "ĠاÙĦس ÙĦ",
+      "еÑĤ ÑĮ",
+      "اب ة",
+      "н ак",
+      "สà¸ĸ าà¸Ļ",
+      "Ġ×ij ׳",
+      "à¸ļ ัà¸Ļ",
+      "׼ ׳",
+      "Ġö ÄŁ",
+      "ãģ¨ è¨Ģ",
+      "uy ến",
+      "di ÄŁ",
+      "áºŃ u",
+      "ÑĢ аÑģ",
+      "ãĤ· ãĥ§ãĥ³",
+      "n ız",
+      "×ķ×ĵ ×Ķ",
+      "ت س",
+      "Ùħ اÙĦ",
+      "à¹Ģห à¸ķุ",
+      "ย ว",
+      "à¸ŀ ัà¸ģ",
+      "ãģĦ ãģªãģĦ",
+      "Ġк аÑĩ",
+      "ล à¹Į",
+      "ר׼ ת",
+      "ÅŁt ur",
+      "×ŀ ×ķס",
+      "ãģ ¥",
+      "б ол",
+      "عÙħ اÙĦ",
+      "×ķר ת",
+      "ÑĨи он",
+      "ศ ึà¸ģ",
+      "ภı",
+      "ÑĢ ен",
+      "اس ÙĬ",
+      "ائ ر",
+      "à¹Ĥ à¸Ľà¸£",
+      "Ġse ç",
+      "غ ÙĬ",
+      "Ñį ÑĤ",
+      "ен н",
+      "ãģª ãģ®",
+      "×Ļש ×Ķ",
+      "×Ļפ ×ķר",
+      "ãģŁãĤģ ãģ«",
+      "ز ة",
+      "Ġç oc",
+      "ãĤ¯ ãĥª",
+      "ÑĪ ен",
+      "ãĤı ãģij",
+      "رÙĬ د",
+      "ĠÑĢ аÑģÑģ",
+      "Ùĥ ات",
+      "ส à¸Ńà¸ļ",
+      "ce ÄŁi",
+      "ãĤ¿ ãĤ¤",
+      "à¸ļ ร",
+      "ĠاÙĦ بر",
+      "׳ ×ķ×¢",
+      "r ün",
+      "را ض",
+      "ศา ส",
+      "à¸ķ รà¹Į",
+      "ãģį ãģŁ",
+      "×ķ׾ ×ĵ",
+      "еÑĢ и",
+      "íĹ ĺ",
+      "ắ p",
+      "ت عÙĦ",
+      "Ùĥ د",
+      "иÑĤелÑĮ но",
+      "Ø· Ùģ",
+      "Ġав ÑĤом",
+      "Ġ×ŀ צ",
+      "ÑĪи Ñħ",
+      "ات Ùģ",
+      "ĠÑħ оÑĤ",
+      "Ùİ Ø§",
+      "ãģı ãĤĭ",
+      "×Ķ פ",
+      "à¹Ĥ à¸Ĺ",
+      "à¹ģ à¸ŀ",
+      "à¹Ī à¸Ńย",
+      "ĠاÙĦÙħ Ø´",
+      "à¸ģาร à¸ĵà¹Į",
+      "ани з",
+      "×Ķ ׾",
+      "ظ Ùħ",
+      "ย ุ",
+      "li ÄŁ",
+      "à¹Ħ à¸Ĥ",
+      "à¸ĸ ืà¸Ń",
+      "ö z",
+      "ãģij ãģ¦",
+      "à¹Ģ à¸ľ",
+      "ุ ม",
+      "ãĥĹ ãĥ¬",
+      "Ġ×Ķ×IJ ×Ĺר",
+      "خت ÙĦÙģ",
+      "ภİ",
+      "ÙĦا ØŃ",
+      "Ġdü zen",
+      "צ ×Ķ",
+      "س اء",
+      "×ķר ×ļ",
+      "×ķ×ĵ ×Ļ",
+      "ÑĢа ÑĦ",
+      "ÅŁt ır",
+      "ãģ« åħ¥",
+      "ãģĪ ãģ°",
+      "ص ÙĪÙĦ",
+      "ĠÐľ оÑģ",
+      "ا Ùĩر",
+      "ãģ£ ãģ",
+      "ĠлÑİ Ð±",
+      "×Ļ×¢ ×Ķ",
+      "Ġ×Ķ×ŀ ק",
+      "สิ à¸Ĺ",
+      "สิà¸Ĺ à¸ĺิ",
+      "×Ļ׳ ×Ŀ",
+      "ÙĦا Ùģ",
+      "à¸ŀัà¸Ļ à¸ĺ",
+      "×ķ×IJ ×Ķ",
+      "ม ั",
+      "à¸Ĥ à¸ĵะ",
+      "д оÑĢ",
+      "ãģ¨ ãģª",
+      "à¸ģระ à¸Ĺ",
+      "ac ı",
+      "×ķ׾ ×ķ×Ĵ",
+      "Ñĥ ÑĪ",
+      "ãĥ¥ ãĥ¼",
+      "ãĥ ¦",
+      "Ùħ ست",
+      "Ġa ÅŁ",
+      "ש ק",
+      "פ ת×Ĺ",
+      "าย à¸Ļ",
+      "í ĩ",
+      "ë ¢",
+      "ï ·",
+      "í ī",
+      "ì µ",
+      "ì ¬",
+      "ðĿ Ľ",
+      "ì Ĵ",
+      "ë Ļ",
+      "ê §",
+      "á ĸ",
+      "â ¨",
+      "â ±",
+      "á ĺ",
+      "ð ĸ",
+      "à ł",
+      "á Ķ",
+      "ðIJ Ń",
+      "ữ ng",
+      "Å© ng",
+      "Ġ×Ķ ת",
+      "ĠاÙĦ ا",
+      "Ġ×ŀ ת",
+      "à¸ĸ ึà¸ĩ",
+      "ò n",
+      "á»ĭ nh",
+      "нÑĭ м",
+      "Ġc ả",
+      "à¸Ķ ู",
+      "Ġ à¹ģà¸ķà¹Ī",
+      "Ġ×ij ×Ķ",
+      "ó i",
+      "ãģ¨ ãģĹãģ¦",
+      "ú ng",
+      "ĠØ °",
+      "Ġ×Ķ ׳",
+      "Ġب ÙĨ",
+      "ÙĦ اÙĦ",
+      "à¹Ħ à¸Ĺย",
+      "á»ĩ p",
+      "t ı",
+      "ม ัà¸Ļ",
+      "ằ ng",
+      "á»ij t",
+      "к ом",
+      "à¸ĭ ึà¹Īà¸ĩ",
+      "à¸Ħร ัà¸ļ",
+      "à¸ļ à¹īาà¸Ļ",
+      "ĠاÙĦ ÙĬ",
+      "l ü",
+      "ÙĪ س",
+      "ãģł ãģ£ãģŁ",
+      "à¹Ģ à¸ĩ",
+      "Ġê³ µ",
+      "н Ñĥ",
+      "ãĤĪ ãĤĬ",
+      "м Ñĥ",
+      "à¹Ģà¸Ĥ า",
+      "ãĤ Ģ",
+      "ни е",
+      "ãģ«ãģª ãĤĭ",
+      "áºŃ y",
+      "ĠÙĪ ا",
+      "ëł ¤",
+      "ש ×ķ",
+      "á p",
+      "×ĵ ×ķ",
+      "ãģ§ ãģĹãģŁ",
+      "ع ض",
+      "Ñģк ой",
+      "æĦŁ ãģĺ",
+      "ÑİÑĤ ÑģÑı",
+      "Ġ×Ļ ׼×ķ׾",
+      "ãĤĵ ãģł",
+      "в и",
+      "à¹Ģล à¹Īà¸Ļ",
+      "ìĿ´ ëĭ¤",
+      "ĠÙĦ Ùĩ",
+      "à¸Ħ ืà¸Ń",
+      "ت Ùĥ",
+      "Ùħ ÙĥÙĨ",
+      "a ģı",
+      "׳ ×ĵ",
+      "ë¯ ¼",
+      "à¹Ħ ว",
+      "สำ ห",
+      "สำห รัà¸ļ",
+      "Ñģл ед",
+      "t ır",
+      "ĠÙĦ ÙĬ",
+      "ĠاÙĦع ÙħÙĦ",
+      "×ij ×ķת",
+      "×ij ×Ļ×Ŀ",
+      "à¸Ħ ำ",
+      "à¹Ģà¸Ħร ืà¹Īà¸Ńà¸ĩ",
+      "lı ģı",
+      "ืà¸Ń à¸ĩ",
+      "ج د",
+      "íŀ Ī",
+      "ìĭ ¬",
+      "×¢ ×ķת",
+      "ส ิà¸Ļ",
+      "Ñĩ и",
+      "ر ض",
+      "à¹Ģà¸Ľ ิà¸Ķ",
+      "à¸Ħ à¹Īา",
+      "ìĦ ł",
+      "ÙĪر Ø©",
+      "ק ×ĺ",
+      "ìľ ł",
+      "ع ÙħÙĦ",
+      "×IJ ×Ļ×Ŀ",
+      "׾ ×Ļ×Ŀ",
+      "à¹ĥห à¸į",
+      "à¹ĥหà¸į à¹Ī",
+      "ừ a",
+      "á»į i",
+      "ãģ ¶",
+      "ÃŃ ch",
+      "ãĥĩ ãĤ£",
+      "×ķר ×Ļ×Ŀ",
+      "Ñģ о",
+      "ìķ ½",
+      "ов а",
+      "Ñĩ аÑģÑĤ",
+      "à¹Ģà¸Ī à¹īา",
+      "п ÑĢо",
+      "Ġ×ŀ ×Ĺ",
+      "ãĥ İ",
+      "×ķ×Ļ ×ķת",
+      "Ġд е",
+      "ë§ Ī",
+      "ì§ ģ",
+      "×Ļפ ×Ķ",
+      "ĠاÙĦع اÙĦÙħ",
+      "ë¥ ´",
+      "ר×IJ ×Ķ",
+      "uy á»ĥn",
+      "×¢ ×Ļ",
+      "ม ืà¸Ń",
+      "Ø¥ ÙĨ",
+      "ร ู",
+      "ĠØ ²",
+      "×Ļ ×ķ×Ŀ",
+      "à¸ķ à¹īà¸Ļ",
+      "ãģ¦ ãģĦãģ¾ãģĻ",
+      "Ùħ اÙĨ",
+      "ĠÐ ¥",
+      "à¸Ľà¸£à¸° à¹Ģà¸Ĺศ",
+      "á» ³",
+      "׾ ×ij",
+      "à¹Ģà¸Ķ à¹ĩ",
+      "ãģŁ ãģ¡",
+      "à¸Ĺี ม",
+      "à¸Ļ ะ",
+      "ìĹ °",
+      "Ġìł Ģ",
+      "ÙĦ Ùĩ",
+      "ợ i",
+      "ĠاÙĦ ز",
+      "د ار",
+      "ãĤ³ ãĥ³",
+      "м ин",
+      "à¹ģห à¹Īà¸ĩ",
+      "à¸Ķ ัà¸ļ",
+      "׼ ר",
+      "ж а",
+      "íĸ Ī",
+      "×ŀ ×ĸ",
+      "ợ i",
+      "à¸Ķ า",
+      "Ġع بد",
+      "à¹ģ ร",
+      "×IJת ר",
+      "×¢ ׳×Ļ",
+      "à¹Ģ à¸Ħ",
+      "×ķצ ר",
+      "ì§Ģ ë§Į",
+      "ائ Ùħ",
+      "أ س",
+      "uy á»ģn",
+      "Ġ×IJ ׳",
+      "׊׳×ķ",
+      "×ĸ ×Ļ",
+      "ร à¹īาà¸Ļ",
+      "ĠÐł оÑģ",
+      "ĠÐłÐ¾Ñģ Ñģ",
+      "رب ÙĬØ©",
+      "t ür",
+      "ãĤĭ ãģĵãģ¨",
+      "ظ ر",
+      "б Ñĭ",
+      "à¸Ĺีà¹Ī สุà¸Ķ",
+      "Ġצ ר",
+      "èĩª åĪĨ",
+      "л аÑģ",
+      "ĠÑı в",
+      "ĠÑıв лÑı",
+      "à¸ŀร à¹īà¸Ńม",
+      "à¸Ńา à¸Ī",
+      "à¸ļริ à¸ģาร",
+      "Ġç ı",
+      "ëį ĺ",
+      "ĠاÙĦÙħ ست",
+      "ت ش",
+      "ש ×ķ×ij",
+      "ãĤ ´",
+      "Ġyap ıl",
+      "ĠاÙĦ Ø°",
+      "ุ à¹Īม",
+      "à¸ĸ à¹īา",
+      "ìĦ ¤",
+      "ì° ¨",
+      "в аÑĢ",
+      "à¹Ģà¸ŀ ิà¹Īม",
+      "Æ°á»Ľ i",
+      "Ùĥ س",
+      "à¸Ńย าà¸ģ",
+      "ãģ¦ ãĤĤ",
+      "Ġг од",
+      "ÙĬ ار",
+      "à¸ķ à¸Ńà¸Ļ",
+      "Ġиг ÑĢ",
+      "à¹Ħà¸Ķà¹ī รัà¸ļ",
+      "ĠاÙĦÙħ ر",
+      "ÙĤ ت",
+      "Ġë ĺ",
+      "Ġëĺ IJ",
+      "ẩ n",
+      "ãģĻãĤĭ ãģĵãģ¨",
+      "×Ĵ ×Ŀ",
+      "Ġ×ij ×ij",
+      "ت د",
+      "ÙĪ ار",
+      "ãĤ ®",
+      "п ол",
+      "Ġм ог",
+      "تر Ùĥ",
+      "ÙĪ Ø«",
+      "Ġç ık",
+      "ا ة",
+      "à¹Ģà¸Ķ ียว",
+      "มี à¸Ħวาม",
+      "Ġ×ŀ ×Ĵ",
+      "ص Ùģ",
+      "ĠТ ак",
+      "Ġ׼ ת",
+      "×Ļ×ĵ ×Ļ",
+      "ов оÑĢ",
+      "ầ y",
+      "สิ à¹Īà¸ĩ",
+      "ب ت",
+      "ür ü",
+      "ÙĨ ج",
+      "หล ัà¸ģ",
+      "×Ļ×Ķ ×Ŀ",
+      "ÙĤ ص",
+      "з Ñĭ",
+      "×Ľ×ª ×ij",
+      "Æ° u",
+      "m ız",
+      "ĠìĦ ¸",
+      "л ог",
+      "Ùħ ÙĬÙĦ",
+      "ÙĬ ج",
+      "íĴ Ī",
+      "à¸ŀ à¸ļ",
+      "ห ัว",
+      "з на",
+      "ר ק",
+      "à¹Ĥ ร",
+      "Ġ×ij ס",
+      "ĠBaÅŁ kan",
+      "ĠëĶ °",
+      "à¸Ń ัà¸Ļ",
+      "ีà¹Īย ว",
+      "н еÑģ",
+      "à¹Ģà¸Ķ ิà¸Ļ",
+      "ÙĬ اÙĨ",
+      "×ķ׾ ×Ļ",
+      "ا خت",
+      "צ ×ķת",
+      "ãģĵ ãģĵ",
+      "ĠاÙĦ اÙĨ",
+      "ĠпÑĢо ÑĨ",
+      "ãģ¾ ãģł",
+      "׼ ס",
+      "ĠاÙĦ Ø¢",
+      "ÙĬ ز",
+      "ĠاÙĦد ÙĪÙĦ",
+      "Ġíķĺ ëĤĺ",
+      "ض ع",
+      "ê» ĺ",
+      "ÅĽ wi",
+      "ย ิ",
+      "ãģ¡ãĤĥ ãĤĵ",
+      "ĠÙħ Ø´",
+      "à¸ĺ ี",
+      "ãģ¨ ãģį",
+      "׳×Ļ ×ķת",
+      "Ġë ¯",
+      "Ġë¯ ¸",
+      "Ġs ı",
+      "ëĭĪ ê¹Į",
+      "Ġп л",
+      "غ ÙĦ",
+      "à¹ģ รà¸ĩ",
+      "ب ÙĬر",
+      "ãģĤãĤĬ ãģ¾ãģĽãĤĵ",
+      "ê· ¼",
+      "Ġy üz",
+      "ĠdeÄŁ er",
+      "åł´ åIJĪ",
+      "á» ¡",
+      "м аÑĤ",
+      "รา à¸Ĭ",
+      "ÙĪر ÙĬ",
+      "ж ен",
+      "ãģ¾ ãĤĬ",
+      "ãģ® ä¸Ń",
+      "×Ļ×ĵ ×¢",
+      "à¸Ń ุ",
+      "à¸ļ à¸Ńล",
+      "à¸Ľà¸±à¸į หา",
+      "ز Ùħ",
+      "ÄŁ a",
+      "à¸Ń ืà¹Ī",
+      "à¸Ńืà¹Ī à¸Ļ",
+      "п л",
+      "Ġне обÑħодим",
+      "׼ ×ij",
+      "à¹Ģ ศ",
+      "קר ×Ķ",
+      "ì² ĺ",
+      "ëł ¨",
+      "×ŀק ×ķ×Ŀ",
+      "jÄħ c",
+      "Ùĩ ÙĦ",
+      "Ġ×¢ ×ij×ķ×ĵ",
+      "à¹Ħม à¹ī",
+      "à¸ģล ัà¸ļ",
+      "×ķ׼ ׾",
+      "ק ×ĵ",
+      "اÙĦ ÙĬØ©",
+      "ر Ùĩ",
+      "ãģij ãĤĮãģ°",
+      "ĠÙĨ Ùģس",
+      "ãĤ¢ ãĥ«",
+      "ìĹ Īëĭ¤",
+      "ק ×ķר",
+      "н еÑĢ",
+      "ب اب",
+      "ãĤ ¶",
+      "سب ب",
+      "ÙĦ ÙĬÙĦ",
+      "ص ÙĨ",
+      "ص در",
+      "ế m",
+      "à¸Ĭà¹Īว à¸ĩ",
+      "ØŃ ÙĨ",
+      "Ġ×ij ×Ĵ",
+      "×ŀ ×ķ×¢",
+      "׾ ×Ĺ",
+      "大 ãģį",
+      "ت ب",
+      "н еÑĤ",
+      "×Ļ×ij ×Ķ",
+      "б л",
+      "ãĥĹ ãĥª",
+      "اص ة",
+      "ãģ¤ ãģij",
+      "×Ļ×ŀ ×ķש",
+      "ãģĮ ãģĤ",
+      "ëĭ ´",
+      "ãģĭãĤĤ ãģĹ",
+      "ãģĭãĤĤãģĹ ãĤĮ",
+      "ãģ¡ ãĤī",
+      "×ij ×ĺ",
+      "Ġba ÄŁ",
+      "×Ļ×Ĺ ×¡",
+      "×ij ×ķ×¢",
+      "ล ี",
+      "פע ×Ļ׾",
+      "им и",
+      "g ÅĤ",
+      "Ġим е",
+      "خد اÙħ",
+      "×IJ ×Ļר",
+      "Ġy apt",
+      "ãģ¨ ãģĦ",
+      "à¸ĩ à¹Īาย",
+      "׾×Ļ ×ķ",
+      "ØŃد Ø«",
+      "را ÙĤ",
+      "ĠÄIJ i",
+      "اد ر",
+      "ãģĵãģ¨ ãĤĤ",
+      "×ij ×Ļר",
+      "Ġв з",
+      "ض اÙģ",
+      "ת ×ķ׼",
+      "ÑĢ ом",
+      "ر ات",
+      "à¹Ģà¸Ĺ à¹Īา",
+      "ãģĺ ãĤĥ",
+      "ãģĿ ãģĵ",
+      "اج تÙħاع",
+      "à¹īà¸Ń à¸Ļ",
+      "ÙĤ Ùħ",
+      "ë³ ¸",
+      "Ä ŀ",
+      "ש ×Ļ×ķ",
+      "×ij ׳×Ļ",
+      "ìľĦ ìĽIJ",
+      "à¹ģ à¸Ī",
+      "×Ĺ ×ķר",
+      "دÙĬ ÙĨØ©",
+      "ت ط",
+      "ằ m",
+      "ò a",
+      "ย à¸Ńà¸Ķ",
+      "Ġëĭ ¹",
+      "สุ à¸Ĥ",
+      "×ĵר ×ļ",
+      "د ÙĨ",
+      "س ÙĬÙĨ",
+      "ÙĪÙĤ Ùģ",
+      "ÑĨ Ñĭ",
+      "г оÑĤов",
+      "еж дÑĥ",
+      "à¸ŀ วà¸ģ",
+      "اÙĤ تص",
+      "اÙĤتص اد",
+      "cz ÄĻ",
+      "ni ÄĻ",
+      "ÑĢ еб",
+      "ØŃ ÙĪ",
+      "à¸Ĺ à¹Į",
+      "ãĤĪ ãģŃ",
+      "д ж",
+      "à¸ģล à¹Īาว",
+      "دÙĬ Ø«",
+      "ãĤ³ ãĥŁ",
+      "ÙĤ ÙĪÙħ",
+      "Ġت ØŃ",
+      "à¹Ģ à¸ķิ",
+      "اÙģ ظ",
+      "à¸Ī ุ",
+      "رÙĬ اض",
+      "×ŀש ×ļ",
+      "à¹Ĥ ย",
+      "еÑĢ е",
+      "ãģ¿ ãģŁãģĦ",
+      "ìĿ´ ëĿ¼",
+      "ĠاÙĦÙħ ÙĪ",
+      "ĠÑģÑĤ о",
+      "à¹Ģรà¹ĩ ว",
+      "Ġд еÑĤ",
+      "ĠÑģ дел",
+      "à¹Ģà¸Ĭ ืà¹Īà¸Ń",
+      "פ ׳×Ļ",
+      "ÙĪض ÙĪع",
+      "×ij ס",
+      "à¹ģ à¸Ķ",
+      "ó c",
+      "ริ ม",
+      "ÑĢаР´",
+      "ìĪ ł",
+      "ãĥ¼ãĤ º",
+      "ãģ« ãģĬ",
+      "и но",
+      "פ ×Ļ׾",
+      "à¸Ĭั à¹Īà¸Ļ",
+      "×Ĺ×ĵ ש",
+      "à¹Ģà¸Ļ ืà¹Īà¸Ńà¸ĩ",
+      "׳ ×Ļס",
+      "غ رب",
+      "ãĤ¸ ãĥ£",
+      "ส ัà¸ĩ",
+      "à¹Ģ à¸Ĺีà¹Ī",
+      "à¹Ģà¸Ĺีà¹Ī ยว",
+      "ëŁ ¼",
+      "à¹ģ à¸Ł",
+      "ãĥ¼ãĤ ·",
+      "ãĥ¼ãĤ· ãĥ§ãĥ³",
+      "Ġвоз мож",
+      "جÙħ ÙĪع",
+      "×ijר ×Ļ×Ŀ",
+      "ãĥĪ ãĥ©",
+      "ĠкаÑĩ еÑģÑĤв",
+      "Ø· ÙĬ",
+      "ÑĤ Ñı",
+      "צ ×ķ×¢",
+      "ģ ını",
+      "ع ÙĦÙī",
+      "ا ذ",
+      "ÙĪاÙĤ ع",
+      "Ùħ ÙĪا",
+      "ائ ÙĬÙĦ",
+      "к ол",
+      "á»ģ m",
+      "à¸ľà¸¥ ิà¸ķ",
+      "×Ļ׳ ×ĺר",
+      "س Ùĥ",
+      "ש ×Ļר",
+      "ศึà¸ģ ษา",
+      "à¸ļ ั",
+      "Ñĩ аÑģ",
+      "×ķפ ×Ķ",
+      "×Ļפ ×ķ׾",
+      "ĠاÙĦس اب",
+      "رÙĬ ب",
+      "ĠاÙĦ بÙĬ",
+      "ãĤ¹ ãĥĨ",
+      "Ñĩ ен",
+      "à¹ģ à¸ľ",
+      "Ġ׳ ש",
+      "ز ÙĬد",
+      "ØŃ Ø§Ø¯",
+      "ëį Ķ",
+      "رÙĪ ع",
+      "à¸Ĺุ à¸Ļ",
+      "ส มา",
+      "c zeÅĦ",
+      "×Ļ×ĵ ×Ķ",
+      "ãģ§ ãģĤ",
+      "Ġçoc uk",
+      "خ ب",
+      "à¸ļ าย",
+      "à¸Ľà¸£à¸° à¸Ĭา",
+      "×ŀש ׾",
+      "ãģª ãģĭ",
+      "à¸ģ าย",
+      "ãĥģ ãĥ£",
+      "аÑĢ и",
+      "ĠÑĩ а",
+      "à¸Ķ ำ",
+      "à¸Ĺั à¹Īว",
+      "Ñĥ Ñħ",
+      "Ġö z",
+      "Ġì¢ ĭ",
+      "ج رÙĬ",
+      "ائ ÙĤ",
+      "à¸ł ัย",
+      "ط ار",
+      "د ارة",
+      "Ä© nh",
+      "Ø« ÙĨ",
+      "zell ik",
+      "اÙĦ ت",
+      "Ġg eli",
+      "ãĥķãĤ ©",
+      "ол од",
+      "رب ع",
+      "שת ×ŀש",
+      "à¸ļร ร",
+      "íĿ ¬",
+      "Ġü rün",
+      "Ġê·¸ ëłĩ",
+      "ศาส à¸ķรà¹Į",
+      "ãģ ľ",
+      "×Ļ×ij ׾",
+      "ĠпÑĢед ÑģÑĤав",
+      "سط ÙĬÙĨ",
+      "ãĤĴ 使",
+      "Ġпом оÑī",
+      "×ķק ר",
+      "ãĥ¯ ãĥ¼",
+      "Ġyö net",
+      "×Ļק ר",
+      "à¸Ĥ า",
+      "еÑĢи ал",
+      "ØŃ Ùģ",
+      "Ġ×Ļ צ",
+      "à¸Ĺ ิ",
+      "å£ ²",
+      "à¸Ļ à¸Ńà¸ģ",
+      "×ķ׼ ר",
+      "íĻ ľ",
+      "ủ y",
+      "ĠاÙĦÙĤ ر",
+      "×Ļ×ij ×ķת",
+      "ÅĽ ni",
+      "Ùħ شار",
+      "ượ t",
+      "ĠÙĦ دÙĬ",
+      "ÑĤ ел",
+      "ĠØ¥ ÙĦÙĬ",
+      "عÙĦ ÙĪÙħ",
+      "ìķ ĺ",
+      "в иÑĤ",
+      "à¸Ħ ะ",
+      "yr ı",
+      "ãģ¨ ãģ£ãģ¦",
+      "à¹Ģ à¸ī",
+      "à¸ĸ าม",
+      "ÙĤ ار",
+      "عÙĦ اÙħ",
+      "ặ ng",
+      "Ùħ ÙĴ",
+      "×Ļ×ŀ ת",
+      "سب ة",
+      "ãĤ¯ ãĥ©",
+      "×ķס ×£",
+      "ĠпÑĢ ин",
+      "ãģĦ ãĤį",
+      "س اس",
+      "عت بر",
+      "วิ à¸Ĺย",
+      "วิà¸Ĺย า",
+      "س Ùĥر",
+      "ãĤ· ãĥ§",
+      "ãģ ģ",
+      "ัà¸ģ ษ",
+      "×ij ×ķ×Ķ",
+      "ห ย",
+      "ãģ¾ ãĤĮ",
+      "ĠоÑĢг аниз",
+      "каз ал",
+      "ĠÑģв Ñıз",
+      "uy ết",
+      "ĠпÑĢо из",
+      "Ġק ×ĺ",
+      "à¹ģà¸ģ à¹ī",
+      "п ÑĥÑģ",
+      "Ġê·¸ ê²ĥ",
+      "ëĬ IJ",
+      "л екÑģ",
+      "ãĥ¼ãĥ Ĺ",
+      "à¸ķ ำ",
+      "ת×Ĺ ×Ļ׾",
+      "à¸Ńà¸ĩ à¸Ħà¹Į",
+      "Ạµ",
+      "׳ צ",
+      "Ø£ Ø´",
+      "Ø´ Ùĩ",
+      "ย ะ",
+      "à¸ģ à¸İ",
+      "ĠاÙĦØ¥ سÙĦاÙħ",
+      "ед ÑĮ",
+      "ãģ² ãģ¨",
+      "ëıĦ ë¡Ŀ",
+      "ãģ© ãģ®",
+      "Ñĥ в",
+      "еÑĩ ение",
+      "ĠاÙĦت ج",
+      "ãģ« è¡Į",
+      "Ġп озв",
+      "ãĤı ãĤĬ",
+      "ÙĦ اث",
+      "íķĺ ìĺĢ",
+      "Ġм аÑĢ",
+      "Ġkon uÅŁ",
+      "ãĥ¬ ãĤ¹",
+      "ãĤĴ æĮģ",
+      "ĠоÑģ нов",
+      "×Ĺ ×ij",
+      "ÙĪج ÙĪد",
+      "פ ×ķף",
+      "в оÑĢ",
+      "Ġн ик",
+      "ãģĭ ãĤĭ",
+      "ÅŁtır ma",
+      "×Ļס ×ĺ",
+      "Ø£ ÙĦ",
+      "ห à¹Į",
+      "и она",
+      "лÑĮ н",
+      "Ġг оÑģ",
+      "ĠÐľÐ¾Ñģ к",
+      "ÑĢ об",
+      "×ķ×IJ ×Ļ",
+      "ãģĬãĤĬ ãģ¾ãģĻ",
+      "ãģ£ãģ ±",
+      "к л",
+      "à¸Ļ à¸Ķà¹Į",
+      "رÙĬ Ùģ",
+      "اس ب",
+      "ĠÑĢ еÑĪ",
+      "Ġд ол",
+      "ãģ¹ ãģį",
+      "×Ļ×ij ×ķר",
+      "м еÑī",
+      "Ġна ÑĪ",
+      "à¹ģ à¸Ľà¸¥",
+      "ÑĢ иÑĤ",
+      "кÑĥ Ñģ",
+      "и ÑĢа",
+      "аÑĤ ÑĥÑĢ",
+      "ÙĪا صÙĦ",
+      "à¹Ģà¸ľ ย",
+      "à¸Ń ำ",
+      "à¹Ģà¸ģ ิà¸Ļ",
+      "غ Ùħ",
+      "ãģĻ ãģİ",
+      "lı kl",
+      "ÅĦ sk",
+      "ê² ¬",
+      "×Ļ׼ ×Ķ",
+      "׊ש×ij",
+      "ÙĪر ÙĬØ©",
+      "Ġд ейÑģÑĤв",
+      "×Ĺ׾ ×ĺ",
+      "Ġ׾ ×ŀ×¢",
+      "צ׾ ×Ļ×Ĺ",
+      "еÑĩ а",
+      "Ùģ اع",
+      "×Ĵ ×Ļ×ĵ",
+      "áºŃ m",
+      "ÄĻ b",
+      "ش ع",
+      "ãģı ãĤĬ",
+      "à¸ŀ ุ",
+      "ед еÑĢ",
+      "à¸Ĥ à¸Ļ",
+      "à¸Ħ าร",
+      "ĠболÑĮ ÑĪ",
+      "ãģı ãģªãĤĬ",
+      "à¸ĵ า",
+      "×ĵ ×ķ×Ĵ",
+      "Ġм н",
+      "ä¸Ĭ ãģĮ",
+      "ç¶ļ ãģį",
+      "ฤ ษ",
+      "ภĨ",
+      "Ø® ÙĬ",
+      "à¹Ģà¸Ĺ à¸ŀ",
+      "สั ม",
+      "à¹Ģส à¸Ļ",
+      "à¹Ģสà¸Ļ à¸Ń",
+      "ãĥ ´",
+      "Ġи ÑģÑĤ",
+      "با شر",
+      "ĠÑĥ ÑĢов",
+      "×ŀ ×ķ×ĸ",
+      "ab ı",
+      "wa ż",
+      "×ķצ ×IJ×Ķ",
+      "ÑĤ веÑĢ",
+      "à¸ŀัà¸Ļà¸ĺ à¹Į",
+      "׳ ×Ĵ×ĵ",
+      "ãĤĭ ãģĵãģ¨ãģĮãģ§ãģį",
+      "ĠÑĤÑĢ еб",
+      "à¸ģร ุà¸ĩ",
+      "ØŃت اج",
+      "à¹Ģ à¸Ħล",
+      "ã Ĩ",
+      "ÄĻ tr",
+      "Ġszcz eg",
+      "Ġר ש",
+      "à¸Ĺ à¸ĺ",
+      "Ġн ек",
+      "Ġнек оÑĤоÑĢ",
+      "в ÑĪ",
+      "Ð ¬",
+      "à¹Īว ย",
+      "ล ุ",
+      "б ÑĢÑı",
+      "หม ูà¹Ī",
+      "à¹ģ à¸ķà¸ģ",
+      "ר׼ ×Ļ×Ŀ",
+      "Ġí ĸī",
+      "ã i",
+      "Ùĥر Ø©",
+      "â Ń",
+      "í IJ",
+      "ã į",
+      "á ģ",
+      "â ®",
+      "â ¥",
+      "ì ®",
+      "à ¿",
+      "â ¿",
+      "á Ĥ",
+      "á ¤",
+      "â ł",
+      "í Ł",
+      "ðIJ į",
+      "ðIJ °",
+      "ðĿ Ĩ",
+      "ðŁ Ī",
+      "Ġ×¢ ׾",
+      "Ġع ÙĨ",
+      "ĠÙħ ع",
+      "Ġ×ĸ ×Ķ",
+      "ĠÙħ ا",
+      "Ġm Ãł",
+      "Ġd ụ",
+      "á»ĩ c",
+      "а Ñħ",
+      "s ı",
+      "íķĺ ê³ł",
+      "Ġ×ķ ×ij",
+      "ĠÐŁ о",
+      "×ķת ר",
+      "ĠÙĦ Ùħ",
+      "Ġ×ķ ׾",
+      "ãģĹãģ¦ ãģĦãĤĭ",
+      "Ġ×ŀ ×Ļ",
+      "Ġب ÙĬÙĨ",
+      "з а",
+      "ĠÙĥ اÙĨ",
+      "Ġ×Ķ ×Ļ×Ķ",
+      "ëħ Ħ",
+      "×IJ ×ķ",
+      "д и",
+      "ĠпеÑĢ е",
+      "d ı",
+      "Ġ׾ ש",
+      "Ġש ×ŀ",
+      "ãģĮ ãģĤãĤĭ",
+      "ãģĦ ãģĦ",
+      "ÑĢ е",
+      "ק ×ķ",
+      "и ли",
+      "м е",
+      "ÙĬ ت",
+      "ãģ§ ãģĤãĤĭ",
+      "Ġв о",
+      "à¹ĥ หม",
+      "à¹ĥหม à¹Ī",
+      "Ġש ×ij",
+      "Ġ à¹Ĥà¸Ķย",
+      "ÙĬ Ùĩ",
+      "ãģ§ãģĻ ãģĮ",
+      "ãģ¨ ãģ¯",
+      "ר ×ķ",
+      "Ġ à¸ĭึà¹Īà¸ĩ",
+      "ãģ§ãģį ãĤĭ",
+      "м о",
+      "à¹Ģà¸ŀ ืà¹Īà¸Ń",
+      "צ ×ķ",
+      "×ĺ ×ķ",
+      "ìķ Ī",
+      "Ġh á»į",
+      "à¹Ģà¸ĩ ิà¸Ļ",
+      "ĠاÙĦ ب",
+      "Ġ มี",
+      "ë¬ ¼",
+      "Ñģ е",
+      "ëĵ¤ ìĿ´",
+      "Ġë§ IJ",
+      "Ġl Ỽ",
+      "a ÅĤ",
+      "×Ĺ ×ijר",
+      "Ġd á»±",
+      "ÙĬ Ø«",
+      "Ġth á»ĭ",
+      "à¸ģà¹Ī à¸Ńà¸Ļ",
+      "Ġ×ij ׼׾",
+      "ãģ ¸",
+      "ãģ¨æĢĿ ãģĦãģ¾ãģĻ",
+      "ả nh",
+      "ย า",
+      "Ùģ ا",
+      "ส ี",
+      "à¸ķ า",
+      "ë² ķ",
+      "ãĥª ãĥ¼",
+      "รา à¸Ħา",
+      "Ġ×ķ ׾×IJ",
+      "ãģ¨ ãģĵãĤį",
+      "à¹Ģล ืà¸Ń",
+      "di ÄŁi",
+      "ÙĪ اÙĨ",
+      "Ġ׾×Ķ ת",
+      "รว ม",
+      "פ ×Ļ×Ŀ",
+      "à¸ľ ม",
+      "ж и",
+      "c ı",
+      "ÑĢ од",
+      "Ġkar ÅŁÄ±",
+      "×Ĵ ×ķ",
+      "ãģ« ãģ¤",
+      "ãģ«ãģ¤ ãģĦãģ¦",
+      "r Ãł",
+      "×Ļ×ķת ר",
+      "ĠìĨ Į",
+      "ק ×Ķ",
+      "ÑģÑĤв о",
+      "ãģij ãģ©",
+      "g é",
+      "à¸Ķ à¹īาà¸Ļ",
+      "çļĦ ãģ«",
+      "ĠÙĬ ÙħÙĥÙĨ",
+      "ìĨ į",
+      "ÙĬ Ùĥ",
+      "à¹Ħว à¹ī",
+      "Ñģки й",
+      "ì m",
+      "Ġ׾×IJ ×Ĺר",
+      "à¸Ńา หาร",
+      "Ġà¹Ģ à¸ŀ",
+      "รา ะ",
+      "ล ูà¸ģ",
+      "ÑģÑĤ а",
+      "Ġìľ ł",
+      "ÙĤ ÙĪÙĦ",
+      "б оÑĢ",
+      "Ñģк ого",
+      "หล ัà¸ĩ",
+      "à¸Ĥ à¹Īาว",
+      "à¹Ģม ืà¸Ńà¸ĩ",
+      "ê° ģ",
+      "t Ãł",
+      "ÙĬ ÙĬÙĨ",
+      "عر ض",
+      "ë° ©",
+      "Ġëı Ļ",
+      "Ġà¹Ģ à¸Ľ",
+      "Ġà¹Ģà¸Ľ à¹ĩà¸Ļ",
+      "ç i",
+      "li ÄŁi",
+      "ìĹIJ ê²Į",
+      "ãĤ¿ ãĥ¼",
+      "Ġ׾ ת",
+      "פ ×ķת",
+      "à¸Ĥ à¸Ń",
+      "ر س",
+      "ìł IJ",
+      "à¸ľ à¹Īาà¸Ļ",
+      "ÑĦ и",
+      "ج ÙĨ",
+      "ì¢ ħ",
+      "Ġ×Ķ פ",
+      "Ġn go",
+      "á»ĭ a",
+      "Ġtá» ķ",
+      "Ġê·¸ 리",
+      "à¹Ģม ืà¹Īà¸Ń",
+      "Ø° Ùĥر",
+      "ìĸ ij",
+      "ìĹ Ń",
+      "×ĺ ׾",
+      "k ı",
+      "Ġع ÙħÙĦ",
+      "Ġع ÙĨد",
+      "à¸ĭ ืà¹īà¸Ń",
+      "Ġê± °",
+      "в е",
+      "r ü",
+      "à¹Ģ à¸Ńา",
+      "ส à¹Į",
+      "à¸Ī à¸Ļ",
+      "ס ת",
+      "Ġgi ả",
+      "ãĤĭ ãģ¨",
+      "à¸ģำ ลัà¸ĩ",
+      "н ей",
+      "à¸Ī ริ",
+      "à¸Īริ à¸ĩ",
+      "Ġë į",
+      "Ġëį Ķ",
+      "à¸Ħà¹Ī ะ",
+      "ì n",
+      "Ġsü re",
+      "Ġqu y",
+      "à¸ļ าà¸ĩ",
+      "åıĸ ãĤĬ",
+      "ר ×Ĺ",
+      "×ij ת",
+      "ãģĮ ãģĤãĤĬãģ¾ãģĻ",
+      "ר ש",
+      "ìĹIJ ëĬĶ",
+      "Ġ×IJ פשר",
+      "ay ı",
+      "ãģĮ ãĤī",
+      "ØŃ Ø¨",
+      "ан Ñģ",
+      "س ÙĪ",
+      "ĠпÑĢ е",
+      "د ÙĪ",
+      "ãģ« ãĤĪ",
+      "à¹Ģà¸ģ ม",
+      "สู à¸ĩ",
+      "m akt",
+      "makt ad",
+      "maktad ır",
+      "Ġön em",
+      "×Ļ×ŀ ×Ļ×Ŀ",
+      "б о",
+      "ÙĪ ÙĬØ©",
+      "รู à¸Ľ",
+      "à¹Ĥล à¸ģ",
+      "Ùħ ÙĬع",
+      "ÑģÑĤ Ñĥп",
+      "à¹Ĥ à¸Ń",
+      "دÙĬ ÙĨ",
+      "ì¤ ij",
+      "ãģĹãģ ı",
+      "à¹Ģส ีย",
+      "в Ñĭ",
+      "Ùħ ت",
+      "íĺ Ħ",
+      "ãĥIJ ãĥ¼",
+      "ا ش",
+      "ק ס",
+      "Ġtá» ¥",
+      "ล à¸Ķ",
+      "Ùģ Ø©",
+      "í ijľ",
+      "ر ج",
+      "k ÅĤad",
+      "ĠÅŁ ey",
+      "ĠØ£ Ùħ",
+      "Ġà¹Ģ ม",
+      "Ġب ÙĦ",
+      "Ñģ каÑı",
+      "ãģ¨ ãģ®",
+      "Ġìĭ ¤",
+      "ấ m",
+      "ห à¹īà¸Ńà¸ĩ",
+      "à¸Ĭ ม",
+      "d ü",
+      "Ġç ek",
+      "Ġê³ ł",
+      "×Ĵ ×ij",
+      "à¸Ĭี วิ",
+      "à¸Ĭีวิ à¸ķ",
+      "Ùģض ÙĦ",
+      "ภ¯",
+      "ç ı",
+      "Ġب Ø´",
+      "ĠÙĩ ÙĨا",
+      "ãģį ãģ¾ãģĹãģŁ",
+      "t ü",
+      "Ġìĺ ģ",
+      "ĠTür k",
+      "к ÑĤ",
+      "פר ס",
+      "ãģ¨ãģĦãģĨ ãģĵãģ¨",
+      "í ĶĦ",
+      "à¹ģร à¸ģ",
+      "ר ×ķף",
+      "Ġar as",
+      "×ŀצ ×IJ",
+      "Ġtá» ī",
+      "س ا",
+      "à¸ŀ à¸Ń",
+      "ĠاÙĦÙħ ØŃ",
+      "ãĥ ¤",
+      "ĠاÙĦ است",
+      "Ùģ ÙĨ",
+      "×Ļ×ŀ ×Ķ",
+      "ر ت",
+      "ãģ¨ ãĤĤ",
+      "Ġна Ñģ",
+      "п ÑĢи",
+      "Ġ×Ĺ ×ķ",
+      "и ла",
+      "ÙĬ Ø´",
+      "Ġgö z",
+      "Ġ×ij ׳×Ļ",
+      "ım ı",
+      "ĠÑĤ еÑħ",
+      "Ġh á»Ļ",
+      "غ ر",
+      "к он",
+      "اØŃ Øª",
+      "Ġ à¸ŀ",
+      "à¸Ń à¸Ńà¸Ļ",
+      "à¸Ńà¸Ńà¸Ļ à¹Ħล",
+      "à¸Ńà¸Ńà¸Ļà¹Ħล à¸Ļà¹Į",
+      "Ñħ о",
+      "Ñı в",
+      "à¹ģ สà¸Ķ",
+      "à¹ģสà¸Ķ à¸ĩ",
+      "à¹Ģà¸ŀ ียà¸ĩ",
+      "ÑĤ ов",
+      "ا ÙĬ",
+      "Ġ×Ķ ×ĵ",
+      "Ġ×ķ ׼",
+      "ãĤī ãģĦ",
+      "×ķפ ף",
+      "Ġë ¶Ī",
+      "ล à¸Ńà¸ĩ",
+      "Ø· اÙĦ",
+      "Ġн и",
+      "ĠÙħ ست",
+      "ế c",
+      "Ġש ׼",
+      "ĠëķĮ 문",
+      "วัà¸Ļ à¸Ĺีà¹Ī",
+      "×Ļ׾ ×ĵ",
+      "ØŃ Ø§",
+      "е ÑĨ",
+      "Ġc ứ",
+      "×ĵ ×ķר",
+      "ĠÙħ ØŃ",
+      "ר׼ ×ij",
+      "بÙĬ ع",
+      "ни и",
+      "ĠاÙĦØ£ ÙĪÙĦ",
+      "à¸Ħว ร",
+      "ãģ¨æĢĿ ãģĨ",
+      "ĠС о",
+      "ائ ÙĬØ©",
+      "ر اء",
+      "оÑģ об",
+      "Ġب Ø£ÙĨ",
+      "×¢ ×ķ×ĵ",
+      "ĠÑĤ е",
+      "ãģĵ ãģĨ",
+      "ÑģÑĤ ÑĢа",
+      "ай н",
+      "Ġsö z",
+      "ت ÙĨا",
+      "à¸Ń ิ",
+      "ặ p",
+      "ĠìķĦ ëĭĪ",
+      "íķ Ń",
+      "Ġר×IJ ש",
+      "Ġ à¹Ħà¸Ķà¹ī",
+      "Ġ×Ĵ ×ĵ",
+      "Ġס פר",
+      "обÑī е",
+      "ĠÙĪ Ø¥",
+      "ada ÅŁ",
+      "ãģ¡ ãĤĩ",
+      "ק ×ķ׾",
+      "ÑĢ ез",
+      "ĠdÃ¼ÅŁ ün",
+      "Ġ×ij ×IJ×ŀ",
+      "Ġìĸ´ ëĸ",
+      "ער ×ij",
+      "н ее",
+      "ĠÑģÑĤÑĢ ан",
+      "س اÙĨ",
+      "yn ı",
+      "ĠاÙĦر ئÙĬس",
+      "ãģĹãģ ª",
+      "Ġ׳ ת",
+      "ãģ«ãģª ãģ£ãģŁ",
+      "g ü",
+      "åıĹ ãģij",
+      "׾ ת",
+      "ìł Ī",
+      "ëĬĶ ëį°",
+      "Ø® ÙĬر",
+      "à¸ķà¹īà¸Ńà¸ĩ à¸ģาร",
+      "ĠÙĦ Ø£ÙĨ",
+      "Ġch á»ĭ",
+      "ÙĪ Ø©",
+      "à¹ĥ ส",
+      "ë¶Ģ íĦ°",
+      "íķĺ ë©´",
+      "ữ u",
+      "à¹Ģหม ืà¸Ńà¸Ļ",
+      "б еÑĢ",
+      "ĠìĿ´ ìļ©",
+      "ĠÑģ еб",
+      "wiÄĻ ks",
+      "Ġ׳ ×¢",
+      "ÑĤ ÑĥÑĢ",
+      "Ġngh Ä©",
+      "ש ×ķ×ĺ",
+      "ti ÄŁi",
+      "Ġde ÄŁi",
+      "×IJ ×ij",
+      "Ġ×ŀ ×ŀ",
+      "ãĥĹ ãĥŃ",
+      "wa ÅĤ",
+      "à¸Ī ึà¸ĩ",
+      "Ø® دÙħ",
+      "×IJ ×Ŀ",
+      "Ä±ÅŁ ı",
+      "cz Äħ",
+      "ר ×ĵ",
+      "ĠÑĢ Ñĥб",
+      "خر Ùī",
+      "ãģ® æĸ¹",
+      "Ġд енÑĮ",
+      "×Ĺ ×Ļ×Ŀ",
+      "еÑĤ е",
+      "ëĤ ľ",
+      "×IJ ×Ĵ",
+      "×¢ ×ķר",
+      "ë³ Ħ",
+      "åIJĮ ãģĺ",
+      "ãĤ ²",
+      "ר ×ļ",
+      "×ķש ×IJ",
+      "ìľ ¡",
+      "ا خ",
+      "צ ×Ļ×Ķ",
+      "á»± a",
+      "ãģĪ ãģ¦",
+      "ש×Ķ ×ķ",
+      "ан ÑĤ",
+      "ลา à¸Ķ",
+      "ин г",
+      "ë¡ ł",
+      "اع د",
+      "ÙĪ سط",
+      "Ġв оп",
+      "Ġвоп ÑĢоÑģ",
+      "Ùħ ÙĬÙĨ",
+      "à¸Ħ à¸ĩ",
+      "×Ļר ×Ļ×Ŀ",
+      "c ów",
+      "ê² ©",
+      "Ġê·¸ 룰",
+      "Ġì§ Ħ",
+      "Ġש ׾×Ķ",
+      "à¹Ģร ิà¹Īม",
+      "à¸Ĭ à¸Ńà¸ļ",
+      "д еÑĤ",
+      "ÑİÑī иÑħ",
+      "à¸ļ à¸Ńà¸ģ",
+      "æĢĿ ãģĦ",
+      "ع ÙĬد",
+      "ס ×ŀ",
+      "×Ĵ ×Ļ×¢",
+      "צ ×ĵ",
+      "ب ات",
+      "ĠëĶ° ëĿ¼",
+      "à¸Ī ัà¸ĩ",
+      "ãģłãģij ãģ§",
+      "×¢ ×Ļר",
+      "ĠÑĩ ел",
+      "ĠÑĩел ов",
+      "ĠÑĩелов ек",
+      "ãĥĥ ãĥģ",
+      "à¹Ģà¸ģ ีà¹Īยว",
+      "à¸Ķ ิ",
+      "Ġפ ×¢",
+      "×Ļ×ŀ ×Ļ",
+      "ë° ĺ",
+      "خ ار",
+      "×ij ×Ļת",
+      "×¢ ×Ļ×Ŀ",
+      "ü yor",
+      "ãĤģ ãģ¦",
+      "к лад",
+      "Ġ à¸Īาà¸ģ",
+      "à¹Ģà¸Ħ ย",
+      "ส à¸Ńà¸ĩ",
+      "à¹ģ à¸Ħà¹Ī",
+      "ẫ u",
+      "หà¸Ļ ัà¸ĩ",
+      "ש׾ ×ķ×Ŀ",
+      "اÙĨ ÙĬØ©",
+      "åĩº ä¼ļ",
+      "åĩºä¼ļ ãģĦ",
+      "à¸ł าย",
+      "à¸ļา à¸Ĺ",
+      "à¸Ĭา ว",
+      "mu ÅŁ",
+      "Ġ׾ק ×ij׾",
+      "ãĤ· ãĥ£",
+      "ĠÄ° ÅŁ",
+      "×Ĵ×ĵ ×ķ׾",
+      "ج عÙĦ",
+      "ë³ Ģ",
+      "ยิ à¹Īà¸ĩ",
+      "à¸Ļ าย",
+      "à¸Ļ ีà¹Ī",
+      "วิ à¸ĺี",
+      "ãĤī ãģªãģĦ",
+      "ëł Ī",
+      "Ġ문 ìłľ",
+      "Ġ à¸ģ",
+      "à¸Ĺำ à¸ĩาà¸Ļ",
+      "à¹Ģว à¹ĩà¸ļ",
+      "ÑĦ е",
+      "楽 ãģĹ",
+      "สำ à¸Ħ",
+      "สำà¸Ħ ัà¸į",
+      "ر Ùħ",
+      "ãģķãĤĮ ãģ¦",
+      "Ġоб ла",
+      "ר×IJ ×Ļ",
+      "หม à¸Ķ",
+      "ÙĨ ÙĬØ©",
+      "ли н",
+      "Ġe ÄŁ",
+      "it im",
+      "ëł ¹",
+      "ص اÙĦ",
+      "ÅĽ l",
+      "à¸ľ ิà¸Ķ",
+      "ãĥŀ ãĥ³",
+      "åħ¥ ãĤĮ",
+      "à¹Ģà¸ķ à¸Ńรà¹Į",
+      "ار ÙĬ",
+      "ĠÐ ¦",
+      "d ür",
+      "ส วย",
+      "ë¦ ½",
+      "رÙĥ Ø©",
+      "Ġh ã",
+      "×Ļת ×Ķ",
+      "à¸Ĥ à¸Ļา",
+      "à¸Ĥà¸Ļา à¸Ķ",
+      "à¸Īำ à¸Ļ",
+      "à¸Īำà¸Ļ วà¸Ļ",
+      "ש ×ķק",
+      "Ġд ом",
+      "ì± ħ",
+      "ãģĭ ãģij",
+      "פ ×ķ׾",
+      "à¸Ĭ าย",
+      "Ñģ моÑĤÑĢ",
+      "Ñģл Ñĥж",
+      "ש ×IJ׾",
+      "кÑĢÑĭ ÑĤ",
+      "Ġìŀ ĺ",
+      "é«ĺ ãģĦ",
+      "ĠÑĢ Ñĥк",
+      "ÙĨ ص",
+      "д ав",
+      "Æ°á» ¡",
+      "ưỡ ng",
+      "ر اÙħ",
+      "×Ļ׳ ×Ļ×Ŀ",
+      "ãĥ© ãĥ¼",
+      "ëĦ ¤",
+      "Ġت ع",
+      "l ke",
+      "好 ãģį",
+      "æĮģ ãģ¡",
+      "Ġë§ İ",
+      "Ġy ük",
+      "ĠÑģоÑģÑĤ ав",
+      "енÑĤ ÑĢ",
+      "pe ÅĤ",
+      "à¹Ģà¸Ľà¸¥ ีà¹Īย",
+      "à¹Ģà¸Ľà¸¥à¸µà¹Īย à¸Ļ",
+      "íı ī",
+      "ãĤĦ ãģĻ",
+      "×Ĺ ×ĸ",
+      "×ijר ×Ķ",
+      "ë£ ¨",
+      "ìĶ Ģ",
+      "بØŃ Ø«",
+      "à¹Ģà¸ķ à¹ĩ",
+      "ów i",
+      "ب Ùĩ",
+      "ãģį ãģ¾ãģĻ",
+      "Ġ×¢ ×ŀ",
+      "×Ĵ ×ķ׾",
+      "ез д",
+      "ÙĬÙģ Ø©",
+      "สà¸Ļ à¹ĥà¸Ī",
+      "Ġת ׾",
+      "Ñı Ñī",
+      "Ġس ÙĨ",
+      "ĠÙĪا ØŃد",
+      "ĠÑģ м",
+      "lad ı",
+      "ı ld",
+      "×Ļר ת",
+      "ีย à¸Ļ",
+      "ת×Ĺ ×ª",
+      "Ġж из",
+      "à¸ŀ ั",
+      "à¸ŀั à¸Ĵ",
+      "à¸ŀัà¸Ĵ à¸Ļา",
+      "à¸Ĭ ิ",
+      "ا Ø®ÙĦ",
+      "ãģ£ãģ¦ ãģĦãģŁ",
+      "รั à¸IJ",
+      "ãĤģ ãĤĭ",
+      "à¹Ĥ à¸ģ",
+      "ĠT á»ķ",
+      "Ġh akk",
+      "ر Ùģ",
+      "ìł Ģ",
+      "Ñģ об",
+      "ãģª ãģijãĤĮãģ°",
+      "Ùĩ ÙĪ",
+      "Ġë² ķ",
+      "ãĤ Ĩ",
+      "ĠاÙĦس عÙĪد",
+      "Ġ×IJ תר",
+      "Ø§Ø º",
+      "Ġ׾ ×ĵ",
+      "à¹ģ à¸ķ",
+      "à¹ģà¸ķ à¹Īà¸ĩ",
+      "íĮ Į",
+      "Ñĥп иÑĤÑĮ",
+      "à¸ŀืà¹īà¸Ļ à¸Ĺีà¹Ī",
+      "×ij ת×Ļ",
+      "à¹ĩ à¸ģ",
+      "ÅĤ at",
+      "Ġê°ľ ìĿ¸",
+      "ìłķ ë³´",
+      "ÑĤ ал",
+      "Ġgü ven",
+      "ĠÄ° l",
+      "Ġê° ģ",
+      "Ġب ت",
+      "×ŀ ×ķ׳×Ķ",
+      "ĠاÙĦØŃ ÙĥÙĪÙħ",
+      "ÙĤ ات",
+      "à¹ģ à¸ģà¹Ī",
+      "ห าà¸ģ",
+      "н ÑĮ",
+      "à¸Ľ รัà¸ļ",
+      "มา à¸ĵ",
+      "Ġне Ñģк",
+      "ĠØ ¶",
+      "สม ั",
+      "สมั à¸Ħร",
+      "ãģĮ ãģĤãĤĬ",
+      "м еÑģÑĤ",
+      "Ġ×IJ צ׾",
+      "Ġкомп ани",
+      "ס ר",
+      "ÙĬÙħ Ø©",
+      "ĠÑħ оÑĢо",
+      "ĠÑħоÑĢо ÑĪ",
+      "Ġ×Ļ ×ķ×ĵ",
+      "ü s",
+      "×Ĵ ×Ļש",
+      "à¸ļ à¸Ĺ",
+      "تÙĨ ظ",
+      "ว าà¸ĩ",
+      "ม หา",
+      "Ġ׼ ×ķ׾",
+      "à¸Ĥ à¹īาà¸ĩ",
+      "ë° ľ",
+      "г од",
+      "д ан",
+      "ãģĭãĤĤãģĹãĤĮ ãģ¾ãģĽãĤĵ",
+      "ãģĵ ãģ¡ãĤī",
+      "ãĥIJ ãĤ¤",
+      "ece ÄŁi",
+      "دÙĬ دة",
+      "ÙĨ Ùī",
+      "Ġëĭ¤ ìĿĮ",
+      "ว ี",
+      "غ ا",
+      "ли з",
+      "à¹Ģà¸Ķ ิ",
+      "à¹Ģà¸Ķิ ม",
+      "ĠÙĬ ست",
+      "Ġy ılı",
+      "ko ÅĦ",
+      "ãģ§ãģĹãĤĩãģĨ ãģĭ",
+      "ãģĤ ãģª",
+      "ãģĤãģª ãģŁ",
+      "ÑĨ ен",
+      "ĠÙĪ ز",
+      "×IJ ×Ļש",
+      "à¹Ī à¸Ń",
+      "ر ØŃ",
+      "ê´ ij",
+      "ÑĢа ÑģÑĤ",
+      "Ġ×Ķ ׾",
+      "ãģĹãģ¦ ãĤĤ",
+      "×ŀר ׼",
+      "×ŀר׼ ×ĸ",
+      "éģķ ãģĦ",
+      "ãģŁ ãģı",
+      "ĠÑģ Ñĥд",
+      "в еÑģÑĤи",
+      "ĠíķĦ ìļĶ",
+      "ãĥķ ãĤ§",
+      "ÑĤелÑĮ но",
+      "à¹Ģà¸ŀ ืà¹Īà¸Ńà¸Ļ",
+      "ÅĤu ż",
+      "à¹Ģà¸Ķิà¸Ļ à¸Ĺาà¸ĩ",
+      "ש ×ķר",
+      "Ġ×ŀ ×ĵ",
+      "×ķ×¢ ׾",
+      "ÙĦ اÙħ",
+      "à¹Ħ à¸ĭ",
+      "л ей",
+      "кÑĥ ÑĢ",
+      "Ạ¢",
+      "à¸Ĺ าà¸Ļ",
+      "ì§ ij",
+      "ĠгоÑĢ од",
+      "ר ס",
+      "׾ ×ķ×Ĵ",
+      "mas ını",
+      "Ġл ÑĥÑĩ",
+      "ล à¹Īา",
+      "ìļ ¸",
+      "ש ×ĺ",
+      "ĠÐĺ н",
+      "í Ĥ¤",
+      "ÙĪÙĦ ا",
+      "ìķ ł",
+      "ĠØ£ÙĬ ضا",
+      "Ùĥ ار",
+      "ĠاÙĦت ع",
+      "ส ูà¹Ī",
+      "ãĤ ¼",
+      "×ij ×Ļ×IJ",
+      "ย à¸ģ",
+      "ĠØŃ ÙĤ",
+      "ر بÙĬ",
+      "ãģĺãĤĥ ãģªãģĦ",
+      "รัà¸ģ ษา",
+      "Ñħод иÑĤ",
+      "à¸ķ à¸Ńà¸ļ",
+      "׳ ×ĺ×Ļ",
+      "ĠاÙĦÙħ ج",
+      "تÙħ ع",
+      "ов аÑĤÑĮ",
+      "ÙĦ ÙĬÙĨ",
+      "×Ļ×ŀ ×ķת",
+      "Ġm ù",
+      "n ÄĻ",
+      "Ġد ÙĬ",
+      "׼ ש×Ļ×ķ",
+      "Ġhi ç",
+      "ë ijIJ",
+      "ÙĪ اء",
+      "ÙĪ Ø·",
+      "ĠاÙĦ بÙĦ",
+      "à¹ģม à¹ī",
+      "ק ×ķת",
+      "ÙĪج د",
+      "å§ĭ ãĤģ",
+      "ÙĬ ئة",
+      "Ġë§ ¤",
+      "ص بØŃ",
+      "פ ×IJ",
+      "г оÑĢ",
+      "ס ×Ķ",
+      "بÙĬ ÙĤ",
+      "ย าà¸ģ",
+      "Ġн ад",
+      "ÙĬ Ùij",
+      "Ġب ÙĪ",
+      "ס ×ķר",
+      "Ùħ ÙĥاÙĨ",
+      "ר ×ij",
+      "×Ĵ ×ĸ",
+      "צ ת",
+      "b ilit",
+      "л аг",
+      "ĠN go",
+      "×IJ ×ķר",
+      "à¸ķ à¸Ļ",
+      "íĬ ¹",
+      "à¸Ĺีà¹Ī à¸Ķี",
+      "à¸Ľà¸£à¸° à¸Īำ",
+      "ов ание",
+      "ãģĦ ãģ¤",
+      "ãĥĥãĤ¯ ãĤ¹",
+      "åIJĪ ãĤı",
+      "åIJĪãĤı ãģĽ",
+      "×Ļ׳ ×ķ×Ļ",
+      "ạ y",
+      "Ø« ÙĤ",
+      "ĠпÑĢ об",
+      "ĠпÑĢоб лем",
+      "ÅŁ eh",
+      "ÅŁeh ir",
+      "ع ادة",
+      "اÙĨ ÙĪÙĨ",
+      "à¸ķัว à¹Ģà¸Ńà¸ĩ",
+      "ì¶ ķ",
+      "ı lan",
+      "б ан",
+      "ãĥ³ ãĥī",
+      "à¸Ī ี",
+      "Ġ×Ķש ׳×Ļ",
+      "п оÑĤ",
+      "×ķ׾ ×Ļ×Ŀ",
+      "ล ัà¸ļ",
+      "ĠÑį ÑĤи",
+      "×ijק ש",
+      "ë¹Ħ ìĬ¤",
+      "à¸Ńยà¹Īาà¸ĩ à¹Ħร",
+      "×Ļ׾ ×Ļ",
+      "à¹ĥà¸Ĭ à¹Ī",
+      "ĠاÙĦ ÙĥÙĦ",
+      "ãĥļ ãĥ¼ãĤ¸",
+      "ص ة",
+      "ÑĤи ÑĢ",
+      "ãĤĵ ãģ©",
+      "зÑĭ к",
+      "wy ż",
+      "Ùĩ ÙĬ",
+      "ĠÙħ ÙĦÙĬ",
+      "Ġвид е",
+      "ظ اÙħ",
+      "دا ÙĪÙĦ",
+      "×ŀ ת×Ļ",
+      "Ġs ık",
+      "à¹Ģà¸ķิ ม",
+      "ãĤ¢ ãĤ¤",
+      "ка Ñħ",
+      "צ ×Ļ׾",
+      "à¹Ģà¸Ĭ à¹Īà¸Ļ",
+      "м аг",
+      "маг аз",
+      "магаз ин",
+      "à¸Ľ ั",
+      "à¸Ľà¸± à¸Ī",
+      "Ġש ×Ļר×ķת",
+      "ีย ม",
+      "ãĥĸ ãĥ«",
+      "Ġد ÙĪÙĦ",
+      "קר ×Ļ×Ŀ",
+      "Ùĩ Ùı",
+      "ов о",
+      "Ġü ret",
+      "د ÙĪÙĨ",
+      "à¹ģà¸Ļ ว",
+      "à¹Ģà¸Ļ ืà¹īà¸Ń",
+      "ĠÑĦ оÑĤ",
+      "ãĥ ĺ",
+      "ãģ¤ ãģĭ",
+      "Ñı Ñģ",
+      "ĠíķĺëĤĺ ëĭĺ",
+      "ائ ع",
+      "Ġп лаÑĤ",
+      "ìĺ Ī",
+      "Ġdost ÄĻp",
+      "ÙĪج Ùĩ",
+      "Ġ×Ķ ×Ĺ×Ļ",
+      "׳ ×Ļק",
+      "д ей",
+      "í ĽĦ",
+      "ı y",
+      "بØŃ Ø±",
+      "à¹Ģส ริม",
+      "Ġ׾ ×Ĵ",
+      "Ø°Ùĩ ب",
+      "ج ÙĬÙĦ",
+      "رÙĥ ز",
+      "Ġë ħ",
+      "Ġëħ ¸",
+      "פ×Ļ׾ ×ķ",
+      "ãģ¾ ãģļ",
+      "iri ÅŁ",
+      "ĠÙĥ ÙĬÙģ",
+      "Ġ×ij צ",
+      "Ġêµ IJ",
+      "ÑĢоÑģ Ñģ",
+      "ĠØ´ ÙĬ",
+      "Ġiç er",
+      "×Ĵ ×ķ×ij×Ķ",
+      "мен но",
+      "×¢ ×ij×Ļר",
+      "×ķ×ŀ ×Ķ",
+      "ãĤī ãģĹãģĦ",
+      "ãģ ¼",
+      "Ñī ин",
+      "è²· ãģĦ",
+      "جÙħÙĪع Ø©",
+      "Ġdön em",
+      "Ġ×ij ×IJר",
+      "в еÑģÑĤ",
+      "×ķר ×ķת",
+      "س Ùģ",
+      "à¹ģà¸Ĺ à¸Ļ",
+      "Ġд окÑĥменÑĤ",
+      "Ġا ÙĬ",
+      "ج اÙĨ",
+      "צ×ķ×¢ ×Ļ",
+      "ĠоÑģ об",
+      "ĠاÙĦÙħ س",
+      "ÑĢаР±",
+      "à¸ł ู",
+      "à¸Ķ าว",
+      "л екÑĤ",
+      "ع ÙĤ",
+      "×ķ×ĵ ×ķת",
+      "Ġol u",
+      "Ġolu ÅŁtur",
+      "ãģ¾ ãģ¾",
+      "ед ин",
+      "à¹Ģ à¸Ńà¸ģ",
+      "ãĤµ ãĤ¤",
+      "ëĦ Ī",
+      "Ø· ÙĨÙĬ",
+      "Ø· ÙĤØ©",
+      "ĠÐł аз",
+      "ÙĦ Ùij",
+      "Ñĩ ем",
+      "Ġ׾ ×ĺ",
+      "สั à¹Īà¸ĩ",
+      "سر ائÙĬÙĦ",
+      "Ġפר ×ĺ×Ļ",
+      "д еÑģÑĮ",
+      "Ġ׳ ׼",
+      "اÙĨ ب",
+      "ÙĬا Ø©",
+      "Ùħ بر",
+      "Ġk ı",
+      "à¸Ľ à¸ı",
+      "à¸Ľà¸ı ิ",
+      "à¸ļั à¸ķิ",
+      "׳ ת×Ļ",
+      "ìĨ ¡",
+      "ر اب",
+      "à¹ĥ à¸ķ",
+      "à¹ĥà¸ķ à¹ī",
+      "×Ļ׳ ת",
+      "ÙĪ ÙĬر",
+      "Ġ×Ķ×ŀ ×Ļ",
+      "ей ÑĩаÑģ",
+      "ק ×ķ×ij",
+      "در اس",
+      "ĠÙħ ÙĤ",
+      "رÙĬ ÙĨ",
+      "خ اص",
+      "ãģĬ éĩij",
+      "Ġج دا",
+      "ãģĨ ãģ¡",
+      "ëħ ¸",
+      "ır ım",
+      "æ§ ĺ",
+      "ãģ« å¯",
+      "ãģ«å¯ ¾",
+      "ÑĨ ев",
+      "Ġv ard",
+      "ĠÐIJ н",
+      "e ÄŁ",
+      "ÑģÑĤв енно",
+      "Ð ¨",
+      "س د",
+      "à¸ģ ุ",
+      "à¹ģà¸ľ à¸Ļ",
+      "รูà¹ī ส",
+      "รูà¹īส ึà¸ģ",
+      "ات ØŃاد",
+      "Ñij ÑĤ",
+      "×Ĺ ×ķק",
+      "ãģĻ ãģIJ",
+      "Ø· ÙĦاÙĤ",
+      "Ġק ×ķ×ĵ",
+      "à¹ĥà¸Ĭ à¹īà¸ĩ",
+      "à¹ĥà¸Ĭà¹īà¸ĩ าà¸Ļ",
+      "ãĥ¼ãĤ ¿",
+      "Ġs ür",
+      "ÑĢ ок",
+      "ë³ ij",
+      "สมา à¸Ĭ",
+      "สมาà¸Ĭ ิà¸ģ",
+      "ãĥķ ãĥ¬",
+      "è¾¼ ãģ¿",
+      "ãĤ» ãĥ³",
+      "Ġê°Ģ ì§Ģ",
+      "à¸ľ à¹īา",
+      "ÑįÑĤ омÑĥ",
+      "иÑĤ ел",
+      "à¸ł ั",
+      "ภij",
+      "ãĥĸ ãĥ©",
+      "×Ľ×ª ×ķ×ij",
+      "׳ ×Ŀ",
+      "ен нÑĭе",
+      "×¢ ×¨×Ľ×ª",
+      "Ġì Ĥ",
+      "ĠìĤ ´",
+      "à¸Ĥ à¹īา",
+      "׳ ×ķס",
+      "ãĥ¬ ãĥĵ",
+      "ÑĢ еÑģ",
+      "à¹Ģล à¸Ĥ",
+      "Ø« اÙĦ",
+      "ìĹ Ĩ",
+      "ĠÑĩ аÑģÑĤ",
+      "า ศ",
+      "ãĥª ãĤ¢",
+      "u ç",
+      "×Ļ׼ ×ķת",
+      "ล à¹īาà¸Ļ",
+      "i ë",
+      "ãĤ¸ ãĤ§",
+      "à¸Ī à¸Ń",
+      "ÙĪ ØŃد",
+      "×Ļצ ×ķ×ij",
+      "Ġ×ij ש׾",
+      "ок о",
+      "ض ة",
+      "ذ ر",
+      "ĠÑĥ д",
+      "Ä° L",
+      "×ķצ ×Ļ×Ŀ",
+      "×ĸ ×ŀף",
+      "à¸Ľ à¸ģ",
+      "íķĻ êµIJ",
+      "س اÙħ",
+      "à¹Ħ à¸Ķ",
+      "ละ à¹Ģà¸Ń",
+      "ละà¹Ģà¸Ń ีย",
+      "ละà¹Ģà¸Ńีย à¸Ķ",
+      "ả y",
+      "аÑĨи он",
+      "ãĤ¹ ãĤ¯",
+      "פ ×ķס",
+      "ร à¹Īาà¸ĩ",
+      "ен нÑĭй",
+      "ع ÙĨ",
+      "عÙĦ ÙĨ",
+      "ائ Ùģ",
+      "d ÄĻ",
+      "ؤ ÙĪÙĦ",
+      "׾×ķ ×ķ",
+      "Ġ×ij ש×ij",
+      "ä»Ĭ åĽŀ",
+      "ĠاÙĦج ÙĨ",
+      "د اد",
+      "wa Äĩ",
+      "ãĥª ãĥ³",
+      "ĠìŀIJ ìĭł",
+      "اÙĨ ÙĬا",
+      "ãĥ¡ ãĥª",
+      "ÙĦ ÙĪÙĨ",
+      "à¸Ĺ à¹Īà¸Ńà¸ĩ",
+      "à¸Ĺà¹Īà¸Ńà¸ĩ à¹Ģà¸Ĺีà¹Īยว",
+      "اÙģ ÙĬ",
+      "Ġли ÑĪ",
+      "Ùħ ÙĬØ©",
+      "оÑĤ веÑĤ",
+      "Ñĩ ин",
+      "Ã Ĭ",
+      "ãĥ¡ ãĥ³",
+      "å® Ł",
+      "éļĽ ãģ«",
+      "ĠÑĢаР¹",
+      "ãĤ¦ ãĥ³",
+      "×Ļר ×ķש",
+      "×Ļר×ķש ׾×Ļ×Ŀ",
+      "ม ะ",
+      "Ġar a",
+      "каз аÑĤÑĮ",
+      "à¸ķ ัà¸Ķ",
+      "ÑĥÑİ ÑĤ",
+      "Ġü st",
+      "×Ĵ ×ķ×ij",
+      "×Ĵ×ķ×ij ×ķת",
+      "mal ı",
+      "ег од",
+      "егод нÑı",
+      "اÙģ ÙĤ",
+      "à¸Ĭ à¹Īà¸Ńà¸ĩ",
+      "Ġö zellik",
+      "×Ļצ ×ķר",
+      "Ġmi ÄĻd",
+      "Ġili ÅŁ",
+      "Ġна Ñħод",
+      "×¢ ×ĸר",
+      "׾ ×Ľ×ª",
+      "ÙĨت اج",
+      "ĠÑģ ем",
+      "à¸Ī à¹Īาย",
+      "à¸ķร ว",
+      "à¸ķรว à¸Ī",
+      "פר ×ķ",
+      "à¸Ĥ ัà¸ļ",
+      "ãģ ŀ",
+      "Ġп ло",
+      "к олÑĮ",
+      "×ŀ×¢ ×ĺ",
+      "íķĺ ìĭľ",
+      "jÄħ ce",
+      "ÙĨ اÙĨ",
+      "ลี à¸ģ",
+      "н ÑĥÑĤ",
+      "Ġоб ÑĢаз",
+      "Ùĥ بر",
+      "ĠاÙĦÙĪ Ø·ÙĨ",
+      "ãģķãģĽ ãģ¦",
+      "ÙĤ اء",
+      "×ŀ×ĵ ×Ļ׳",
+      "y ü",
+      "פ ×Ļת",
+      "׳ ×ķף",
+      "ÙħÙĨ ظ",
+      "หà¸Ļ ัà¸ģ",
+      "ìŀ Ī",
+      "ãĤ« ãĥ¼ãĥī",
+      "ع ÙĨÙĬ",
+      "п од",
+      "ض اء",
+      "à¸Ļ à¸ķà¹Į",
+      "×ŀש פ",
+      "ว à¹Į",
+      "ר ×ķק",
+      "ส ืà¹Īà¸Ń",
+      "פק ×Ļ×ĵ",
+      "ãģªãĤī ãģªãģĦ",
+      "ĠìŬ 룬",
+      "ÙĦ ج",
+      "Ñī иÑĤ",
+      "ãĥĥ ãĤ·",
+      "ÙĦÙĬ س",
+      "ĠÙĦ Ùħا",
+      "ìł ij",
+      "×ij ×Ļף",
+      "ãĥģ ãĤ§",
+      "Ġgü ç",
+      "Ġch ứ",
+      "×ķצ ×IJ",
+      "קר ×ij",
+      "à¹Ĥ à¸ŀ",
+      "оÑĩ но",
+      "סק ×Ļ",
+      "ש׾ ×Ŀ",
+      "صر Ùģ",
+      "ĠL Ãł",
+      "×¢ ×Ļת",
+      "á» ·",
+      "à¹Ĥ à¸Ńà¸ģ",
+      "à¹Ĥà¸Ńà¸ģ า",
+      "à¹Ĥà¸Ńà¸ģา ส",
+      "Ġ×Ķ ×ĵ×ijר",
+      "à¸Ļั à¹Īà¸Ļ",
+      "ز ر",
+      "нак о",
+      "íļ į",
+      "ãĤĤ ãģ¡",
+      "ãĤĤãģ¡ ãĤį",
+      "ãĤĤãģ¡ãĤį ãĤĵ",
+      "اÙħ ت",
+      "عد اد",
+      "и нÑĭ",
+      "ÅĤy w",
+      "à¸Ħ à¸ĵะ",
+      "à¸Ĺ ะ",
+      "kt ör",
+      "×Ļ×Ĺ ×Ķ",
+      "Ġм е",
+      "Ġме ÑģÑı",
+      "׳×Ķ ×Ĵ",
+      "ĠÑģ ÑĥÑīеÑģÑĤв",
+      "à¸Ļ ัà¸Ļ",
+      "ÑĦ ÑĦ",
+      "ек ÑĤив",
+      "عÙĦÙĪÙħ ات",
+      "б Ñĥд",
+      "à¸Ļัà¸ģ à¸ĩาà¸Ļ",
+      "หà¸Ļà¹īา à¸Ĺีà¹Ī",
+      "ÙĤÙĬ ÙĤ",
+      "ãĤ· ãĥ³",
+      "ãģ« éĸ¢",
+      "×IJר ×Ĵ",
+      "ĠпÑĢ оÑĤ",
+      "ĠпÑĢоÑĤ ив",
+      "ĠìŀĪ ìĸ´",
+      "ÙĤÙĬ ÙĤØ©",
+      "ìĹ ĩ",
+      "k ür",
+      "ãģ«ãģªãĤĬ ãģ¾ãģĹãģŁ",
+      "Ġде ÑıÑĤ",
+      "ĠдеÑıÑĤ елÑĮ",
+      "פ×ķר ×ĺ",
+      "à¸Ł à¹īา",
+      "à¹Ģ à¸ł",
+      "ĠавÑĤом аÑĤ",
+      "×ĸ ×Ļק",
+      "Ġold uk",
+      "ع اÙħ",
+      "ĠÑĤ оÑĢ",
+      "yrı ca",
+      "ê Ì",
+      "ãĤŃ ãĥ³ãĤ°",
+      "ãģ« ãģ¨ãģ£ãģ¦",
+      "à¹Ģà¸ī à¸ŀ",
+      "à¹Ģà¸īà¸ŀ าะ",
+      "ãģ¯ ãģļ",
+      "×ŀ ×IJ×Ļ",
+      "สะ à¸Ķ",
+      "สะà¸Ķ วà¸ģ",
+      "ìľ¼ ë©°",
+      "à¸ģ ี",
+      "ภ¬",
+      "Ġ×¢ ×ķש",
+      "à¸łà¸² ษา",
+      "à¸Ĺ ัà¸Ļ",
+      "ac akt",
+      "acakt ır",
+      "اع دة",
+      "ĠÑĥÑģл Ñĥг",
+      "ס ר×ĺ",
+      "×ķ×ŀ ×ķת",
+      "×Ķ ×ķר",
+      "×ŀ ×ķ×ij",
+      "×ŀ×ķ×ij ף",
+      "سÙĬ اس",
+      "اتÙģ اÙĤ",
+      "×Ķ צ׾",
+      "Ùħؤ س",
+      "Ġp ó",
+      "Ġк ни",
+      "×Ļ׼ ×ķ׾",
+      "à¹Ģหล ืà¸Ń",
+      "׼׾ ׼",
+      "׳ ×ĸ",
+      "ÑĪи е",
+      "r ès",
+      "ĠاÙĦØŃ ÙĤ",
+      "лÑı ÑĢ",
+      "ห à¸į",
+      "หà¸į ิà¸ĩ",
+      "ר×Ĵ ×Ļש",
+      "à¹Ģส à¹īà¸Ļ",
+      "ש×ij ×ķף",
+      "ô tel",
+      "ап ÑĢ",
+      "апÑĢ имеÑĢ",
+      "اب ÙĦ",
+      "ĠÑĢаз виÑĤ",
+      "Ġп олÑĮз",
+      "ĠС еÑĢ",
+      "×ķ×ij ×Ļ",
+      "r óż",
+      "ìĭ Ń",
+      "ãĤ¯ ãĥĪ",
+      "ãģĹ ãĤĪãģĨ",
+      "à¸ģร ม",
+      "ØŃ ÙĥÙĪÙħ",
+      "à¹Ĥ à¸ļ",
+      "à¸Ĺ à¹īาย",
+      "ĠM á",
+      "ĠÑĤ Ñĭ",
+      "à¸Ħร ัว",
+      "ÑĢÑĥ б",
+      "ạ p",
+      "Ġm ÅĤ",
+      "ĠmÅĤ od",
+      "Ġgör Ã¼ÅŁ",
+      "Ġgeli ÅŁ",
+      "Æ°Æ¡ i",
+      "×ŀש ק",
+      "ÙĢÙĢ ÙĢÙĢ",
+      "รา ว",
+      "ãģĹãģ £",
+      "ãģĹãģ£ ãģĭãĤĬ",
+      "ĠÐļ он",
+      "Ġk ê",
+      "à¹Ĥà¸Ĺ ร",
+      "èIJ½ ãģ¡",
+      "åĩº ãģ¦",
+      "ล ัà¸ģษ",
+      "Ġ×Ĵ ×ij×ķ×Ķ",
+      "ãĥĻ ãĥ«",
+      "ê±° ëĤĺ",
+      "ë§ IJ",
+      "×Ļ׾ ×ĵ×Ļ×Ŀ",
+      "ĠëĦ Ī",
+      "×ŀר ×Ļ",
+      "ร ส",
+      "ãĥŃ ãĥ³",
+      "и ло",
+      "ноÑģÑĤÑĮ Ñİ",
+      "×ĸר ×Ĺ",
+      "п он",
+      "Ġ×Ķש ׾",
+      "ê²ł ìĬµëĭĪëĭ¤",
+      "Ġki ÅŁ",
+      "ĠÐļ и",
+      "ว ร",
+      "د اع",
+      "ÅŁ im",
+      "ÙĨ Ùij",
+      "в аÑĤ",
+      "را Ùĥ",
+      "ب اÙĦ",
+      "ид е",
+      "Ġ×Ķ×ŀ ×Ĺ",
+      "ìĸ µ",
+      "تÙģ اع",
+      "أ ت",
+      "ëĬ ĺ",
+      "ש ×Ļת",
+      "ست Ùħر",
+      "ĠÑĦ ак",
+      "ĠاÙĦØ£Ùħ رÙĬ",
+      "ëŀ ¨",
+      "اس Ùħ",
+      "Ġa ÄŁ",
+      "Ġç ev",
+      "Ùĥ ÙĪر",
+      "ãģķ ãģ¾",
+      "Ġç öz",
+      "Ġر س",
+      "Äħ da",
+      "สà¸Ļ ุ",
+      "ãģĹãģ¦ ãģıãĤĮ",
+      "н Ñİ",
+      "leÅŁ me",
+      "ãĤª ãĥ³",
+      "ãģ¨ ãģªãĤĬ",
+      "ava ÅŁ",
+      "×ĺ ×Ļ×ij",
+      "ØŃ Ø¶",
+      "×ķצ ×IJ×ķת",
+      "ÙĨ ÙħÙĪ",
+      "ı t",
+      "ĠÑħ а",
+      "ĠÑħа ÑĢак",
+      "ĠÑħаÑĢак ÑĤеÑĢ",
+      "Ġd ÅĤ",
+      "ãĥĹ ãĥ©",
+      "à¸Ĭ ุม",
+      "à¹Ī à¸Ńà¸Ļ",
+      "×ķ×ij ׾",
+      "Ñģ ол",
+      "×ĵ ×Ĵ",
+      "аÑĢ аÑĤ",
+      "n ivers",
+      "Ġgerçek leÅŁtir",
+      "ĠاÙĦ ÙĦÙĬ",
+      "ระ ยะ",
+      "ĠÙħ ختÙĦÙģ",
+      "Ġgö nder",
+      "Ùģ ار",
+      "do ÄŁ",
+      "doÄŁ an",
+      "ص ÙĦاØŃ",
+      "Ġyay ın",
+      "ãĥĨ ãĥ³",
+      "รว à¸Ī",
+      "×Ļ×Ĺ ×Ļ×ĵ",
+      "ünk ü",
+      "ÑĨи алÑĮн",
+      "à¸ļ ู",
+      "ม ุ",
+      "h ä",
+      "Ø® Ùģ",
+      "å¢ Ĺ",
+      "å¢Ĺ ãģĪ",
+      "еÑĩ но",
+      "ĠاÙĦس ÙĨ",
+      "à¸Ĥ าว",
+      "im di",
+      "Ð «",
+      "à¸Ļà¸Ńà¸ģ à¸Īาà¸ģ",
+      "à¸ļา ล",
+      "ת ש",
+      "Ġdüzen le",
+      "мÑĭ Ñģл",
+      "ãģı ãģª",
+      "ż u",
+      "Ġwsp óÅĤ",
+      "Ġн аз",
+      "ınd aki",
+      "تر ة",
+      "ÅŁ ek",
+      "Ġö d",
+      "ĠÙĪ Ùĥ",
+      "Ġпозв олÑı",
+      "Ġת ×ķ׼",
+      "ÙħÙĨ تج",
+      "ë§ ī",
+      "ĠاÙĦØ« ÙĦاث",
+      "аÑĨи Ñİ",
+      "ÙĪر ÙĪ",
+      "Ñĭв аеÑĤ",
+      "خص ص",
+      "ĠاÙĦÙģ ÙĦ",
+      "ĠاÙĦÙģÙĦ سطÙĬÙĨ",
+      "إ جر",
+      "إجر اء",
+      "اÙĨت Ø®",
+      "اÙĨتخ اب",
+      "ار ÙĬØ©",
+      "×ķ Ö",
+      "Ø¢ ÙĨ",
+      "×ŀ×¢ ×ķת",
+      "Ġм ал",
+      "Ġ×IJ ×Ĺ",
+      "à¸Ĺ à¹īà¸Ńà¸ĩ",
+      "ze ÅĽ",
+      "Ġë§Į ëĵ¤",
+      "رÙĬ ع",
+      "äºĭ ãĤĴ",
+      "à¸ļริ หาร",
+      "׾ ×ŀ×Ļ×ĵ",
+      "Ġм Ñĥж",
+      "ت رÙĪ",
+      "ĠباÙĦ Ø¥",
+      "פ ×Ļק",
+      "ز ÙħØ©",
+      "ĠÃ¶ÄŁ renc",
+      "ãĥ ¶",
+      "اÙħ عة",
+      "ק×ij ×ķצ",
+      "×ŀ ׳×ķת",
+      "رÙĬ Ùħ",
+      "Ġо каз",
+      "ãģłãģij ãģ©",
+      "Ġh ız",
+      "Ġש ×IJת",
+      "ãĤ¢ ãĥ¼",
+      "Ġmożli wo",
+      "ìĦ ¼",
+      "ÙĪ اب",
+      "ог ÑĢаÑĦ",
+      "Ġعبد اÙĦ",
+      "ãĤĴ è¡Į",
+      "ب ÙĬÙĦ",
+      "ĠÄ° ç",
+      "ย าย",
+      "ĠÑĥ ÑĩаÑģÑĤ",
+      "ÑĦ еÑģÑģ",
+      "ÑĦеÑģÑģ иона",
+      "Ạ¤",
+      "ÙĨ ÙĬÙĨ",
+      "عد ÙĦ",
+      "สร ร",
+      "دÙĬ ÙĦ",
+      "×ij ×Ļק",
+      "czy ÅĤ",
+      "ÑĢом е",
+      "Ġм ед",
+      "ìĻ Ķ",
+      "ãĥ© ãĤ¤ãĥ³",
+      "ĠÑĤ еп",
+      "еÑĢ ÑĮ",
+      "i ÄŁi",
+      "в ели",
+      "ÑĢи ÑģÑĤ",
+      "ס ×ķפ",
+      "×ŀ׾ ×Ĺ",
+      "ĠاÙĦØ¥ ÙĨ",
+      "Ġ׾×Ķ ש",
+      "è¶Ĭ ãģĹ",
+      "ĠÑĢ Ñĭ",
+      "×ķ×IJ ר",
+      "رÙĩ اب",
+      "פ ×ķ×IJ×Ļ",
+      "ĠгоÑģ Ñĥд",
+      "ĠгоÑģÑĥд аÑĢ",
+      "ĠгоÑģÑĥдаÑĢ ÑģÑĤв",
+      "ĠاÙĦØ£Ùħ ÙĬر",
+      "Ùħ ج",
+      "à¹Ģหม าะ",
+      "ÑĢ ев",
+      "à¸Ĭี à¸ŀ",
+      "ãĥķ ãĥĪ",
+      "иÑĩ но",
+      "ĠاÙĦÙħ ؤ",
+      "Ġi ht",
+      "íħ ľ",
+      "د ÙĨÙĬ",
+      "ر ص",
+      "ла ÑģÑĤ",
+      "à¹Ģหล à¹Īา",
+      "ılı r",
+      "ร à¸ĵà¹Į",
+      "×ŀש ×Ļ×ļ",
+      "Ġd á»ĭ",
+      "Ø·Ùģ اÙĦ",
+      "×ĺ ×ķף",
+      "Ġ×ij ×Ļ׳",
+      "ãģ¾ ãģ£ãģŁ",
+      "лож ениÑı",
+      "تØŃ Ø±",
+      "ب اØŃ",
+      "à¹Ģส ืà¹īà¸Ń",
+      "ãģĻ ãģĶ",
+      "lt ür",
+      "à¸ĩ าม",
+      "Ġt ü",
+      "ĠпÑĢ им",
+      "ĠпÑĢим ен",
+      "Ġhay at",
+      "ëĥ IJ",
+      "ëĭ Į",
+      "׳×Ļ ×ķ",
+      "вед ен",
+      "ìħ ¨",
+      "à¸Ī ัย",
+      "à¸ģà¹Ī à¸Ń",
+      "Ġв од",
+      "оÑģÑĤ оÑı",
+      "н аÑĤ",
+      "à¹ģ หล",
+      "سÙħ ÙĬ",
+      "à¸Ķำ à¹Ģà¸Ļ",
+      "à¸Ķำà¹Ģà¸Ļ ิà¸Ļ",
+      "w ód",
+      "ö yle",
+      "ãĥĢ ãĤ¤",
+      "ÑĪи й",
+      "меÑī ен",
+      "ãģĹãģ¾ ãģĨ",
+      "ãĥī ãĥ©",
+      "ÙĪض ØŃ",
+      "à¸Ńà¸Ļ ุ",
+      "ĠاÙĦ اجتÙħاع",
+      "laÅŁ ma",
+      "à¸Ħ à¸Ńà¸Ļ",
+      "×ŀר ×Ļ×Ŀ",
+      "ÙĨ اÙħج",
+      "שר ×ķת",
+      "اÙĦ Ø£",
+      "Ġksi Äħż",
+      "Ġа н",
+      "ÑĢаР¹",
+      "اÙĩر Ø©",
+      "×ŀ×ĵ ×Ķ",
+      "ä¸Ģ ç·",
+      "ä¸Ģç· Ĵ",
+      "ä¸Ģç·Ĵ ãģ«",
+      "ÑĢиÑĤ оÑĢ",
+      "d ıkl",
+      "à¹ģ à¸ĸ",
+      "à¹ģà¸Ĥ à¹Īà¸ĩ",
+      "екÑĤ оÑĢ",
+      "×ŀס ×¢",
+      "ÑĢак ÑĤи",
+      "u ÄŁu",
+      "×ķ×ij ת",
+      "สู à¸ķร",
+      "ĠçalÄ±ÅŁ m",
+      "ĠçalÄ±ÅŁm alar",
+      "Ġа на",
+      "ãĥĽ ãĥ¼ãĥł",
+      "Ġböl üm",
+      "Ġب ص",
+      "ол оÑģ",
+      "ĠìķĬ ëĬĶ",
+      "à¹Ī ะ",
+      "ÙĪ تر",
+      "ä¹ Ĺ",
+      "ست خداÙħ",
+      "פ×Ļ ×Ļס",
+      "פ×Ļ×Ļס ×ij",
+      "פ×Ļ×Ļס×ij ×ķק",
+      "Ġк ÑĢаÑģ",
+      "ли к",
+      "رÙĬ ØŃ",
+      "×ŀש ׾×Ķ",
+      "à¹Ģย ีà¹Īย",
+      "à¹Ģยีà¹Īย ม",
+      "в иÑģ",
+      "ом н",
+      "ÄŁ un",
+      "ãĥŃ ãĥ¼ãĥ³",
+      "Ø£ تÙĬ",
+      "à¸ķร ี",
+      "çĶ³ ãģĹ",
+      "تÙħ ر",
+      "ìĹ ĪìĬµëĭĪëĭ¤",
+      "ĠÙĪ غÙĬر",
+      "red ni",
+      "ĠاÙĦص Ùģ",
+      "Ġна ÑģÑĤоÑı",
+      "ĠнаÑģÑĤоÑı Ñī",
+      "à¸ķ รา",
+      "ĠÑĥÑģл ов",
+      "ĠÑĥÑģлов иÑı",
+      "ÑĨ еп",
+      "×Ķ ×Ĺ׾×ĺ",
+      "Ø· ÙĬع",
+      "ĠB akan",
+      "ĠاÙĦ رÙĪ",
+      "илÑĮ но",
+      "Ġм еÑĤ",
+      "à¸Ķ à¸Ńà¸ģ",
+      "ãģĭãĤī ãģªãģĦ",
+      "Ġпо ÑģÑĤоÑı",
+      "ĠпоÑģÑĤоÑı н",
+      "ĠÑĩ аÑģ",
+      "ü c",
+      "wr ó",
+      "б ÑĥÑĢ",
+      "ãĥIJ ãĥĥãĤ¯",
+      "ãĥ©ãĥ³ ãĥī",
+      "Ġо гÑĢ",
+      "สั à¸į",
+      "สัà¸į à¸įา",
+      "มั à¹Īà¸Ļ",
+      "à¸Ħ à¸Ńม",
+      "al ık",
+      "Ġн ед",
+      "üm üz",
+      "ĠÅĽ wie",
+      "é rio",
+      "×Ļ×IJ ×Ķ",
+      "دÙħ ات",
+      "ı rl",
+      "ĠоÑĤ з",
+      "ĠоÑĤз Ñĭв",
+      "ä»ĺ ãģį",
+      "Ġkaż de",
+      "мин иÑģÑĤ",
+      "ãĤ° ãĥ«",
+      "ë° ĸ",
+      "ез н",
+      "اÙĦ Ùģ",
+      "Ġש ק׾",
+      "Ùħ ض",
+      "ãĥĿ ãĥ¼ãĥĪ",
+      "ÙħÙĨ ت",
+      "ÙĤÙĬ اÙħ",
+      "Ø´ ÙĨ",
+      "×Ļר ×ķ×¢",
+      "ãĤŃãĥ£ ãĥ³",
+      "доÑĢ ов",
+      "×ŀ ×Ļת×Ļ",
+      "ÙĪÙĦ ÙĪج",
+      "Ùĥ اÙģ",
+      "ĠÑĢаз лиÑĩ",
+      "иÑĤ еÑĤ",
+      "н олог",
+      "ลà¸ĩ à¸Ĺุà¸Ļ",
+      "Ġyak laÅŁ",
+      "ãĥ¬ ãĤ¤",
+      "ê²ł ëĭ¤",
+      "æ±Ĥ ãĤģ",
+      "رÙĪ Ùģ",
+      "Ġí Ĭ",
+      "ĠíĬ ¹",
+      "ãģ£ ãģıãĤĬ",
+      "à¸Ħวาม à¸Ħิà¸Ķ",
+      "×Ķ ×Ļס×ĺ",
+      "Ø¥ ÙĤ",
+      "ãģ¦ ãģĦ",
+      "à¹Ĥ à¸Ĭ",
+      "ĠBü yük",
+      "ĠФ едеÑĢ",
+      "ÑĨи н",
+      "ÑĢов а",
+      "ĠاÙĦ اÙĤتصاد",
+      "Ġch á",
+      "à¸ĺ าà¸Ļ",
+      "ë¥ ł",
+      "à¹Ħ à¸ķ",
+      "ÃŃ pio",
+      "Ùĭ ا",
+      "Ġоб Ñıз",
+      "Ùĩ ج",
+      "Ġì¤ij ìļĶ",
+      "ãģ® ãģ§ãģ¯ãģªãģĦ",
+      "بار اة",
+      "ãĤ¤ ãĥ«",
+      "Ġн оÑĢм",
+      "á»ī nh",
+      "m ö",
+      "mö glich",
+      "ÑĨи п",
+      "ãĤ¢ ãĤ¯",
+      "×Ķ ×Ļ",
+      "ÑĨи алÑĮно",
+      "ĠÅĽ wi",
+      "ت ÙĤ",
+      "ĠÑģÑĤо им",
+      "بÙĬ عÙĬ",
+      "Ġ׾ ש×ŀ",
+      "г лÑı",
+      "глÑı д",
+      "ãģ¦ ãģıãĤĮ",
+      "ÄĻd zi",
+      "à¸Ĥ ั",
+      "à¸Ĥั à¹īà¸Ļ",
+      "Ø· ÙĤ",
+      "ĠìĹ Ń",
+      "ãģ£ãģ¦ãģĹãģ¾ ãģĨ",
+      "ĠdeÄŁer l",
+      "ĠdeÄŁerl endir",
+      "Ġü lk",
+      "Ġмн ог",
+      "๠ĭ",
+      "ë¿ IJ",
+      "ĠУ кÑĢа",
+      "ÄŁ ini",
+      "Ġбез оп",
+      "Ġбезоп аÑģ",
+      "à¸Ńà¸Ńà¸ģ à¹ģà¸ļà¸ļ",
+      "Ø§Ø ¸",
+      "ØŃد اث",
+      "л еÑĢ",
+      "×Ļ× ¥",
+      "×Ļ׳×ĺר ׳×ĺ",
+      "lar ınız",
+      "ØŃÙĬ ØŃ",
+      "ż eli",
+      "à¸Ń ัà¸ĩ",
+      "à¸Ńัà¸ĩ à¸ģ",
+      "à¸Ńัà¸ĩà¸ģ ฤษ",
+      "ĠоÑĤ лиÑĩ",
+      "ั ส",
+      "ëŀ į",
+      "ож но",
+      "ãĤ¹ ãĥĿ",
+      "ĠÑħ оÑĩ",
+      "Ġк ап",
+      "еÑĩ ен",
+      "ØŃÙĦ Ø©",
+      "ÙĬا Ùĩ",
+      "на л",
+      "×ķצ ר×Ļ×Ŀ",
+      "Ġk ald",
+      "åĥ į",
+      "ĠاÙĦØ´ خص",
+      "Ġз на",
+      "Ġwz gl",
+      "ż ycz",
+      "ê° Ŀ",
+      "à¸ŀ ลัà¸ĩ",
+      "íģ ¼",
+      "Ġö l",
+      "Ġb ụ",
+      "Ø´ Ùĩر",
+      "Ġз ам",
+      "Ġд ев",
+      "×Ļ×ĺ ת",
+      "تعÙĦ ÙĤ",
+      "ÙĪÙħ Ø©",
+      "ãĤĴ ä½ľ",
+      "ãģį ãģ¦",
+      "í ĥĿ",
+      "ras ında",
+      "ãĤĴ æİ¢",
+      "ĠÙħ باشر",
+      "راج ع",
+      "Ġв озд",
+      "ÙħØŃ Ø§",
+      "×ķש ר",
+      "ĠиÑģÑĤ оÑĢ",
+      "ม ัà¸ģ",
+      "t ıģ",
+      "ث ار",
+      "تر ÙĨت",
+      "à¹ģà¸Ĥ à¹ĩ",
+      "à¹ģà¸Ĥà¹ĩ à¸ĩ",
+      "п оÑĩ",
+      "Ġ×ij ×IJ×ķת",
+      "ë¯ Ģ",
+      "ëĿ¼ ëıĦ",
+      "à¸Ĭ ัà¸Ķ",
+      "ส à¸ķà¹Į",
+      "ãĥĭ ãĥĥãĤ¯",
+      "ид енÑĤ",
+      "Ġг ÑĢÑĥпп",
+      "ت خ",
+      "Ạł",
+      "ย ืà¸Ļ",
+      "ย ัà¸Ļ",
+      "ó ry",
+      "T Ãľ",
+      "ãģĹ ãĤĥ",
+      "ĠпÑĢов ед",
+      "лÑı еÑĤ",
+      "Ùħ Ø®",
+      "ย à¸Ńม",
+      "×Ľ×ł×¡ ת",
+      "ĠاÙĦÙħ ÙĨت",
+      "Ġol mad",
+      "ר׼ ×ĸ×Ļ",
+      "Ġв ÑģÑĤÑĢ",
+      "ĠиÑģ Ñģлед",
+      "ÑĤвеÑĢ ж",
+      "بد ÙĪ",
+      "еÑĢ ÑĤ",
+      "ï» ·",
+      "± ħ",
+      "สัม à¸ŀัà¸Ļà¸ĺà¹Į",
+      "ิ à¹Īà¸Ļ",
+      "צ ×Ļ×ij",
+      "wiÄĻ t",
+      "Ġì° ¸",
+      "Ġz wiÄħz",
+      "سب ÙĪع",
+      "ãĥĥ ãĤ°",
+      "à¸Ľà¸¥ à¸Ńà¸Ķ",
+      "à¸Ľà¸¥à¸Ńà¸Ķ à¸łà¸±à¸¢",
+      "ãĤĤ ãĤĬ",
+      "ÙĤد س",
+      "Ġspr z",
+      "Ġsprz eda",
+      "Ġist edi",
+      "Ġk hu",
+      "Ġд ен",
+      "Ġko ÅĦ",
+      "Ġ×ij ×Ĺ×Ļ",
+      "à¹Ģà¸Ĺ à¹īา",
+      "×ķס ×Ļ×£",
+      "ãĥĭ ãĥ¥ãĥ¼",
+      "ĠпÑĢед оÑģÑĤ",
+      "ĠпÑĢедоÑģÑĤ ав",
+      "à¹Ĥ à¸Ł",
+      "é v",
+      "ĠاÙĦص ØŃ",
+      "صØŃ Ø§Ø¨",
+      "à¹Ģà¸Ī à¹ĩà¸ļ",
+      "вл ек",
+      "วั à¸ķ",
+      "à¸ĸ ุ",
+      "ãģĵãģ¨ãģĮãģ§ãģį ãģ¾ãģĻ",
+      "ÙĤÙĬ ÙĤÙĬ",
+      "×ķ׊ר",
+      "Ñĭ ÑĪ",
+      "ĠоÑĤ но",
+      "ĠоÑĤно ÑĪ",
+      "об илÑĮ",
+      "Ùģ ØŃ",
+      "ı nt",
+      "ınt ı",
+      "Ġ׾ ×ij×ĵ",
+      "í İĺìĿ´ì§Ģ",
+      "ãĥĬ ãĥ«",
+      "ĠÙħ ساء",
+      "×Ļ×ĺ ×ij",
+      "ÑĮ еÑĢ",
+      "ëĦ ·",
+      "Ñĭ ÑĤа",
+      "ĠоÑĩ еÑĢ",
+      "à¸Ķ ืà¹Ī",
+      "à¸Ķืà¹Ī ม",
+      "ĠN gh",
+      "ت عب",
+      "ÙĦاÙĤ ات",
+      "×ķ׾×ķ×Ĵ ×Ļ×Ķ",
+      "ĠìĿ´ ê²ĥ",
+      "Ġ×Ķ ×ijר",
+      "ìľ µ",
+      "à¹Ģà¸Ħล ืà¹Īà¸Ńà¸Ļ",
+      "Ùĩ Ø©",
+      "à¸Īำ à¹Ģà¸Ľà¹ĩà¸Ļ",
+      "å¤ī ãģĪ",
+      "wi ÅĽcie",
+      "ch od",
+      "chod zÄħ",
+      "в ÑĢо",
+      "×ŀ×Ĺ ×Ļר",
+      "Ġy ı",
+      "Ġyı ll",
+      "ì¡ Į",
+      "à¹Ħ หว",
+      "ãģªãģı ãģª",
+      "Ġзав иÑģ",
+      "ĠìĺĪ ìĪĺ",
+      "Ùģ Ø°",
+      "ủ ng",
+      "à¸ŀุ à¸Ĺà¸ĺ",
+      "з н",
+      "lay an",
+      "ãĤ ¡",
+      "à¸ģà¹ĩ à¸ķาม",
+      "ĠsaÄŁ lam",
+      "ร à¸ĵ",
+      "ĠÑģ иÑĤ",
+      "ĠÑģиÑĤ Ñĥ",
+      "ĠاÙĦت ÙĨ",
+      "×Ķ ×ĸ",
+      "ĠØ· ÙĪÙĬÙĦ",
+      "ta ÅĤ",
+      "Ġgö rd",
+      "å¤ī ãĤı",
+      "ëĥ ¥",
+      "à¸Ħà¹Ī à¸Ńย",
+      "×IJ ×ķ×ĺ",
+      "ëħ IJ",
+      "ãĥ©ãĥ³ ãĤ¹",
+      "วั à¸Ĵ",
+      "วัà¸Ĵ à¸Ļ",
+      "Ġol uÅŁ",
+      "פע ×ķ׾",
+      "Ġszczeg óÅĤ",
+      "à¸Ħา สิ",
+      "à¸Ħาสิ à¹Ĥà¸Ļ",
+      "pow ied",
+      "ĠÑĤ еб",
+      "หà¸Ļ à¹Īวย",
+      "Ġм ил",
+      "ØŃ Ùĥ",
+      "à¸Ĺ à¸Ķ",
+      "ĠмаÑĤ еÑĢиал",
+      "ÅĤ ow",
+      "à¹Ģà¸ģ ีย",
+      "ĠÑģов еÑĢ",
+      "ãĤ ©",
+      "à¸Ľ ริ",
+      "Ġи Ñİ",
+      "наÑĩ ен",
+      "ÑĢен д",
+      "mu ÅŁtur",
+      "ĠпÑĢод Ñĥк",
+      "з д",
+      "Ñı ÑĤи",
+      "ÑıÑĤи Ñı",
+      "à¹Ģม ีย",
+      "رات ÙĬج",
+      "Ġam acı",
+      "ש ×ķ׾",
+      "ש×ķ׾ ×Ĺ",
+      "สะ à¸Ńา",
+      "สะà¸Ńา à¸Ķ",
+      "פ×Ĵ ×¢",
+      "عب ة",
+      "d ın",
+      "íħ Ķ",
+      "Ġ×ŀש ×Ĺק",
+      "Ġfi yat",
+      "Ġз аÑı",
+      "ĠзаÑı в",
+      "à¹Ĥ หล",
+      "à¹Ĥหล à¸Ķ",
+      "à¸ģรุà¸ĩ à¹Ģà¸Ĺà¸ŀ",
+      "צ×Ļ ×Ļף",
+      "ìļ ±",
+      "Ùħ ب",
+      "Ùħب اد",
+      "land ır",
+      "Ġв еÑģÑĮ",
+      "Ġh ük",
+      "ĠÐĴ оз",
+      "ÑĩиÑĤ Ñĭва",
+      "ว ล",
+      "×ķצ ×¢",
+      "à¸Ĥà¸ĵะ à¸Ĺีà¹Ī",
+      "ĠaÅŁ aģı",
+      "׾×IJ ×ķ×ŀ×Ļ",
+      "tr zym",
+      "Ã¤ÃŁ ig",
+      "owo ÅĽci",
+      "ãģĿ ãĤĤ",
+      "Ġroz wiÄħz",
+      "ĠgÅĤ ówn",
+      "м онÑĤ",
+      "×ŀ ×ķ×ŀ",
+      "ĠÑģÑĤ ан",
+      "ÙĦا ÙĤØ©",
+      "p rowad",
+      "prowad zi",
+      "ĠÑģоÑģÑĤ оÑı",
+      "×Ļ×IJ ×ķת",
+      "r ı",
+      "g ı",
+      "ãĥij ãĥij",
+      "Ġна лиÑĩ",
+      "×Ķ צע",
+      "Ġ׳ ×Ķ",
+      "à¸Ħ ัà¸ļ",
+      "ع راض",
+      "и ж",
+      "Ùĩ ائÙĬ",
+      "ãĤī ãģı",
+      "ож еÑĤ",
+      "Ġоб оÑĢ",
+      "ĠобоÑĢ Ñĥд",
+      "Ø£ سÙĦ",
+      "à¹ĩ à¸Ķ",
+      "ÑĢÑĥ ÑĤ",
+      "دÙĬ ÙħÙĤ",
+      "دÙĬÙħÙĤ را",
+      "Ġjest e",
+      "×ķ×ķ ×Ļר",
+      "×ij×ĵ ×Ļק",
+      "деÑĢж ива",
+      "ãģĬ ãģı",
+      "ewn ÄĻtr",
+      "ewnÄĻtr zn",
+      "à¸ŀ ฤ",
+      "Ġ×IJ ×ķ×Ķ",
+      "ת×Ĺ ×ķש",
+      "Ġz ob",
+      "д Ñĥм",
+      "ĠÑģ Ñĭ",
+      "ÙĬر ا",
+      "ĠwiÄĻ ks",
+      "à¹ģà¸ķà¸ģ à¸ķà¹Īาà¸ĩ",
+      "lar aras",
+      "lararas ı",
+      "íĺ Ģ",
+      "ëī ´",
+      "×ķ×Ĵ ׾",
+      "ĠоÑĤ меÑĤ",
+      "ĠÑĢ ан",
+      "ت ÙĥÙĦ",
+      "иÑĤелÑĮ н",
+      "à¸Ľà¸£à¸° วั",
+      "à¸Ľà¸£à¸°à¸§à¸± à¸ķิ",
+      "ìŀ ĸ",
+      "мож но",
+      "pie czeÅĦ",
+      "pieczeÅĦ st",
+      "ëª »",
+      "ìĬ ¨",
+      "×ŀס ×ŀ",
+      "á» ¦",
+      "ศ ิ",
+      "ศิ ล",
+      "ศิล à¸Ľ",
+      "ĠÅļ w",
+      "ãĥĥ ãĤ·ãĥ§ãĥ³",
+      "unit Ãł",
+      "Ġmiesz ka",
+      "Ġmieszka ÅĦ",
+      "pr zed",
+      "przed si",
+      "przedsi ÄĻb",
+      "przedsiÄĻb ior",
+      "à¸Ľà¸£à¸° สิà¸Ĺà¸ĺิ",
+      "à¸Ľà¸£à¸°à¸ªà¸´à¸Ĺà¸ĺิ à¸łà¸²à¸ŀ",
+      "ย à¹Ī",
+      "ìķ Ļ",
+      "รว à¸Ķ",
+      "รวà¸Ķ à¹Ģรà¹ĩว",
+      "å½ĵ ãģŁãĤĬ",
+      "äl le",
+      "Ñĥ еÑĤÑģÑı",
+      "ã n",
+      "ëł µ",
+      "th è",
+      "ãĤĴ åĪ©çĶ¨",
+      "ì µľ",
+      "íĵ ¨",
+      "à¸Ĺ ัà¸ļ",
+      "า à¸Ħม",
+      "ãģ ĩ",
+      "ëĤ Į",
+      "à¹Ģà¸Ľà¸¥ à¹Īา",
+      "â ¦",
+      "ë ¾",
+      "ê Ģ",
+      "ê ĩ",
+      "â ¡",
+      "ðŁ Ł",
+      "ã IJ",
+      "â º",
+      "á Ń",
+      "á Ļ",
+      "á ĵ",
+      "á ²",
+      "ðĵ ı",
+      "á ¬",
+      "â ¯",
+      "ä ¨",
+      "ê Ŀ",
+      "ê «",
+      "ð ij",
+      "ðĵ ĥ",
+      "ðĿ ħ",
+      "< unk",
+      "<unk >",
+      "<s >",
+      "</ s",
+      "</s >",
+      "Ġع ÙĦÙī",
+      "Ġm á»Ļt",
+      "Ġv Ỽi",
+      "Ġng Æ°á»Ŀi",
+      "ĠØ¥ ÙĦÙī",
+      "Ġnh ững",
+      "Ġth á»ĥ",
+      "Ġ×IJ ×ķ",
+      "Ġ×¢ ×Ŀ",
+      "ا Ùĭ",
+      "Ġ à¹ģละ",
+      "ĠÙĦ ا",
+      "Ġnh Æ°",
+      "ĠاÙĦت ÙĬ",
+      "Ġ×Ķ ×ķ×IJ",
+      "ĠÄij ến",
+      "ĠØ£ ÙĪ",
+      "Ġv á»ģ",
+      "ĠlÃł m",
+      "Ġs ẽ",
+      "Ġc Å©ng",
+      "Ġ ợ",
+      "ĠÄij ó",
+      "Ġnhi á»ģu",
+      "Ġt ại",
+      "Ġtr ên",
+      "Ġ×Ĵ ×Ŀ",
+      "Ġnh Ãł",
+      "Ġ׼ ×Ļ",
+      "Ġs á»±",
+      "ĠÄij ầu",
+      "Ġb á»ĭ",
+      "ĠÙĩ ذا",
+      "Ġnh ất",
+      "Ġph ải",
+      "Ġhi á»ĩn",
+      "Ġdụ ng",
+      "ĠÄij á»Ļng",
+      "ĠاÙĦÙĦ Ùĩ",
+      "ĠØ Į",
+      "ĠÙĥ ÙĦ",
+      "Ġvi á»ĩc",
+      "Ġn Äĥm",
+      "Ġth ì",
+      "Ġh á»įc",
+      "ĠÙĪ ت",
+      "t é",
+      "Ġا ÙĨ",
+      "Ġt ôi",
+      "Ġ×IJ ׳×Ļ",
+      "Ġ׾ ×Ļ",
+      "Ġ×ŀ ×ķ",
+      "Ġng Ãły",
+      "Ġn Æ°á»Ľc",
+      "Ġ×Ķ ×Ļ×IJ",
+      "Ġ×IJ ×Ļ",
+      "Ġh Æ¡n",
+      "ĠÙĩ Ø°Ùĩ",
+      "ĠÙĪ ÙĬ",
+      "ĠاÙĦ Ø°ÙĬ",
+      "Ġ×ķ ×ŀ",
+      "Ġgi á",
+      "Ġnh ân",
+      "Ġch ÃŃnh",
+      "Ġm ình",
+      "ĠÐĿ а",
+      "Ġth ế",
+      "Ġ×Ļ ×ķתר",
+      "Ġ×IJ ×Ŀ",
+      "Ġn ên",
+      "Ġh ợ",
+      "Ġhợ p",
+      "Ġc òn",
+      "ĠÙĩ ÙĪ",
+      "Ġc Æ¡",
+      "Ġr ất",
+      "ĠVi á»ĩt",
+      "Ġب عد",
+      "Ġש ×Ļ",
+      "Ġth á»Ŀi",
+      "Ġc ách",
+      "ĠÄij á»ĵng",
+      "Ġн о",
+      "Ġtr Æ°á»Ŀng",
+      "Ø Ł",
+      "ĠÄij á»ĭnh",
+      "ĠÄiji á»ģu",
+      "×Ļ ×Ļ×Ŀ",
+      "Ġth á»±c",
+      "n ın",
+      "Ġh ình",
+      "Ġn ói",
+      "Ġc ùng",
+      "Ġ×Ķ ×Ķ",
+      "ĠØ¥ ÙĨ",
+      "Ġ×IJ ×ij׾",
+      "Ġnh Æ°ng",
+      "Ġbi ết",
+      "Ġж е",
+      "Ġch úng",
+      "ĠÄij ang",
+      "ĠØ° ÙĦÙĥ",
+      "Ġl ên",
+      "Ġkh ách",
+      "Ġn Ãło",
+      "Ġs á»Ń",
+      "Ġkh ác",
+      "Ġë° ı",
+      "Ġl ý",
+      "×Ļ ×Ļ",
+      "ĠÄij ây",
+      "Ġ׾ ×ŀ",
+      "Ġc ần",
+      "Ġtr ình",
+      "Ġph át",
+      "ãģ« ãĤĤ",
+      "п о",
+      "Ġn Äĥng",
+      "Ġb á»Ļ",
+      "Ġv ụ",
+      "ĠÄij á»Ļ",
+      "Ñĩ е",
+      "Ġnh áºŃn",
+      "Ġtr Æ°á»Ľc",
+      "Ġ×¢ ×ĵ",
+      "Ġh Ãłnh",
+      "ĠØ® ÙĦاÙĦ",
+      "Ġl ượng",
+      "Ġc ấp",
+      "Ġtá» ±",
+      "Ġv ì",
+      "Ġt Æ°",
+      "Ġch ất",
+      "Ġ׼ ×ŀ×ķ",
+      "Ġg ì",
+      "Ġש ׳",
+      "Ġt ế",
+      "ת ×ķ",
+      "Ġnghi á»ĩp",
+      "Ġm ặt",
+      "ĠÙĥ Ùħا",
+      "Ġ×ij ×Ļף",
+      "Ġר ק",
+      "Ġth ấy",
+      "Ġmá y",
+      "ĠÙģ Ùī",
+      "Ġd ân",
+      "Ġ×IJ ×Ĺ×ĵ",
+      "Ġt âm",
+      "Ġ׼ ×ļ",
+      "Ġ׾ ×ķ",
+      "в о",
+      "Ġt ác",
+      "Ġto Ãłn",
+      "ĠÙĪ Ùħ",
+      "Ġk ết",
+      "Ġ หรืà¸Ń",
+      "ĠÙĪاÙĦ Ùħ",
+      "ĠÄiji á»ĥm",
+      "Ġ×ĸ ×ķ",
+      "Ġ×ij ×ķ",
+      "׼ ×ķת",
+      "Ġh á»Ļi",
+      "Ġb ằng",
+      "ت Ùĩا",
+      "Ġ׼ ×ĵ×Ļ",
+      "Ġ×Ķ ×Ŀ",
+      "Ġxu ất",
+      "ĠÙĤ د",
+      "Ġb ảo",
+      "Ġt á»ijt",
+      "Ġt ình",
+      "ĠÙĩ ÙĬ",
+      "ĠÄij á»iji",
+      "Ġthi ết",
+      "Ġhi á»ĩu",
+      "Ġti ếp",
+      "Ġt ạo",
+      "ת ×Ķ",
+      "Ġch ủ",
+      "o ÅĽÄĩ",
+      "Ġgi ú",
+      "Ġgiú p",
+      "ĠÃ ½",
+      "Ġqu ả",
+      "Ġlo ại",
+      "Ġc ô",
+      "ĠÃ ´",
+      "Ġô ng",
+      "Ġ×Ķ ×ķ",
+      "ĠاÙĦÙĬ ÙĪÙħ",
+      "ĠtÃŃ nh",
+      "г а",
+      "Ġph òng",
+      "Ġ Äĥn",
+      "Ġع اÙħ",
+      "Ġv á»ĭ",
+      "lar ını",
+      "r ÃŃa",
+      "Ġt Ỽi",
+      "ĠÄij Æ°á»Ŀng",
+      "Ġgi Ỽi",
+      "Ġb ản",
+      "Ġc ầu",
+      "Ġnhi ên",
+      "Ġb á»ĩnh",
+      "Ġth Æ°á»Ŀng",
+      "Ġ×IJ ×Ļף",
+      "ĠÄij á»ģ",
+      "Ġh á»ĩ",
+      "Ġ×Ļש ר×IJ׾",
+      "Ġqu á",
+      "ĠÐĹ Ð°",
+      "ãģ® ãģ§ãģĻãģĮ",
+      "ĠÐŁ ÑĢи",
+      "Ġph ần",
+      "ĠÙĪ ÙĦا",
+      "ĠlỼ n",
+      "Ġtr á»ĭ",
+      "Ġcả m",
+      "Ġм о",
+      "Ġd ùng",
+      "ĠاÙĦ Ùī",
+      "ĠعÙĦÙĬ Ùĩ",
+      "ĠìŀĪ ìĬµëĭĪëĭ¤",
+      "ÙĬ ÙĤ",
+      "ĠÙĤ بÙĦ",
+      "Ġho ặc",
+      "ĠØŃ ÙĬØ«",
+      "Ġ à¸Ĺีà¹Ī",
+      "Ġغ ÙĬر",
+      "ĠÄij ại",
+      "Ġsá»ij ng",
+      "нÑĭ ми",
+      "Ġth ức",
+      "Ġפ ×Ļ",
+      "ĠÄiji á»ĩn",
+      "ãģª ãģĭãģ£ãģŁ",
+      "Ġgi ải",
+      "Ġv ẫn",
+      "Ġи Ñħ",
+      "Ġö nce",
+      "Ġv áºŃy",
+      "Ġmu á»ijn",
+      "Ġ ảnh",
+      "à¹ĥà¸Ļ à¸ģาร",
+      "ĠQu á»ijc",
+      "Ġk ế",
+      "׳ ×IJ",
+      "Ġס ×Ļ",
+      "Ġy êu",
+      "ãģ® ãģĭ",
+      "ĠÄij ẹ",
+      "ĠÄijẹ p",
+      "Ġch ức",
+      "Ġy ıl",
+      "ĠTür kiye",
+      "d é",
+      "ĠÙĤ اÙĦ",
+      "Ġd á»ĭch",
+      "ĠolduÄŁ u",
+      "Ġch á»įn",
+      "Ġت Ùħ",
+      "หà¸Ļ ึà¹Īà¸ĩ",
+      "ãģķãĤĮ ãģŁ",
+      "Ġph áp",
+      "ìĽ Ķ",
+      "Ġti á»ģn",
+      "ãģĹ ãģ¾ãģĹãģŁ",
+      "Ġש ׾×IJ",
+      "ÙĦ Ø©",
+      "Ġ׾פ ׳×Ļ",
+      "Ġ×ij ×Ļת",
+      "ĠH Ãł",
+      "ĠØŃ Øª",
+      "ĠØŃت Ùī",
+      "Ġ×¢ ×ķ×ĵ",
+      "Ġn ó",
+      "Ġth áng",
+      "à¹Ģลืà¸Ń à¸ģ",
+      "ר ×Ķ",
+      "Ġt Äĥng",
+      "Ġcá i",
+      "Ġtri á»ĥn",
+      "Ġ×IJ×ķת ×ķ",
+      "ìłģ ìĿ¸",
+      "ĠC ông",
+      "Ġ׾×Ķ ×Ļ×ķת",
+      "Ġг ода",
+      "и Ñİ",
+      "Ġب عض",
+      "Ġ à¸ģาร",
+      "èī¯ ãģĦ",
+      "ÙĪ ت",
+      "Ġli ên",
+      "ĠÐĿ о",
+      "ĠÐĿ е",
+      "çļĦ ãģª",
+      "ĠÙħ ت",
+      "ĠÑĤак же",
+      "ĠкоÑĤоÑĢ Ñĭе",
+      "Ġ×Ļ ×ĵ×Ļ",
+      "Ġtr á»įng",
+      "ãĤµ ãĤ¤ãĥĪ",
+      "ìłģ ìľ¼ë¡ľ",
+      "Ġt áºŃp",
+      "Ġש ׾×Ļ",
+      "íķĺ ê²Į",
+      "Ġt Ãłi",
+      "ĠÐ ¯",
+      "Ġr á»ĵi",
+      "ا Ùĥ",
+      "Ġth Æ°Æ¡ng",
+      "Ġ×Ķ ×ĸ×Ķ",
+      "ĠÙĪ ÙħÙĨ",
+      "à¸Ĺีà¹Ī มี",
+      "Ġcu á»Ļc",
+      "Ġbü yük",
+      "ãģ¨ ãģĭ",
+      "Ġ×ij ×Ļ×ķתר",
+      "Ġl ần",
+      "Ġgö re",
+      "Ġtr ợ",
+      "Ġ×ĺ ×ķ×ij",
+      "ÑĤÑĮ ÑģÑı",
+      "Ġth á»ijng",
+      "Ġ׼ ש",
+      "Ġti êu",
+      "Ġ×ŀ×IJ ×ķ×ĵ",
+      "Ø Ľ",
+      "k Äħ",
+      "Ġ à¹ĥà¸Ļ",
+      "Ġv ấn",
+      "Ġש ׾×ķ",
+      "ĠÄij á»ģu",
+      "Ùģ ت",
+      "Ġê²ĥ ìĿ´",
+      "Ġh óa",
+      "ĠاÙĦع اÙħ",
+      "ĠÙĬ ÙĪÙħ",
+      "к ой",
+      "Ġbi á»ĩt",
+      "ÑģÑĤ о",
+      "Ġ×Ķ ×Ļ×ķ",
+      "à¸Ĺีà¹Ī à¸Īะ",
+      "Ġ×ĵ ×Ļ",
+      "Ġ×IJ ×ļ",
+      "Ġá n",
+      "ص ÙĪر",
+      "Ġtr ÃŃ",
+      "ĠÐŁÑĢ о",
+      "Ġl á»±c",
+      "ãģĹãģ¦ ãģĦãģ¾ãģĻ",
+      "Ġb Ãłi",
+      "Ġ×ĸ ×IJת",
+      "Ġb áo",
+      "à¸ļ à¸Ļ",
+      "ĠëĮĢ íķľ",
+      "Ġti ế",
+      "Ġtiế ng",
+      "Ġb ên",
+      "ãģķãĤĮ ãĤĭ",
+      "s ión",
+      "Ġt ìm",
+      "×¢ ×ķ",
+      "m é",
+      "ни Ñı",
+      "ãģ» ãģ©",
+      "Ġà¹Ģà¸ŀ ราะ",
+      "ب ة",
+      "Ġë¶ Ħ",
+      "Ġ×IJ ×ĸ",
+      "à¸Ĺ à¹Īาà¸Ļ",
+      "ת ×Ŀ",
+      "Ġth êm",
+      "Ġho ạt",
+      "y ı",
+      "×ĸ ×ķ",
+      "Ġgi á»Ŀ",
+      "Ġb án",
+      "à¸Ĥ าย",
+      "Ñĩ а",
+      "Ġ à¹Ĩ",
+      "ĠاÙĦÙħ ت",
+      "ĠоÑĩ енÑĮ",
+      "Ġb ất",
+      "Ġtr ẻ",
+      "ÑĤ ÑĢ",
+      "ĠØ£ ÙĨÙĩ",
+      "ĠØ« Ùħ",
+      "Ġ׼ ×ŀ×Ķ",
+      "Ġkh ó",
+      "Ġr ằng",
+      "ĠÙĪ ÙģÙĬ",
+      "ни й",
+      "Ġho Ãłn",
+      "t ó",
+      "Ġ×IJ שר",
+      "ĠìĥĿ ê°ģ",
+      "Ñģ а",
+      "Ġ׼ ×ijר",
+      "ĠÑįÑĤ ом",
+      "lar ının",
+      "Ġch Æ°a",
+      "з и",
+      "Ġd ẫn",
+      "ĠÐļ ак",
+      "ج ÙĪ",
+      "ĠбÑĭ ло",
+      "ĠÙĬ ت",
+      "n ı",
+      "ÅĤ am",
+      "ĠÙĪÙĩ ÙĪ",
+      "×ij ×ķ",
+      "п и",
+      "ר ת",
+      "Ġqu á»ijc",
+      "ж д",
+      "ĠÄij Æ¡n",
+      "Ùĥت ب",
+      "Ġm ắt",
+      "ระ à¸ļ",
+      "ระà¸ļ à¸ļ",
+      "ĠÙĥ اÙĨت",
+      "Ġth ân",
+      "สิà¸Ļ à¸Ħà¹īา",
+      "×Ĵ ×Ļ",
+      "Ġph Æ°Æ¡ng",
+      "à¹Ħมà¹Ī à¹Ħà¸Ķà¹ī",
+      "ĠìĦ ±",
+      "ĠC ác",
+      "Ġ×Ķ×ŀ ×ķ",
+      "ĠÑĤ ем",
+      "Ġ×ĵ ×ķ",
+      "à¸Ńะ à¹Ħร",
+      "Ġv Äĥn",
+      "ãģª ãģ®ãģ§",
+      "ĠN á»Ļi",
+      "Ġ×¢ ×ķ",
+      "ãĤīãĤĮ ãĤĭ",
+      "Ġs áng",
+      "Ġgö ster",
+      "ãģĵãģ¨ ãĤĴ",
+      "Ġtaraf ından",
+      "Ġм а",
+      "ĠпоÑģл е",
+      "Ġ׳ ×Ļת",
+      "Ġ׳×Ļת ף",
+      "Ġл еÑĤ",
+      "Ġ׾ ׳×ķ",
+      "Ñģ Ñģ",
+      "Ġ×Ļ ×ķ",
+      "п е",
+      "ĠÙĪ ÙĦÙĥ",
+      "ĠÙĪÙĦÙĥ ÙĨ",
+      "Ġngo Ãłi",
+      "ĠÄij á»ĭa",
+      "r zÄħd",
+      "dz iaÅĤ",
+      "ĠÙħ ر",
+      "иÑĤÑĮ ÑģÑı",
+      "Ġ×IJ×Ĺר ×Ļ",
+      "Ġ׾ ׼׾",
+      "à¸Ĥ à¹īà¸Ńม",
+      "à¸Ĥà¹īà¸Ńม ูล",
+      "Ġб ол",
+      "Ġбол ее",
+      "جÙħ ع",
+      "л еÑĤ",
+      "Ġl á»ĭch",
+      "ĠÙħ Ø«ÙĦ",
+      "Ġ그리 ê³ł",
+      "Ġth ứ",
+      "ĠdeÄŁ il",
+      "ÙĪ ØŃ",
+      "Ġש׾ ×ļ",
+      "ĠÙħ ØŃÙħد",
+      "Ġn ếu",
+      "ĠÄij á»ķi",
+      "Ġv ừa",
+      "Ġm á»įi",
+      "Ġо ни",
+      "Ġl úc",
+      "ĠÙĬ ÙĥÙĪÙĨ",
+      "ì§ Ī",
+      "Ġש׾ ׳×ķ",
+      "ĠÐĶ о",
+      "Ġש ׳×Ļ",
+      "ล ิ",
+      "×IJ פשר",
+      "Ġs ức",
+      "ê¶ Į",
+      "Ġ ứng",
+      "à¹Ħมà¹Ī มี",
+      "Ø·ÙĦ ب",
+      "ĠÑĩ ем",
+      "Ġch uyên",
+      "Ġth ÃŃch",
+      "Ġ×ķ ×Ļ",
+      "íķ ©",
+      "ĠÙħ صر",
+      "д о",
+      "ĠÄij ất",
+      "Ġch ế",
+      "à¸Ĭ ืà¹Īà¸Ń",
+      "Ġìĭ ł",
+      "ĠØ¥ ذا",
+      "Ġر ئÙĬس",
+      "Ġש ×Ļש",
+      "Ġgiả m",
+      "Ñģ ка",
+      "lar ında",
+      "Ġs ợ",
+      "ĠtÃŃ ch",
+      "ĠÙĦ ÙĥÙĨ",
+      "Ġب Ùħ",
+      "×¢ ×ķ×ij",
+      "×¢×ķ×ij ×ĵ",
+      "ÅĤÄħ cz",
+      "ları na",
+      "Ġש ×Ŀ",
+      "ĠÙĦ ت",
+      "Ġש×Ķ ×ķ×IJ",
+      "t ów",
+      "Ġëĭ¤ 른",
+      "ĠØ£ Ùĥثر",
+      "ãģ® ãģ§ãģĻ",
+      "׼ ×Ļ×Ŀ",
+      "ĠolduÄŁ unu",
+      "ãģĭ ãģª",
+      "ãĤĤ ãģĨ",
+      "ÙĬ ØŃ",
+      "Ġnh ìn",
+      "Ġngh á»ĩ",
+      "ãģ«ãģª ãģ£ãģ¦",
+      "п а",
+      "Ġquy ết",
+      "ÙĦ ÙĤ",
+      "t á",
+      "Ġlu ôn",
+      "ĠÄij ặc",
+      "Ġ×IJ ר",
+      "Ġtu á»ķi",
+      "s ão",
+      "ìĻ ¸",
+      "ر د",
+      "ĠبÙĩ ا",
+      "Ġ×Ķ×Ļ ×ķ×Ŀ",
+      "×ķ ×ķ×Ļ",
+      "ãģ§ãģĻ ãģŃ",
+      "ĠÑĤ ого",
+      "Ġth ủ",
+      "ãģĹãģŁ ãģĦ",
+      "ر ÙĤ",
+      "Ġb ắt",
+      "г Ñĥ",
+      "Ġtá» Ń",
+      "ÑĪ а",
+      "Ġ à¸Ľà¸µ",
+      "Ġ×Ķ×IJ ×Ŀ",
+      "íı ¬",
+      "ż a",
+      "Ġ×IJת ×Ķ",
+      "Ġn á»Ļi",
+      "Ġph ÃŃ",
+      "ĠÅŁek ilde",
+      "Ġl á»Ŀi",
+      "d ıģı",
+      "Ġ׼×IJ ף",
+      "Ġt üm",
+      "Ġm ạnh",
+      "ĠM ỹ",
+      "ãģĿ ãĤĵãģª",
+      "Ġnh á»ı",
+      "ãģª ãģĮãĤī",
+      "Ġb ình",
+      "ı p",
+      "à¸ŀ า",
+      "ĠÄij ánh",
+      "ĠÙĪ ÙĦ",
+      "ר ×ķת",
+      "Ġ×IJ ×Ļ×ļ",
+      "Ġch uyá»ĥn",
+      "Ùĥ ا",
+      "ãĤĮ ãĤĭ",
+      "à¹ģม à¹Ī",
+      "ãĤĪ ãģı",
+      "ĠÙĪ ÙĤد",
+      "íĸ Īëĭ¤",
+      "Ġn Æ¡i",
+      "ãģ«ãĤĪ ãģ£ãģ¦",
+      "Ġvi ết",
+      "Ġà¹Ģà¸ŀ ืà¹Īà¸Ń",
+      "ëIJĺ ëĬĶ",
+      "اد ÙĬ",
+      "ĠÙģ Ø¥ÙĨ",
+      "ì¦ Ŀ",
+      "ĠÄij ặt",
+      "Ġh Æ°á»Ľng",
+      "Ġx ã",
+      "Ġönem li",
+      "ãģł ãģ¨",
+      "Ġm ẹ",
+      "Ġ×ij ×Ļ",
+      "Ġ×ĵ ×ijר",
+      "Ġv áºŃt",
+      "ĠÄij ạo",
+      "Ġdá»± ng",
+      "ĠÑĤ ом",
+      "ĠÙģÙĬ Ùĩا",
+      "Ġج ÙħÙĬع",
+      "Ġthu áºŃt",
+      "st ÄĻp",
+      "Ġti ết",
+      "Ø´ ÙĬ",
+      "Ġе Ñīе",
+      "ãģĻãĤĭ ãģ¨",
+      "ĠmÃł u",
+      "ĠÑįÑĤ ого",
+      "Ġv ô",
+      "ĠÐŃ ÑĤо",
+      "Ġth áºŃt",
+      "Ġn ữa",
+      "Ġbi ến",
+      "Ġn ữ",
+      "Ġ׾ ׼×Ŀ",
+      "×Ļ ×Ļף",
+      "Ġس ت",
+      "ĠÐŀ ÑĤ",
+      "Ġph ụ",
+      "ê¹Į ì§Ģ",
+      "Ġ׾ ×ļ",
+      "Ġk ỳ",
+      "à¹ĥ à¸Ħร",
+      "Ġg ây",
+      "ĠÙĦ ÙĦÙħ",
+      "Ġtụ c",
+      "ت ÙĬÙĨ",
+      "Ġtr ợ",
+      "Ġ׾ פ×Ļ",
+      "Ġb á»ij",
+      "ĠÐļ а",
+      "ĠÄij ình",
+      "ow Äħ",
+      "s ında",
+      "Ġkhi ến",
+      "s ız",
+      "Ġк огда",
+      "ס ׾",
+      "ĠбÑĭ л",
+      "à¸Ļ à¹īà¸Ńย",
+      "обÑĢаР·",
+      "Ġê²ĥ ìĿ´ëĭ¤",
+      "ëĵ¤ ìĿĢ",
+      "ãģ¸ ãģ®",
+      "Ġà¹Ģม ืà¹Īà¸Ń",
+      "Ġph ục",
+      "Ġ׊׾ק",
+      "Ġh ết",
+      "ĠÄij a",
+      "à¹Ģà¸Ķà¹ĩ à¸ģ",
+      "íĺ ķ",
+      "l ÃŃ",
+      "ê¸ ī",
+      "Ġع دد",
+      "ĠÄij á»ĵ",
+      "Ġg ần",
+      "Ġ×Ļ ×ķ×Ŀ",
+      "Ġs Ä©",
+      "ÑĢ Ñıд",
+      "Ġquy á»ģn",
+      "Ġ×IJ ׾×IJ",
+      "Ùĩ Ùħا",
+      "׳ ×Ļ×Ķ",
+      "׾ ×ķת",
+      "Ġ×Ķר ×ij×Ķ",
+      "Ġti ên",
+      "Ġal ın",
+      "Ġd á»ħ",
+      "人 ãģĮ",
+      "но Ñģ",
+      "л ÑģÑı",
+      "ĠÄij Æ°a",
+      "ส าว",
+      "иÑĢов ан",
+      "Ġ×ŀס פר",
+      "×Ĵ ף",
+      "Ġki ến",
+      "ĠÐ ¨",
+      "p é",
+      "б Ñĥ",
+      "ов ой",
+      "б а",
+      "ĠØ¥ ÙĦا",
+      "×IJ ׾×Ļ",
+      "Ġx ây",
+      "Ġb ợi",
+      "Ġש ×ķ",
+      "人 ãģ®",
+      "ק ×Ļ×Ŀ",
+      "à¹Ģà¸Ķ ืà¸Ńà¸Ļ",
+      "Ġkh á",
+      "Ġ×ķ ׾×Ķ",
+      "×ĵ ×ķת",
+      "Ġ×¢ ×ij×ķר",
+      "Ġبش ÙĥÙĦ",
+      "ĠÙĩÙĨا Ùĥ",
+      "ÑĤ ÑĢа",
+      "Ġ íķĺëĬĶ",
+      "ร à¸Ńà¸ļ",
+      "owa ÅĤ",
+      "h é",
+      "Ġdi á»ħn",
+      "Ġ×Ķ ׼׾",
+      "ĠØ£ س",
+      "Ġch uyá»ĩn",
+      "ระ à¸Ķัà¸ļ",
+      "ĠNh ững",
+      "Ġ×IJ ×Ĺת",
+      "ĠØŃ ÙĪÙĦ",
+      "л ов",
+      "׳ ר",
+      "Ġ×ķ ׳",
+      "Ġch Æ¡i",
+      "Ġiç inde",
+      "ÑģÑĤв Ñĥ",
+      "Ġph á»ij",
+      "ĠÑģ Ñĥ",
+      "ç§ģ ãģ¯",
+      "Ġch ứng",
+      "Ġv á»±c",
+      "à¹ģ à¸Ń",
+      "Ġl áºŃp",
+      "Ġtừ ng",
+      "å°ij ãģĹ",
+      "ĠNg uy",
+      "ĠNguy á»ħn",
+      "ĠÙģÙĬ Ùĩ",
+      "Ġб а",
+      "×Ļ ×Ļת",
+      "Ġ×ľ×¢ ש×ķת",
+      "Ġ×ŀ ׼",
+      "Ġnghi á»ĩm",
+      "Ġм ного",
+      "Ġе е",
+      "ëIJĺ ìĸ´",
+      "Ġl ợi",
+      "Ġ׾ ׾×IJ",
+      "Ġ׼ ף",
+      "Ġch ÃŃ",
+      "ãģ§ ãģ®",
+      "×Ĺ ×ķ",
+      "ש ×ķ×Ŀ",
+      "Ġ×ŀ ר",
+      "ĠÐĶ лÑı",
+      "Å ģ",
+      "Ġ׼×IJ שר",
+      "ĠM á»Ļt",
+      "ĠÙĪاÙĦ ت",
+      "ĠìĿ´ 룰",
+      "ÅŁ a",
+      "Ġchi ến",
+      "Ġaras ında",
+      "Ġ×ij ×IJתר",
+      "ãģķãĤĮ ãģ¦ãģĦãĤĭ",
+      "Ø´ ÙĥÙĦ",
+      "Ġt ượng",
+      "Ġت ت",
+      "ĠC ó",
+      "Ġb á»ı",
+      "Ġtá»ī nh",
+      "Ġkh ÃŃ",
+      "ĠпÑĢ оÑģÑĤ",
+      "ĠпÑĢоÑģÑĤ о",
+      "ĠÙĪ ÙĤاÙĦ",
+      "Ġgi áo",
+      "ĠN ếu",
+      "×IJ ×ŀר",
+      "×¢×ł×Ļ ×Ļף",
+      "íİ ¸",
+      "Ùĩد Ùģ",
+      "ĠB á»Ļ",
+      "Ġb Ãłn",
+      "Ġng uyên",
+      "Ġgü zel",
+      "ส าย",
+      "ì² ľ",
+      "×ŀ ×ķר",
+      "Ġph ân",
+      "ס פק",
+      "ק ×ij׾",
+      "ĠاÙĦÙħ تØŃ",
+      "ĠاÙĦÙħتØŃ Ø¯Ø©",
+      "ائ د",
+      "Ġ×IJ ×ŀר",
+      "Ġki ÅŁi",
+      "ì¤ Ģ",
+      "Ġtr uyá»ģn",
+      "ĠÙĦ Ùĩا",
+      "ĠÐľ а",
+      "à¸ļริ ษ",
+      "à¸ļริษ ั",
+      "à¸ļริษั à¸Ĺ",
+      "Ġש ׳×Ļ×Ŀ",
+      "Ġмен Ñı",
+      "ÅŁ e",
+      "Ġdi á»ĩn",
+      "Ġ×IJ׳ ×Ĺ׳×ķ",
+      "k ü",
+      "Ġc á»ķ",
+      "Ġm á»Ĺi",
+      "w ä",
+      "Ùħ ÙĬ",
+      "Ġhi á»ĥu",
+      "ëĭ ¬",
+      "Ġ×Ķ ×Ĺ׾",
+      "Ġt ên",
+      "Ġki á»ĩn",
+      "ÙĨ ÙĤÙĦ",
+      "Ġv á»ĩ",
+      "×ĵ ת",
+      "ĠÐłÐ¾ÑģÑģ ии",
+      "л Ñĥ",
+      "ĠاÙĦع ربÙĬØ©",
+      "ĠØ· رÙĬÙĤ",
+      "Ġ×Ķ×ij ×Ļת",
+      "Ñģ еÑĢ",
+      "Ġм не",
+      "ä u",
+      "Ġtri á»ĩu",
+      "ĠÄij ủ",
+      "Ġר ×ij",
+      "ت ÙĩÙħ",
+      "à¸ĭ ี",
+      "Ġì§Ģ ê¸Ī",
+      "li ÅĽmy",
+      "د عÙħ",
+      "ãģł ãĤįãģĨ",
+      "Ñģки е",
+      "Ġh á»ıi",
+      "Ġק ×ķ",
+      "ÑĢÑĥ Ñģ",
+      "ÙĨ ظر",
+      "ãģ® ãĤĤ",
+      "Ġ×Ķ ׼×Ļ",
+      "ĠìĽ IJ",
+      "ÙĪ Ùĩ",
+      "ĠÙĪ Ùİ",
+      "ĠB ạn",
+      "п лаÑĤ",
+      "Ġ×ŀ ×ŀש",
+      "лÑİ Ð±",
+      "ĠнÑĥж но",
+      "Ġth Æ°",
+      "ãģ µ",
+      "ãģı ãĤīãģĦ",
+      "ر ش",
+      "ר ×ķ×Ĺ",
+      "ĠÙĬ تÙħ",
+      "Ġצר ×Ļ×ļ",
+      "Ġph á",
+      "ม à¸Ńà¸ĩ",
+      "Ġ×ij×IJ ×ķפף",
+      "Ġcả nh",
+      "Ġíķľ ëĭ¤",
+      "Ġ×Ķ×ŀ ת",
+      "à¸ķà¹Īาà¸ĩ à¹Ĩ",
+      "มี à¸ģาร",
+      "Ñģки Ñħ",
+      "ĠÐĴ Ñģе",
+      "Ġا ÙĪ",
+      "ج ÙĬ",
+      "ãģĵãģ¨ ãģ¯",
+      "Ġd Ãłi",
+      "Ġh á»ĵ",
+      "èĩªåĪĨ ãģ®",
+      "à¹Ħ หà¸Ļ",
+      "ëĵ¤ ìĿĦ",
+      "ĠV Äĥn",
+      "Ġд аж",
+      "Ġдаж е",
+      "Ñĭ ми",
+      "лаÑģ ÑĮ",
+      "ÙĬ ÙĪÙĨ",
+      "ÙĨ ÙĪ",
+      "c ó",
+      "ãģĹãģ¦ ãģĦãģŁ",
+      "ãģł ãģĭãĤī",
+      "طاÙĦ ب",
+      "Ġc á»Ńa",
+      "п ÑĢоÑģ",
+      "ãģªãģ© ãģ®",
+      "รุ à¹Īà¸Ļ",
+      "Ġchi ếc",
+      "л Ñĭ",
+      "ĠÑıвлÑı еÑĤÑģÑı",
+      "Ġn á»ķi",
+      "ãģ® ãģĬ",
+      "Ġ×IJת ×Ŀ",
+      "ĠëķĮ문 ìĹIJ",
+      "à¸ģล าà¸ĩ",
+      "ĠbaÅŁ ka",
+      "ìĦ Ŀ",
+      "ĠÑĨ ел",
+      "Ùģ ÙĤ",
+      "ãģ«ãĤĪ ãĤĭ",
+      "ÙĤ ا",
+      "Ġçı kar",
+      "Ġcứ u",
+      "ط ا",
+      "Ġש ת",
+      "à¹Ĥ à¸Ħ",
+      "Ġ×ŀ ׾",
+      "Ġ×Ķ פר",
+      "Ġг де",
+      "ĠØ® Ø·",
+      "åīį ãģ«",
+      "c jÄĻ",
+      "Ġ׊ש×ķ×ij",
+      "ר×Ĵ ×¢",
+      "Ġkho ảng",
+      "ĠÄij á»Ŀi",
+      "ĠÐł е",
+      "Ġо на",
+      "Ġ×IJ ׳×ķ",
+      "ãģ® ãģ«",
+      "ĠاÙĦØ° ÙĬÙĨ",
+      "кÑĥ п",
+      "ãĤµ ãĥ¼ãĥ",
+      "ãĤµãĥ¼ãĥ ĵ",
+      "ãĤµãĥ¼ãĥĵ ãĤ¹",
+      "в ал",
+      "г е",
+      "Ġgi ữa",
+      "ĠKh ông",
+      "ĠâĹ ĭ",
+      "à¸ģล ุà¹Īม",
+      "ĠÙħÙĨ Ø°",
+      "à¸Ń à¹Īาà¸Ļ",
+      "ĠÑģп оÑģоб",
+      "ĠÄij á»Ļi",
+      "Ġdi ÄŁer",
+      "Ġ à¸ĸà¹īา",
+      "Ùħ Ø«ÙĦ",
+      "Ġ×Ķ×IJ ×Ļ",
+      "Ġد ÙĪÙĨ",
+      "ÙĬر اÙĨ",
+      "Ñī и",
+      "بÙĨ اء",
+      "ĠØ¢ خر",
+      "ظ Ùĩر",
+      "Ġ×ij ׼",
+      "ĠاÙĦÙħ ع",
+      "ãĥ Ĵ",
+      "Ġt ất",
+      "Ġm ục",
+      "ĠdoÄŁ ru",
+      "ãģŁ ãĤī",
+      "Ġס ×ķ",
+      "Ġx ác",
+      "ร à¸Ń",
+      "ĠcÄĥ n",
+      "Ġон л",
+      "Ġонл айн",
+      "Ġk ý",
+      "Ġch ân",
+      "Ġ à¹Ħมà¹Ī",
+      "اØŃ Ø©",
+      "r án",
+      "׳×Ļ ×Ļ×Ŀ",
+      "Ġ×ij ף",
+      "ĠÐ ĸ",
+      "à¸ķร à¸ĩ",
+      "д Ñĭ",
+      "Ġs ắc",
+      "ÙĦ ت",
+      "ãĥŃ ãĥ¼",
+      "ĠÙĦ ÙĨ",
+      "Ġר ×ķ",
+      "Ġd Æ°á»Ľi",
+      "à¹Ģ à¸ĺ",
+      "à¹Ģà¸ĺ à¸Ń",
+      "e ÄŁi",
+      "Ġ×ķ ש",
+      "ĠÙĦ Ø£",
+      "Ġg ặp",
+      "Ġc á»ij",
+      "ãģ¨ ãģ¦ãĤĤ",
+      "رÙĪ س",
+      "Ġ׾×Ķ ×Ļ",
+      "Ġë³ ¸",
+      "ä¸Ĭ ãģĴ",
+      "Ġm ức",
+      "Ñħ а",
+      "Ġìŀ ¬",
+      "à¸ī ัà¸Ļ",
+      "ÑĢÑĥ ж",
+      "Ġaç ık",
+      "ÙĪ اÙĦ",
+      "Ġ×ĸ ×ŀף",
+      "人 ãģ¯",
+      "ع ÙĬÙĨ",
+      "Ñı Ñħ",
+      "Ġ×Ĵ×ĵ ×ķ׾",
+      "ר ×ķ×ij",
+      "g ó",
+      "ëĿ¼ ê³ł",
+      "Ġark adaÅŁ",
+      "ÙĨ شر",
+      "Ġгод Ñĥ",
+      "ĠболÑĮ ÑĪе",
+      "ãģ¡ãĤĩ ãģ£ãģ¨",
+      "Ġcâ u",
+      "Ġs át",
+      "íĶ ¼",
+      "Ġti ến",
+      "íķ´ ìķ¼",
+      "ĠÙĪ Ø£ÙĨ",
+      "à¸Ļ าà¸Ļ",
+      "Ġ×ij×IJ×ŀ צע",
+      "Ġ×ij×IJ×ŀצע ×ķת",
+      "Ġ׾ ר",
+      "Ġqu ản",
+      "ĠÙĪاÙĦ Ø£",
+      "Ġ×IJ×ķת ×Ķ",
+      "Ġìĸ´ëĸ ¤",
+      "Ġê²ĥ ìĿĢ",
+      "ØŃس ÙĨ",
+      "Ġm ất",
+      "à¸Ħ ูà¹Ī",
+      "ãĥ¬ ãĥ¼",
+      "ĠÐĶ а",
+      "Ġol ması",
+      "Ġthu á»Ļc",
+      "׳ ×Ĺ",
+      "íĨ ł",
+      "Ġsö yle",
+      "ãģĿãģĨ ãģ§ãģĻ",
+      "Ġت ÙĥÙĪÙĨ",
+      "л ÑĥÑĩ",
+      "׾ ×Ļ×ļ",
+      "ĠØ£ ØŃد",
+      "ли ÑģÑĮ",
+      "ĠвÑģ его",
+      "Ġ×Ķר ×ij",
+      "Ġëª »",
+      "o ÄŁ",
+      "oÄŁ lu",
+      "ĠìĦ ł",
+      "Ġк аÑĢ",
+      "à¸łà¸² à¸Ħ",
+      "e ÅĦ",
+      "Ġ à¸ģà¹ĩ",
+      "Ġa ynı",
+      "Ġb Ãł",
+      "ãģªãĤĵ ãģ¦",
+      "Ġ모 ëĵł",
+      "ÙĤر ار",
+      "ãģĹãģª ãģĦ",
+      "ĠÐĴ о",
+      "ĠÙĪÙĩ ÙĬ",
+      "ни ки",
+      "ãĤĮ ãģŁ",
+      "Ġchu ẩn",
+      "ר ע",
+      "Ùģ رÙĬÙĤ",
+      "ãĤĴ åıĹãģij",
+      "ĠÄij úng",
+      "б е",
+      "׼ ×ķ×Ĺ",
+      "п Ñĥ",
+      "Ġ×ķ ×Ĵ×Ŀ",
+      "×ŀ ׳×Ļ",
+      "íĸ ¥",
+      "צ ×Ļ×Ŀ",
+      "à¸ĭ ิ",
+      "Ùĩ ÙĨ",
+      "н ем",
+      "Ġ×ij×ij ×Ļת",
+      "ر ع",
+      "Ġ ส",
+      "ĠÄIJ Ãł",
+      "íķĺ ëĭ¤",
+      "Ġ ấy",
+      "×Ĺ ×ķ×ĵ",
+      "×Ĺ×ķ×ĵ ש",
+      "ĠÑĩеÑĢ ез",
+      "Ñĥ л",
+      "ĠB ình",
+      "Ġê²ĥ ìĿĦ",
+      "Ġ×Ĵ ר",
+      "ä»ĺ ãģij",
+      "×Ĺ׾ ק",
+      "Ġت ÙĦÙĥ",
+      "à¹ĥส à¹Ī",
+      "sz Äħ",
+      "ÙĤ اÙħ",
+      "د ÙĪر",
+      "ĠÙģ ÙĤØ·",
+      "Ġh ữu",
+      "Ġмог ÑĥÑĤ",
+      "Ġg á»įi",
+      "Ġק ר",
+      "à¸Īะ มี",
+      "ت ÙĤدÙħ",
+      "Ġع بر",
+      "Ġ׾×Ķ ×Ŀ",
+      "ĠÑģам о",
+      "ס ×ĵר",
+      "Ġc Ãłng",
+      "r ÃŃ",
+      "Ġìŀ ¥",
+      "ëĵ¤ ìĿĺ",
+      "ĠÙĦ Ùĥ",
+      "п оÑĢÑĤ",
+      "Ġkh ả",
+      "ĠÑģеб Ñı",
+      "׳ ף",
+      "Ġد ÙĪر",
+      "Ġm ợ",
+      "Ġcâ y",
+      "Ġf ark",
+      "Ġfark lı",
+      "а ÑİÑĤ",
+      "Ġtr á»±c",
+      "wiÄĻks z",
+      "Ġthu á»ijc",
+      "Ġت ØŃت",
+      "ت ÙĦ",
+      "ов Ñĭе",
+      "ëĤ ł",
+      "Ġв ам",
+      "بÙĦ غ",
+      "Ġê°Ļ ìĿĢ",
+      "íĮ IJ",
+      "ÙĦ ب",
+      "Ġnas ıl",
+      "Ġод ин",
+      "м ан",
+      "ĠعÙĦÙĬ Ùĩا",
+      "б и",
+      "Ġפ ש×ķ×ĺ",
+      "×ijר ×Ļ",
+      "Ġש ׳×Ķ",
+      "Ġëı Ħ",
+      "ĠÄIJ ại",
+      "Ġ×IJ×ķת ×Ŀ",
+      "ĠاÙĦØŃ Ø±",
+      "Ġб о",
+      "à¸Ī ุà¸Ķ",
+      "Ġr õ",
+      "ĠdeÄŁi ÅŁ",
+      "Ġëĭ ¨",
+      "ĠÑģлÑĥÑĩ а",
+      "ĠÑģлÑĥÑĩа е",
+      "Ġ×IJ׳ ש×Ļ×Ŀ",
+      "×ĵ ×£",
+      "ש×ij ת",
+      "Ġש׾ ׼×Ŀ",
+      "Ġch ú",
+      "nik ów",
+      "Ġtan ı",
+      "Ġcá o",
+      "ĠÄij á",
+      "Ġ×IJ ×ĵ×Ŀ",
+      "Ġê° ķ",
+      "Ġnhi á»ĩm",
+      "Ġ׾ ס",
+      "Ġ×Ľ×ª ×ij",
+      "Ġ×Ķס פר",
+      "ĠÄij Äĥng",
+      "Ġë ijIJ",
+      "à¸ľ ิ",
+      "à¸ľà¸´ ว",
+      "ج ا",
+      "Ġê° IJ",
+      "ر أ",
+      "ست خدÙħ",
+      "ãģ«ãģªãĤĬ ãģ¾ãģĻ",
+      "Ġtá» ·",
+      "×ĺ ×ķר",
+      "г овоÑĢ",
+      "Ġв оÑģ",
+      "ĠÙħÙĨ Ùĩا",
+      "иÑĢов аÑĤÑĮ",
+      "ĠÄij ầy",
+      "׳ ×Ĵ",
+      "ĠÙħ ÙĪ",
+      "ĠÙħ ÙĪÙĤع",
+      "ר׼ ×Ļ",
+      "ت Ùı",
+      "ëª ¨",
+      "Ġת ×ķ",
+      "ÙĬا Ùĭ",
+      "à¹ĥ à¸Ķ",
+      "ãĤĬ ãģ¾ãģĻ",
+      "à¸Ńยูà¹Ī à¹ĥà¸Ļ",
+      "ĠØ£ ÙĪÙĦ",
+      "ĠØ£ خرÙī",
+      "Ġc Æ°",
+      "ص ار",
+      "×ŀ׊ש×ij",
+      "б ÑĢа",
+      "ÅĦ ski",
+      "б ÑĢ",
+      "ĠÙĬ Ùı",
+      "à¸ģ ิà¸Ļ",
+      "Ġch á»ijng",
+      "Ùħ Ùı",
+      "Ġ à¸Ħืà¸Ń",
+      "Ġت ÙĨ",
+      "t ÃŃ",
+      "y Äĩ",
+      "Ġm ạng",
+      "Ùģ ÙĪ",
+      "Ġdü nya",
+      "ק ר×IJ",
+      "Ġק ׾",
+      "ĠØŃ Ø§ÙĦ",
+      "c ÃŃa",
+      "Ġà¹Ģ รา",
+      "Ġר ×ķצ×Ķ",
+      "Ġá p",
+      "ë° ķ",
+      "ا ÙĤØ©",
+      "ни Ñİ",
+      "Ġ×IJ ׾×ķ",
+      "Ġ×ŀס ×ķ",
+      "ãģ§ãģ¯ ãģªãģı",
+      "Ġtr ả",
+      "Ġק שר",
+      "mi ÅŁtir",
+      "Ġl Æ°u",
+      "Ġh á»Ĺ",
+      "ĠбÑĭ ли",
+      "Ġl ấy",
+      "عÙĦ Ùħ",
+      "Ġö zel",
+      "æ°Ĺ ãģĮ",
+      "Ġ×ĵ ר×ļ",
+      "Ùħ د",
+      "s ını",
+      "׳ ×ķש×IJ",
+      "r ów",
+      "Ñĩ еÑĢ",
+      "êµIJ ìľ¡",
+      "ĠÐľ о",
+      "л ег",
+      "ĠV Ỽi",
+      "วัà¸Ļ à¸Ļีà¹ī",
+      "ÑİÑī ие",
+      "ãģĬ ãģĻ",
+      "ãģĬãģĻ ãģĻ",
+      "ãģĬãģĻãģĻ ãĤģ",
+      "ëı ħ",
+      "Ġ×Ļ×Ķ ×Ļ×Ķ",
+      "×ŀ ×ĺר",
+      "Ñı ми",
+      "Ġl á»±a",
+      "ĠÄij ấu",
+      "à¹Ģส ียà¸ĩ",
+      "Ġt Æ°Æ¡ng",
+      "ëĵ ±",
+      "ĠÑģÑĤ аÑĢ",
+      "à¹ĥ à¸ļ",
+      "ว ัà¸Ķ",
+      "ĠÄ° stanbul",
+      "Ġ à¸Īะ",
+      "à¸ķ ลาà¸Ķ",
+      "Ġب ÙĬ",
+      "à¹ģà¸Ļ ะ",
+      "à¹ģà¸Ļะ à¸Ļำ",
+      "س اعد",
+      "Ġب Ø£",
+      "Ġki á»ĥm",
+      "ØŃ Ø³Ø¨",
+      "à¸Ĭั à¹īà¸Ļ",
+      "Ġ×ķ ×¢×ķ×ĵ",
+      "ов ÑĭÑħ",
+      "оÑģ нов",
+      "Ġtr Æ°á»Łng",
+      "צ ×ij×¢",
+      "ĠÃŃ t",
+      "Ġk ỹ",
+      "cr é",
+      "Ñı м",
+      "êµ °",
+      "ãģĮ ãģªãģĦ",
+      "ÙĬÙĦ Ø©",
+      "ãĥķ ãĤ£",
+      "ر Ùī",
+      "ĠÙĬ جب",
+      "Ġ×IJ ×£",
+      "Ġc á»±c",
+      "ãĤīãĤĮ ãģŁ",
+      "Ġ à¸ľà¸¹à¹ī",
+      "Ġ à¸Ń",
+      "lar ımız",
+      "Ġkad ın",
+      "Ġê·¸ ëŀĺ",
+      "Ġê·¸ëŀĺ ìĦľ",
+      "ĠëĺIJ ëĬĶ",
+      "ĠÄij ả",
+      "ĠÄijả m",
+      "Ġ×IJ ×ķ×ŀר",
+      "Ġy ếu",
+      "ci Äħ",
+      "ciÄħ g",
+      "Ġt á»ij",
+      "Ġש×IJ ׳×Ļ",
+      "Ġdz iaÅĤa",
+      "Ñī а",
+      "ĠÄij Ãłn",
+      "s ına",
+      "ãģĵãĤĮ ãģ¯",
+      "Ġ×ij ׾×Ļ",
+      "Ġ×ij ×Ļשר×IJ׾",
+      "л оÑģÑĮ",
+      "Ġgi ữ",
+      "ê° IJ",
+      "ÑĢ он",
+      "تج ار",
+      "г лав",
+      "в ин",
+      "Ġh ạn",
+      "Ġyapı lan",
+      "ب س",
+      "Ġ à¸ŀรà¹īà¸Ńม",
+      "ê´Ģ 리",
+      "mÄ±ÅŁ tır",
+      "b ü",
+      "r ück",
+      "ĠBaÅŁkan ı",
+      "ĠÙĦ ÙĬس",
+      "Ġs Æ¡",
+      "à¸Īัà¸ĩ หว",
+      "à¸Īัà¸ĩหว ัà¸Ķ",
+      "د اء",
+      "Ġ×Ķ ׼",
+      "v ÃŃ",
+      "ש ×IJר",
+      "Ġh Æ°á»Łng",
+      "Ġb óng",
+      "ĠCh ÃŃnh",
+      "Äħ c",
+      "à¹Ģà¸ģีà¹Īยว à¸ģัà¸ļ",
+      "Ġtá» ©",
+      "Ġtứ c",
+      "ĠÑĨ веÑĤ",
+      "Ġt á»iji",
+      "ĠnghÄ© a",
+      "ÙĦا عب",
+      "د ÙĦ",
+      "Ġפע ×Ŀ",
+      "h ör",
+      "à¸Ĭ ุà¸Ķ",
+      "à¸ŀ ู",
+      "à¸ŀู à¸Ķ",
+      "п аÑģ",
+      "ĠÅŁ u",
+      "Ġt Æ°á»Łng",
+      "خار ج",
+      "Ġâ m",
+      "ĠинÑĤеÑĢ еÑģ",
+      "ен нÑĭÑħ",
+      "×IJ ׳×Ļ",
+      "بد أ",
+      "ëĿ¼ ëĬĶ",
+      "ì¹ ´",
+      "æĸ¹ ãģĮ",
+      "ли в",
+      "Ġ à¸Ħà¸Ļ",
+      "ער ×ļ",
+      "à¸Ĥà¸Ńà¸ĩ à¸Ħุà¸ĵ",
+      "п ад",
+      "Ġc ạnh",
+      "ĠëĤ ¨",
+      "ĠÄij âu",
+      "Ġbi á»ĥu",
+      "ãĤĤ ãģĤãĤĭ",
+      "׾ ×Ĵ",
+      "Ġ สำหรัà¸ļ",
+      "Ġxu á»ijng",
+      "ס ×ķ",
+      "ĠØ° ات",
+      "ĠÐľ е",
+      "ع اÙĦÙħ",
+      "×IJ ס",
+      "ب ÙĬØ©",
+      "ش ا",
+      "и ем",
+      "ĠNg Æ°á»Ŀi",
+      "íĺ ij",
+      "Ñģл ов",
+      "Ġп а",
+      "Ġm ẫu",
+      "ĠпÑĢоÑĨ еÑģÑģ",
+      "ĠNh Ãł",
+      "пÑĢо из",
+      "пÑĢоиз вод",
+      "à¸łà¸²à¸¢ à¹ĥà¸Ļ",
+      "Ġ à¸ļาà¸Ĺ",
+      "×ŀ ׳×ķ",
+      "ĠоÑĢг ан",
+      "רצ ×ķ",
+      "×ķ×ŀ ×Ļ×Ŀ",
+      "Ġyaz ı",
+      "Ġd ù",
+      "ãĥ¬ ãĥ³",
+      "ÙĪÙĦ ÙĬ",
+      "ย ู",
+      "Ġtr ò",
+      "à¹Ģà¸ŀ ลà¸ĩ",
+      "Ġ×ŀ ׾×IJ",
+      "à¸ķ ล",
+      "à¸ķล à¸Ńà¸Ķ",
+      "ĠÄij ạt",
+      "Ġ×Ĺ×ĵ ש",
+      "p óÅĤ",
+      "Ġ×ŀ ×ĵ×Ļ",
+      "ujÄħ c",
+      "×ŀ׳×Ķ ׾",
+      "Ġש×ij ×ķ",
+      "Ġ×Ķ×ŀש פ×ĺ",
+      "Ġ×IJ ׾×Ķ",
+      "ĠÙĪ Ø°ÙĦÙĥ",
+      "à¹Ģà¸ŀ ราะ",
+      "ĠÄijo Ãłn",
+      "Ġíķ¨ ê»ĺ",
+      "Ġd ục",
+      "ش ت",
+      "Ġ ula",
+      "Ġula ÅŁ",
+      "Ġqu ý",
+      "Ġ×Ķ ×Ĵ×ĵ×ķ׾",
+      "à¸ķัà¹īà¸ĩ à¹ģà¸ķà¹Ī",
+      "Ġש ר",
+      "Ø´ Ùĩد",
+      "׳ ש×Ļ×Ŀ",
+      "à¸ŀ ล",
+      "رÙĪ ا",
+      "ãĤĮ ãģ¦",
+      "Ġн иÑħ",
+      "Ġдел а",
+      "ãģ§ãģį ãģªãģĦ",
+      "ÅĤo ż",
+      "×IJ ×Ĺר",
+      "ì ½Ķ",
+      "ãĤ¢ ãĥĥãĥĹ",
+      "د Ùģع",
+      "Ġti á»ĩn",
+      "Ġkh á»ı",
+      "Ġkhá»ı e",
+      "ĠاÙĦع اÙħØ©",
+      "ãģ« ãģĤãĤĭ",
+      "ĠÄij á»Ļc",
+      "ì¡ ±",
+      "Ġc ụ",
+      "й ÑĤе",
+      "Ġзак он",
+      "ĠпÑĢо екÑĤ",
+      "ìĸ ¸",
+      "ÙĦ ØŃ",
+      "ĠçalÄ±ÅŁ ma",
+      "ãĤĴ ãģĻãĤĭ",
+      "Ñħ и",
+      "ع اد",
+      "Ġ׳ ×ŀצ×IJ",
+      "Ġר ×Ļ",
+      "à¸Ńà¸Ńà¸ģ มา",
+      "ĠT ôi",
+      "Ġth ần",
+      "ĠÙĬ ا",
+      "ล าย",
+      "Ġав ÑĤо",
+      "Ġsı ra",
+      "ĠÙĥ Ø«ÙĬر",
+      "Ùħ ÙĬز",
+      "ĠاÙĦع ÙĦÙħ",
+      "æĸ¹ ãģ¯",
+      "×ķ×¢ ×ĵ",
+      "Ġобла ÑģÑĤи",
+      "×Ļ׾ ×Ļ×Ŀ",
+      "ãģĮ åĩº",
+      "à¸ĺ ุ",
+      "à¸ĺุ ร",
+      "à¸ĺุร à¸ģิà¸Ī",
+      "ÙĤت ÙĦ",
+      "ר×IJ ×ķ",
+      "Ġng u",
+      "Ġngu á»ĵn",
+      "Ġ มา",
+      "Ġпл ан",
+      "t ório",
+      "Ġcu á»iji",
+      "Ñģк ом",
+      "ĠاÙĦÙħ اض",
+      "ĠاÙĦÙħاض ÙĬ",
+      "Ġ×ij×¢ ׾",
+      "Ġר ×ij×Ļ×Ŀ",
+      "Ġlu áºŃn",
+      "Ùĥ ÙĪ",
+      "à¸Ĺัà¹īà¸ĩ หมà¸Ķ",
+      "в ан",
+      "Ġtho ại",
+      "à¹Ħ à¸Ń",
+      "б иÑĢ",
+      "ĠاÙĦ ض",
+      "ت ا",
+      "ĠÑĢ од",
+      "ĠV Ãł",
+      "×ŀ ×Ļף",
+      "ĠбÑĭ ла",
+      "к ами",
+      "ĠÐĶ е",
+      "t ık",
+      "קר ×Ļ",
+      "ĠeÄŁ itim",
+      "ĠÙĥ بÙĬر",
+      "ب Ùĥ",
+      "ĠÙĦ ÙĪ",
+      "в ой",
+      "Ġ ãģĵãģ®",
+      "ĠÑĤ ÑĢÑĥд",
+      "my ÅĽl",
+      "Ġs Æ°",
+      "à¸ŀ ีà¹Ī",
+      "Ġ à¹ģลà¹īว",
+      "ע ק",
+      "Ġ×Ĺ×ijר ת",
+      "ระ หว",
+      "ระหว à¹Īาà¸ĩ",
+      "×Ļ ×Ļ×Ķ",
+      "ĠاÙĦÙĨ اس",
+      "ün ü",
+      "Ġ׾ ×ŀ×Ķ",
+      "Ġch Æ°Æ¡ng",
+      "ĠH á»ĵ",
+      "ار ت",
+      "ãĤĪãģĨ ãģ§ãģĻ",
+      "l á",
+      "ק×Ļ ×Ļ×Ŀ",
+      "æľ¬ å½ĵ",
+      "æľ¬å½ĵ ãģ«",
+      "ãģĵãĤĵ ãģª",
+      "Ñģ ов",
+      "Ġ×ķ ×Ĺ",
+      "à¹Ģà¸ģ à¹ĩà¸ļ",
+      "Ġк ÑĤо",
+      "à¹Ĥร à¸Ħ",
+      "ĠØ´ رÙĥØ©",
+      "ع زÙĬ",
+      "عزÙĬ ز",
+      "Ø·ÙĦ ÙĤ",
+      "п ÑĥÑģÑĤ",
+      "Ùģ تØŃ",
+      "ëŀ Ģ",
+      "Ġhã y",
+      "ض Ùħ",
+      "ë¦ °",
+      "åł´åIJĪ ãģ¯",
+      "ãĤª ãĥ¼",
+      "Ġh ắn",
+      "Ġ×IJ ×ij×Ļ×ij",
+      "Ġש׾×Ķ ×Ŀ",
+      "Ġ×Ķ×Ļ ×Ļת×Ķ",
+      "ĠاÙĦد ÙĪÙĦØ©",
+      "ĠاÙĦ ÙĪÙĤ",
+      "ĠاÙĦÙĪÙĤ ت",
+      "ãģĤ ãģ¾ãĤĬ",
+      "Ġta ÅŁÄ±",
+      "Ä° N",
+      "ע סק",
+      "ãģ¦ ãģĦãģŁ",
+      "Ġtá»ķ ng",
+      "ĠاÙĦØ¥ ÙĨس",
+      "ĠاÙĦØ¥ÙĨس اÙĨ",
+      "ÑĢ еÑĪ",
+      "Ġg ái",
+      "ĠÑĨ ен",
+      "ĠÙģ ÙĤد",
+      "Ùħ ات",
+      "ãģķãĤĵ ãģ®",
+      "Ġph ù",
+      "×ĺ ×Ķ",
+      "ĠÙĪاÙĦ تÙĬ",
+      "Ġب Ùĥ",
+      "ìĿ´ ëĤĺ",
+      "к Ñģ",
+      "Ùħ ÙĬر",
+      "Ġv ùng",
+      "ĠاÙĦØ´ عب",
+      "ĠNh Æ°ng",
+      "ãĥĢ ãĥ¼",
+      "Ġ×Ĺ×Ļ ×Ļ×Ŀ",
+      "ĠØ´ خص",
+      "ק ×ķ×ĵ",
+      "ê² Ģ",
+      "ע ש",
+      "×¢ ×ķ׾×Ŀ",
+      "צ ×ķר",
+      "ع ÙĤد",
+      "ĠiÅŁ lem",
+      "Ġ×Ķ×ij ×IJ",
+      "Ġd ưỡng",
+      "à¸Ł รี",
+      "Ġph ÃŃa",
+      "ãģ®ä¸Ń ãģ§",
+      "Ġп и",
+      "Ġng Ãłnh",
+      "ним а",
+      "ĠÙĩ ÙĦ",
+      "Ġ×ķ ×IJת",
+      "ĠÄij áng",
+      "é quipe",
+      "ĠÑįÑĤ оÑĤ",
+      "Ġgö rev",
+      "ë§ ¤",
+      "Ġqu ân",
+      "å¼ķ ãģį",
+      "æĻĤ ãģ«",
+      "Ġب Ùħا",
+      "×ŀ ×Ļת",
+      "Ġü lke",
+      "Ġ×ŀק ×ķ×Ŀ",
+      "×ij ף",
+      "æ°Ĺ æĮģãģ¡",
+      "Ġë§İ ìĿĢ",
+      "Ġyük sek",
+      "ÑĨ енÑĤÑĢ",
+      "ĠÙħ جÙĦس",
+      "ç§ģ ãģ®",
+      "ÙĤد ر",
+      "Ġë¶Ģ ë¶Ħ",
+      "Ġì° ¨",
+      "خر ج",
+      "ãģĭ ãģªãĤĬ",
+      "ë³´ ëĭ¤",
+      "Ġ×ŀ ×Ļ×ĵ×¢",
+      "peÅĤ ni",
+      "Ġx á»Ń",
+      "ìĹIJìĦľ ëĬĶ",
+      "ĠباÙĦ Ùħ",
+      "ĠÙĪ Ùħا",
+      "ĠÑįÑĤ ой",
+      "ب ÙĬÙĨ",
+      "n ü",
+      "ØŃ Ø²",
+      "ØŃز ب",
+      "ĠÑĢабоÑĤ а",
+      "ĠNh áºŃt",
+      "ÙĦ اء",
+      "Ġëĵ ¤",
+      "Ġëĵ¤ ìĸ´",
+      "ãĤĦãģĻ ãģĦ",
+      "×Ĺ×ĸ ק",
+      "Ġ×Ķ×Ĺ ×ijר×Ķ",
+      "п иÑĤ",
+      "ãģĭãĤī ãģ®",
+      "Ġë§IJ ìĶĢ",
+      "Ġפ ×ķ",
+      "ÙĦ Ùİ",
+      "à¹Ģà¸ķà¹ĩ ม",
+      "ĠÐļ о",
+      "Ġm ówi",
+      "Ġt ÃŃn",
+      "ר×Ĵ ש",
+      "פר ק",
+      "Ġtr ạng",
+      "ĠÐŀ н",
+      "×Ĺ ×ķ×¥",
+      "ĠعÙĨد Ùħا",
+      "Ġب ر",
+      "使 ãģĦ",
+      "Ġr á»Ļng",
+      "ëĮĢ ë¡ľ",
+      "íĪ ¬",
+      "Ġktóry ch",
+      "в ид",
+      "ลูà¸ģ à¸Ħà¹īา",
+      "Ġmog Äħ",
+      "Ġש ×Ĺ",
+      "×ij ×Ĺר",
+      "ãĥĸ ãĥŃãĤ°",
+      "ĠTh Ãłnh",
+      "Ġ×Ķ ר×Ļ",
+      "ĠÑģÑĤ аÑĤÑĮ",
+      "ĠH á»Ļi",
+      "à¸ļ à¹īาà¸ĩ",
+      "çī¹ ãģ«",
+      "ĠÄIJ ức",
+      "èĢħ ãģ®",
+      "×¢ ×ŀ×ķ×ĵ",
+      "×ĺר ×Ķ",
+      "Ð ¥",
+      "ĠÙħ Ùħا",
+      "Ġe ÅŁ",
+      "ĠнеобÑħодим о",
+      "ник ов",
+      "Ġüzer inde",
+      "a ÅĤa",
+      "Ġchá»ĭ u",
+      "ĠاÙĦ دÙĬÙĨ",
+      "أخ بار",
+      "ĠÄij au",
+      "ãģĮ å¤ļãģĦ",
+      "jÄħ cych",
+      "د Ø®ÙĦ",
+      "ları nd",
+      "larınd an",
+      "Ġs ẻ",
+      "à¸ŀิ à¹Ģศ",
+      "à¸ŀิà¹Ģศ ษ",
+      "ת ף",
+      "t ıģı",
+      "Ġlu áºŃt",
+      "ĠÅŀ e",
+      "ãĤ« ãĥ¼",
+      "ãģ® ãģĤãĤĭ",
+      "Ġ×Ķ×IJ תר",
+      "ĠاÙĦØ¢ ÙĨ",
+      "ıld ı",
+      "Ġá o",
+      "ĠнаÑĩ ал",
+      "Ġvi á»ĩn",
+      "Ġ×ij×¢ ×ķ׾×Ŀ",
+      "з наÑĩ",
+      "×Ļ×ĺ ×Ķ",
+      "к ам",
+      "ĠÐĺ з",
+      "à¹Ģà¸Ĥ ียà¸Ļ",
+      "à¸Ļ à¹īà¸Ńà¸ĩ",
+      "ÑĤ ÑĢо",
+      "à¹Ģ à¸Ł",
+      "Ġжиз ни",
+      "Ġ สà¹Īวà¸Ļ",
+      "Ġv áºŃn",
+      "Ġê´Ģ 볨",
+      "Ġl âu",
+      "ס ×ĺר",
+      "ק ש",
+      "س ÙĬر",
+      "Ġ×IJ×ķת ×Ļ",
+      "Ġm ôi",
+      "ائ ب",
+      "Ġо ÑģÑĤа",
+      "Ġm ón",
+      "Ġ×ij ×ŀק×ķ×Ŀ",
+      "Ġد اخÙĦ",
+      "Ġ×IJ ×ķר",
+      "Ġв аÑģ",
+      "Ùĥ Ø´Ùģ",
+      "ìĺ ¨",
+      "à¸ĸ à¹Īาย",
+      "Ġkullan ıl",
+      "Ġt ô",
+      "ãģ« ãĤĪãĤĬ",
+      "ĠëĺIJ íķľ",
+      "Ġ×¢×ij×ķ×ĵ ×Ķ",
+      "Ġri ê",
+      "Ġriê ng",
+      "Ġyak ın",
+      "ز ا",
+      "Å »",
+      "×IJ ×ķ׼׾",
+      "شار Ùĥ",
+      "Ġб еÑģ",
+      "× ´",
+      "Ġا بÙĨ",
+      "ĠTá»ķ ng",
+      "ÙĨ ظ",
+      "ÅĽwi ad",
+      "ãĤµ ãĥ¼",
+      "ห าย",
+      "ĠG ün",
+      "Ġhakk ında",
+      "à¹Ģà¸Ĥà¹īา มา",
+      "ز ÙĨ",
+      "ĠÐł о",
+      "Ġbi á»ĥn",
+      "ãģ© ãģĵ",
+      "Ùģ عÙĦ",
+      "ز ع",
+      "פר ×ĺ",
+      "Ġ×Ķ ף",
+      "Ø£ ÙĩÙĦ",
+      "Ġth ất",
+      "ØŃ ÙħÙĦ",
+      "Ñĩ Ñĥ",
+      "ĠìĤ¬ ìĭ¤",
+      "ì° ¸",
+      "ĠìľĦ íķ´",
+      "ÙĪ ظ",
+      "ĠÐŁ од",
+      "Ġkho ản",
+      "ÑĤ ен",
+      "ĠÙģ اÙĦ",
+      "Ñģ ад",
+      "à¸Ļ à¸Ńà¸Ļ",
+      "ĠاÙĦسعÙĪد ÙĬØ©",
+      "\" ØĮ",
+      "ĠاÙĦ ÙĴ",
+      "ãĤī ãģļ",
+      "Ġto án",
+      "Ġch ắc",
+      "׼ ×Ļר",
+      "m éd",
+      "méd ia",
+      "ز ÙĪ",
+      "Ġyan ı",
+      "פ ׳×Ļ×Ŀ",
+      "ØŃ Ø¸",
+      "Ġб еÑģп",
+      "ĠбеÑģп лаÑĤ",
+      "ĠбеÑģплаÑĤ но",
+      "ĠØ£ ÙħاÙħ",
+      "à¸Ń าย",
+      "à¸Ńาย ุ",
+      "ר שת",
+      "Ġg á»ĵ",
+      "Ġgá»ĵ m",
+      "Ġu á»ijng",
+      "ص ب",
+      "k ır",
+      "ãĥij ãĥ¼",
+      "Ġ׾×ĵ עת",
+      "Ġк ÑĥпиÑĤÑĮ",
+      "׾ ×ķ×Ĺ",
+      "ÙĪض ع",
+      "ÙĤÙĬ Ùħ",
+      "à¸Ľ า",
+      "ж ив",
+      "à¸Ķ ิà¸Ļ",
+      "×IJ ×ķפ",
+      "à¹Ģล à¹ĩà¸ģ",
+      "ãĥĥ ãĥī",
+      "иÑĩеÑģки Ñħ",
+      "ĠCh ủ",
+      "кÑĢ аÑģ",
+      "ÙĪ صÙĦ",
+      "p ÅĤat",
+      "м оÑĢ",
+      "Ġ×Ķ×IJ ×ķ",
+      "à¸Ń ิà¸Ļ",
+      "Ġíķľ êµŃ",
+      "гÑĢ е",
+      "Ġìłľ ê³µ",
+      "ì° ½",
+      "Ġê°ľìĿ¸ ìłķë³´",
+      "Ġngh á»ĭ",
+      "à¸ĭ า",
+      "ØŃس اب",
+      "Ġby ÅĤa",
+      "ÙħÙĦ Ùĥ",
+      "иÑĩеÑģки е",
+      "Ġb ác",
+      "ض ØŃ",
+      "ê¸ ¸",
+      "ש ×ŀ×¢",
+      "Ġìĸ´ëĸ »",
+      "Ġìĸ´ëĸ» ê²Į",
+      "ìĽ Į",
+      "ات Ùĩ",
+      "à¹Ĥรà¸ĩ à¹ģ",
+      "à¹Ĥรà¸ĩà¹ģ รม",
+      "خد ÙħØ©",
+      "ĠÐł а",
+      "׼×ķ׾ ×Ŀ",
+      "×ŀש ×Ĺק",
+      "ĠÙĪ ÙĥاÙĨ",
+      "ס ×ķ×£",
+      "ĠاÙĦØŃÙĥÙĪÙħ Ø©",
+      "Ġ×ij ×ĺ",
+      "Ġtr áºŃn",
+      "Ġ×Ķ×¢ ×ķ׾×Ŀ",
+      "ĠÃŃ ch",
+      "t Äħ",
+      "ש×ŀ ×ķ",
+      "Ġ×Ķר×IJש ×ķף",
+      "Ġíķĺ ê³ł",
+      "ãģķ ãĤī",
+      "ãģķãĤī ãģ«",
+      "ãģ« ãģĹãģ¦",
+      "Ġ à¸ľà¸¡",
+      "ãģ® ãĤĪãģĨãģª",
+      "ĠÙĪ ÙĤت",
+      "ãĥį ãĥĥãĥĪ",
+      "ÙĦ عب",
+      "ÙĪ Ø´",
+      "ìĺ ¬",
+      "Ġ หาà¸ģ",
+      "Ġm iaÅĤ",
+      "à¸Ĺ à¸Ńà¸ĩ",
+      "иÑĤ а",
+      "ا صر",
+      "ил ÑģÑı",
+      "з е",
+      "à¸Ľà¸£à¸° มาà¸ĵ",
+      "ãģĿãĤĮ ãģ¯",
+      "Ġb ır",
+      "Ġbır ak",
+      "صÙĨ اع",
+      "Ð ®",
+      "ش عر",
+      "Ġ׳ ×Ĵ×ĵ",
+      "Ġب سبب",
+      "ãĥĿ ãĤ¤",
+      "ãĥĿãĤ¤ ãĥ³ãĥĪ",
+      "ĠاÙĦج ÙĪ",
+      "ĠнеÑģк олÑĮко",
+      "Ġki ếm",
+      "Ùģ Ùİ",
+      "Ġض د",
+      "×ij×Ļ×ĺ ×ķ×Ĺ",
+      "تاب ع",
+      "ÙĨ ز",
+      "ĠB ản",
+      "Ġaç ıkl",
+      "Ġaçıkl ama",
+      "Ġ à¸Ħุà¸ĵ",
+      "à¸Ĺ า",
+      "ÅĤ ów",
+      "ط ب",
+      "ÙĨ ØŃÙĨ",
+      "Ġ×ŀק ×ķר",
+      "ĠÄ° s",
+      "Ġдом а",
+      "Ġ วัà¸Ļ",
+      "Ġd Ãłnh",
+      "Ñı н",
+      "ми ÑĢ",
+      "Ġm ô",
+      "ĠvÃł ng",
+      "ص اب",
+      "s ının",
+      "à¸Ħ ืà¸Ļ",
+      "خ بر",
+      "×ĸ׼ ×ķ",
+      "Ġ×ŀ ש×Ķ×ķ",
+      "m ü",
+      "Ġкомпани и",
+      "Ġ×Ķ×¢ ×Ļר",
+      "ĠÙĥ ÙĪ",
+      "ÙĤÙĦ ب",
+      "ĠlỼ p",
+      "и ки",
+      "׳ ×ij",
+      "à¹Ĥ à¸Ħร",
+      "à¹Ĥà¸Ħร à¸ĩ",
+      "à¹Ĥà¸Ħรà¸ĩ à¸ģาร",
+      "×ŀ×ķ×¢ ×ĵ",
+      "ÑıÑĤ ÑģÑı",
+      "หลัà¸ĩ à¸Īาà¸ģ",
+      "ени Ñİ",
+      "Ġש ×¢",
+      "Ġb Æ°á»Ľc",
+      "ãĥ¡ ãĥ¼ãĥ«",
+      "ãĤĦ ãĤĬ",
+      "Ġ×Ļ×ķ×ĵ ×¢",
+      "Ġê´Ģ íķľ",
+      "ĠاÙĦØ£ Ùħر",
+      "Ġböl ge",
+      "ĠÑģв ой",
+      "ÙĦ س",
+      "Ġ×ŀ×Ļ ×ķ×Ĺ×ĵ",
+      "ĠëĤ´ ìļ©",
+      "ĠØ£ جÙĦ",
+      "ĠÄIJ ông",
+      "Ġ×ŀ ×ł×ª",
+      "Ġìĭľ ê°Ħ",
+      "Ùĥ Ùİ",
+      "ãģ¨ãģĦãģĨ ãģ®ãģ¯",
+      "Ġnale ży",
+      "تÙĨظ ÙĬÙħ",
+      "ĠÑģозд а",
+      "Ġph é",
+      "Ġphé p",
+      "ãģ§ãģį ãģ¾ãģĻ",
+      "Ġع ÙĦÙħ",
+      "大ãģį ãģª",
+      "ãĤ² ãĥ¼ãĥł",
+      "í ħĮ",
+      "Ġ׼×ķ׾ ׾",
+      "ĠинÑĤеÑĢ неÑĤ",
+      "ĠT ừ",
+      "ãģ¨ ãģªãĤĭ",
+      "ز اÙĦ",
+      "Ġktóry m",
+      "Ġnh é",
+      "ìĪ ľ",
+      "н ев",
+      "д еÑĢ",
+      "ãĤ¢ ãĥĹãĥª",
+      "i á»ĩu",
+      "×ij ×Ļ׾",
+      "Ġت س",
+      "ĠÄIJ ây",
+      "ĠاÙĦØ® اصة",
+      "Ġà¹Ģ à¸Ĭ",
+      "Ġà¹Ģà¸Ĭ à¹Īà¸Ļ",
+      "ص اد",
+      "Ġd ạng",
+      "س عر",
+      "Ġש ×Ļ×ŀ×ķש",
+      "×Ĵ ×Ļ×Ŀ",
+      "ãģĮãģĤ ãģ£ãģŁ",
+      "п ÑĢов",
+      "пÑĢов од",
+      "Ġ×IJ ×Ļ׳×ķ",
+      "Ġ׾ ר×IJ",
+      "Ġ׾ר×IJ ×ķת",
+      "ĠØ£ ÙģضÙĦ",
+      "ĠØŃ ÙĦ",
+      "ĠØ£ بÙĪ",
+      "ê° ķ",
+      "Ġì§ ij",
+      "ãģ® ãĤĪãģĨãģ«",
+      "Ġפ ׳×Ļ",
+      "ס ×Ļ×Ŀ",
+      "ĠÙĪÙĩ ذا",
+      "Ġka ç",
+      "Ġé én",
+      "Ġê± ´",
+      "ë° Ķ",
+      "Ñĥ з",
+      "à¸Ĥà¸Ńà¸ĩ à¹Ģรา",
+      "i ÅĤ",
+      "ĠÐľ Ñĭ",
+      "Ġch ết",
+      "ĠاÙĦØ« اÙĨÙĬ",
+      "×IJ ק",
+      "Ġ×ķ ×¢×ľ",
+      "ĠاÙĦØ· ب",
+      "×ij×ĺ ×Ĺ",
+      "Ġج دÙĬدة",
+      "Ġع دÙħ",
+      "ع ز",
+      "สิà¹Īà¸ĩ à¸Ĺีà¹Ī",
+      "ãģĻ ãĤĮãģ°",
+      "ĠÄij ô",
+      "ì£ ł",
+      "د ÙĤ",
+      "н омÑĥ",
+      "Ġk á»ĥ",
+      "ãĤ¢ ãĥ³",
+      "å¤ļãģı ãģ®",
+      "à¸Ľà¸£à¸° à¸ģ",
+      "à¸Ľà¸£à¸°à¸ģ à¸Ńà¸ļ",
+      "פע×Ļ׾ ×ķת",
+      "ĠÑģÑĤ ол",
+      "may ı",
+      "ãģ¤ ãģĦ",
+      "Ġyılı nda",
+      "Ġ à¸Īึà¸ĩ",
+      "koÅĦ cz",
+      "ĠTh ông",
+      "Ġак ÑĤив",
+      "н ÑģÑĤ",
+      "нÑģÑĤ ÑĢÑĥ",
+      "ĠÃĸ z",
+      "Ġת ×ŀ×Ļ×ĵ",
+      "ĠÙĥ ÙĨت",
+      "Ñģ иÑģÑĤем",
+      "pr és",
+      "prés ent",
+      "Ġn â",
+      "Ġnâ ng",
+      "gÅĤ os",
+      "ĠÙĪز ÙĬر",
+      "ØŃ ØµÙĦ",
+      "Ġиме еÑĤ",
+      "ØŃ Ø±ÙĥØ©",
+      "à¸ŀ à¹Īà¸Ń",
+      "ãĤĴ ãģĬ",
+      "Ġاست خداÙħ",
+      "×IJ×Ļר ×ķ×¢",
+      "ä»ĸ ãģ®",
+      "Ġש×Ķ ×Ŀ",
+      "ãģĹãģŁ ãĤī",
+      "ש×ŀ ×Ļ",
+      "Ñģ ла",
+      "m ı",
+      "Ġbaz ı",
+      "Ġíķĺ ì§Ģë§Į",
+      "×ĵ ׾",
+      "Ġyapt ıģı",
+      "ãĥĬ ãĥ¼",
+      "׾ ×Ļ׾×Ķ",
+      "ãģ¨ãģĦ ãģ£ãģŁ",
+      "änd ig",
+      "ĠÅŁ a",
+      "ĠÙģÙĬ Ùħا",
+      "иÑĤ елÑı",
+      "×ŀ ×ķש",
+      "à¸Ĥ à¸Ńà¸ļ",
+      "l ük",
+      "Ġh á»ĵi",
+      "Ġëª ħ",
+      "ĠاÙĦÙĥ Ø«ÙĬر",
+      "צ ×IJ",
+      "Ġhaz ır",
+      "طر Ùģ",
+      "ا ÙĬا",
+      "ĠÄij ôi",
+      "ен д",
+      "ÙĦ غ",
+      "×Ĺ ×ĸ×ķר",
+      "ĠвÑģ ег",
+      "ĠвÑģег да",
+      "ëIJĺ ê³ł",
+      "×ĵ ×ķ×ĵ",
+      "ан а",
+      "د ÙĪÙĦØ©",
+      "Ġho ạch",
+      "ع ÙĦا",
+      "عÙĦا ج",
+      "Ġ×ķ ×¢×ĵ",
+      "×Ķ ×Ŀ",
+      "ки й",
+      "ÙĦ ÙIJ",
+      "Ġ×¢ ׾×Ļ×ķ",
+      "ÑİÑī ий",
+      "Ġng ủ",
+      "صÙĨ ع",
+      "ĠاÙĦع راÙĤ",
+      "à¸ķà¹Īà¸Ń à¹Ħà¸Ľ",
+      "ãģŁãģı ãģķãĤĵ",
+      "Ġph ạm",
+      "ÙĦ اÙĨ",
+      "ات Ùĩا",
+      "Ġbö yle",
+      "تÙĨ ÙģÙĬ",
+      "تÙĨÙģÙĬ Ø°",
+      "Ġש×Ķ ×Ļ×IJ",
+      "Ñģ Ñĥ",
+      "ย าว",
+      "Ġש ×ķ׳×Ļ×Ŀ",
+      "Ġ×ŀ ×ķ׾",
+      "ĠÑģ ил",
+      "Ġ×IJ×Ĺר ×Ļ×Ŀ",
+      "Ġph ủ",
+      "ÙĤØ· ع",
+      "ĠTh ủ",
+      "à¸Ľà¸£à¸°à¹Ģà¸Ĺศ à¹Ħà¸Ĺย",
+      "ÙĨ ÙĤ",
+      "ĠÄijo ạn",
+      "Ġب Ø¥",
+      "п ÑĢедел",
+      "×ķת ×ķ",
+      "Ġy arı",
+      "пÑĢ е",
+      "ĠczÄĻ ÅĽci",
+      "ØŃ ÙĥÙħ",
+      "×ķ׳ ×Ļת",
+      "פע ׾",
+      "ãĤĴ ãģĹãģ¦",
+      "Ġktó rzy",
+      "׾ ×Ŀ",
+      "ĠÄIJi á»ģu",
+      "ĠкоÑĤоÑĢ аÑı",
+      "ĠìĿ´ ìĥģ",
+      "ãģĤ ãģ£ãģŁ",
+      "Ġ×ŀ×ĵ ×ķ×ijר",
+      "פ ×ķ×¢×ľ",
+      "d ım",
+      "éĢļ ãĤĬ",
+      "ĠбÑĥд ÑĥÑĤ",
+      "à¹Ģวà¹ĩà¸ļ à¹Ħà¸ĭ",
+      "à¹Ģวà¹ĩà¸ļà¹Ħà¸ĭ à¸ķà¹Į",
+      "ا خر",
+      "×Ĺ ×Ļ׾",
+      "Ġ×Ļ ׾",
+      "Ġ×Ļ׾ ×ĵ×Ļ×Ŀ",
+      "×Ĺ ×Ļפ",
+      "×Ĺ×Ļפ ×ķש",
+      "Ġd òng",
+      "Ġש ×ĸ×Ķ",
+      "ÑĮ е",
+      "ãģĤ ãģ¨",
+      "ìŀIJ ê°Ģ",
+      "×IJ ×ĵ",
+      "Ġü z",
+      "Ġüz ere",
+      "ظ ÙĦ",
+      "Ġ×IJ ×ķ׾×Ļ",
+      "Ġ×ij ×Ļ×ķ×Ŀ",
+      "ÙĦ ات",
+      "Ġm ê",
+      "ì¹ ¨",
+      "تØŃ Ø¯",
+      "تØŃد Ø«",
+      "ĠØ® اصة",
+      "Ġب رÙĨ",
+      "ĠبرÙĨ اÙħج",
+      "ĠH Ãłn",
+      "×Ĺ ×¡",
+      "ĠÙĪ ÙĦÙħ",
+      "×¢ ×Ŀ",
+      "Ġm ı",
+      "à¸Ł ัà¸ĩ",
+      "ש ×¢×Ķ",
+      "ÙĪÙģ ÙĤ",
+      "ס ×ij×Ļר",
+      "алÑĮ нÑĭй",
+      "×Ĺש ×ķ×ij",
+      "Ġn Ãłng",
+      "ë³ ¼",
+      "ĠкоÑĤоÑĢ ÑĭÑħ",
+      "Ġ×Ĺ ×ķק",
+      "t ör",
+      "ĠлÑĥÑĩ ÑĪе",
+      "ãĥij ãĥ³",
+      "ลà¹Īา สุà¸Ķ",
+      "Ġج دÙĬد",
+      "ÙĬد Ø©",
+      "à¸Ĺ รà¸ĩ",
+      "ãĤĪãĤĬ ãĤĤ",
+      "ÙĦ ÙĦ",
+      "ãĤĤ ãģ£ãģ¨",
+      "ש×ĺ ×Ĺ",
+      "Ġ×ķ ×IJ×Ļ",
+      "Ġgi á»ijng",
+      "Ø¥ ضاÙģ",
+      "ק ת",
+      "ë§ Ŀ",
+      "Ġzosta ÅĤ",
+      "ÑĢ оз",
+      "×Ļפ ×Ļ×Ŀ",
+      "Ġ׼׾ ׾",
+      "ת×ķ׼ ף",
+      "dıģ ını",
+      "ÙĤ سÙħ",
+      "ĠÑģ ÑĩиÑĤ",
+      "ĠÑģÑĩиÑĤ а",
+      "×ĺ ×ķת",
+      "Ġ Æ°u",
+      "ĠØ¢ ÙĦ",
+      "Ġм ом",
+      "Ġмом енÑĤ",
+      "ĠاÙĦتع ÙĦÙĬÙħ",
+      "×¢×ľ ×ķת",
+      "Ġch ữa",
+      "Ġy ön",
+      "Ġtr Ãł",
+      "ĠØŃ ÙĬÙĨ",
+      "à¸ĭ ั",
+      "ĠC á",
+      "×¢ ×ĸ",
+      "ĠاÙĦØ£ ÙħÙĨ",
+      "c ÃŃ",
+      "Ġv á»ijn",
+      "Ġ à¸Ļาย",
+      "об ÑĢа",
+      "ק ×IJ",
+      "Ġthi ếu",
+      "ãĥŀ ãĥ¼",
+      "ส วà¸Ļ",
+      "Ġg á»Ń",
+      "Ġgá»Ń i",
+      "Ġê ¹",
+      "Ġê¹ Ģ",
+      "Ġthi á»ĩn",
+      "ÙĤ ع",
+      "w ÄĻ",
+      "Ġн ам",
+      "ÑĤ ол",
+      "Ġs ân",
+      "ס ×ķ×Ĵ",
+      "Ġgeç ir",
+      "ÑĤ он",
+      "ев а",
+      "ĠÙĪ ضع",
+      "Ġع شر",
+      "Ñģ ло",
+      "à¸Ī ัà¸ļ",
+      "ãĤ· ãĥ¼",
+      "ãĤĤ ãģĤãĤĬãģ¾ãģĻ",
+      "Ġv ẻ",
+      "ĠÄIJ á»ĥ",
+      "ر Ùģع",
+      "ĠاÙĦØ£ÙĪÙĦ Ùī",
+      "ÑĤ аÑĢ",
+      "ãģªãģı ãģ¦",
+      "Ùħ Ùİ",
+      "qu ÃŃ",
+      "×¢×ł×Ļ ×Ļ׳",
+      "г ен",
+      "Ġh ôm",
+      "à¸Ī า",
+      "Ġnh Ỽ",
+      "ĠاÙĦع ربÙĬ",
+      "×IJ ף",
+      "Ġl á»Ļ",
+      "Ġje ÅĽli",
+      "à¹Ģà¸Ĺà¹Īา à¸Ļัà¹īà¸Ļ",
+      "ĠØ£ÙĨ Ùĩا",
+      "Ġt uy",
+      "Ġtuy á»ĩt",
+      "Ġت ص",
+      "Ġتص ÙĨÙĬ",
+      "ĠتصÙĨÙĬ Ùģ",
+      "Ġê·¸ëŁ¬ ëĤĺ",
+      "о ÑĨен",
+      "à¸ģิà¸Ī à¸ģรรม",
+      "ãĤĦ ãģ£ãģ¦",
+      "Ġkh á»ıi",
+      "Ġl á»ĩ",
+      "ĠاÙĦÙħج تÙħع",
+      "à¸Ńาà¸Ī à¸Īะ",
+      "à¸Īะ à¹Ģà¸Ľà¹ĩà¸Ļ",
+      "ов Ñĭй",
+      "ר ×Ŀ",
+      "ร à¹īà¸Ńà¸Ļ",
+      "ש ×ŀש",
+      "人 ãģ«",
+      "Ġüzer ine",
+      "פר ×Ļ",
+      "du ÄŁu",
+      "Ñĩ ик",
+      "Ġmù a",
+      "Ġ×ŀת ×ķ×ļ",
+      "Ġc áºŃp",
+      "Ġت ارÙĬØ®",
+      "×ij׾ ת×Ļ",
+      "Ġì¢ Ģ",
+      "ÙĦ ع",
+      "ب اÙĨ",
+      "Ġch út",
+      "Ġ×Ķ×ĸ ×ŀף",
+      "n ée",
+      "ĠLi ên",
+      "ĠÙĦÙĦ Ø£",
+      "ØŃد ÙĪد",
+      "Ġ×¢ ׼ש×Ļ×ķ",
+      "в оз",
+      "Ġyapt ı",
+      "Ġоб о",
+      "à¹ĥหà¹ī à¸ģัà¸ļ",
+      "Ġ×ij×Ķ ×Ŀ",
+      "ãģı ãģ¦",
+      "ر أس",
+      "ĠÑģÑĢед ÑģÑĤв",
+      "ĠB Ãłi",
+      "ãģĵãģ¨ ãģ«",
+      "ĠìĤ¬ íļĮ",
+      "Ġ모 ëijIJ",
+      "×ij ×IJ",
+      "Ġtr ắng",
+      "ĠاÙĦبÙĦ د",
+      "ĠHo Ãłng",
+      "ли бо",
+      "ĠдÑĢÑĥг иÑħ",
+      "Ä° R",
+      "Ñĥм а",
+      "ĠJe ÅĽli",
+      "ãĤĤ ãģĹ",
+      "Ġv òng",
+      "Ġ×IJתר ×Ļ×Ŀ",
+      "ĠÄij á»įc",
+      "Ġв оÑĤ",
+      "ãģł ãģĮ",
+      "ë° °",
+      "à¸Ķู à¹ģล",
+      "Ġ×ŀ ׼׾",
+      "ìĹIJ ëıĦ",
+      "г аз",
+      "Ġ׳×ķס פ×Ļ×Ŀ",
+      "ãģĵãģ¨ ãģ§",
+      "Ġت ÙĪ",
+      "ãģ§ ãģĤãĤĬ",
+      "à¸Ļั à¹Īà¸ĩ",
+      "ĠможеÑĤ е",
+      "sz ÄĻ",
+      "ãģ® ãģł",
+      "ĠÙħÙĨ Ùĩ",
+      "Ġb á»ķ",
+      "Ġb üt",
+      "Ġbüt ün",
+      "ë³´ ê³ł",
+      "Ġch á»ĵng",
+      "à¹ģà¸Ī à¹īà¸ĩ",
+      "ĠV ì",
+      "ĠØŃ Ø±",
+      "Ġgi ản",
+      "ĠÙħ دÙĬÙĨØ©",
+      "تط بÙĬÙĤ",
+      "à¸Ī ิ",
+      "æĹ¥ ãģ®",
+      "б ил",
+      "à¸ģ à¸Ńà¸ĩ",
+      "ê³ ³",
+      "ĠØ£ Ùħا",
+      "ìĨ IJ",
+      "Ġtr ái",
+      "ĠвÑģ ем",
+      "Ġس ÙĨØ©",
+      "ĠÑģай ÑĤ",
+      "Ġг оÑĤов",
+      "п Ñĭ",
+      "ĠëIJ ł",
+      "ĠاÙĦØ® Ø·",
+      "ĠاÙĦرئÙĬس ÙĬØ©",
+      "Ġíķ ©ëĭĪëĭ¤",
+      "ĠìķĦëĭĪ ëĿ¼",
+      "ĠìĿ´ ëłĩ",
+      "ĠìĿ´ëłĩ ê²Į",
+      ") ØĮ",
+      "h ält",
+      "ĠØ£ Ùħر",
+      "Ġع Ùħر",
+      "à¸ģà¹ĩ à¸Īะ",
+      "Ġ à¸Ĺำà¹ĥหà¹ī",
+      "Ġc ân",
+      "Ġ×ij ׾",
+      "Ġ×ij׾ ×ij×ĵ",
+      "פ סק",
+      "ĠÙĬ ÙĤÙĪÙĦ",
+      "н ÑĥÑĤÑĮ",
+      "à¹ģ à¸Ħ",
+      "Ġק צת",
+      "Ġn ằm",
+      "Ġh òa",
+      "bilit Ãł",
+      "ĠìĹĨ ëĭ¤",
+      "Ġ׼ פ×Ļ",
+      "ÑĢ ож",
+      "лаг а",
+      "Ġ×Ķש ×Ļ",
+      "ĠNgo Ãłi",
+      "ĠÙĪ ج",
+      "ĠÙĪج ÙĪد",
+      "ĠìľĦ íķľ",
+      "Ġus ÅĤug",
+      "Ġtu ần",
+      "d ź",
+      "×ŀ ×ķף",
+      "ĠاÙĦع دÙĬد",
+      "Ġch ẳng",
+      "สุà¸Ĥ à¸łà¸²à¸ŀ",
+      "Ġ×ij ×ĵר×ļ",
+      "ĠÑģеб е",
+      "ĠìŀĪ ìĿĦ",
+      "ĠاÙĦØŃ Ø§ÙĦ",
+      "Ġd á",
+      "Ġc Æ°á»Ŀi",
+      "Ġnghi ên",
+      "ie ÅĦ",
+      "ĠD Æ°Æ¡ng",
+      "ï¼ ħ",
+      "ش د",
+      "ãģĦãģ¤ ãĤĤ",
+      "ĠвÑĭб оÑĢ",
+      "Ġc á»Ļng",
+      "ש ×Ļ׳×ķ×Ļ",
+      "Ġch ạy",
+      "Ġ×ij×¢ ׾×Ļ",
+      "اخ بار",
+      "íķĺ ë©°",
+      "ż Äħ",
+      "ج از",
+      "Ġ׳ ר×IJ×Ķ",
+      "ศ ู",
+      "ศู à¸Ļ",
+      "ศูà¸Ļ ยà¹Į",
+      "×Ĵ ×¢",
+      "Ġ×¢ ×ĵ×Ļ",
+      "Ġ×¢×ĵ×Ļ ×Ļף",
+      "بر ا",
+      "ÑĨи й",
+      "ĠÄIJ á»ĵng",
+      "ÙĤ اÙĨÙĪÙĨ",
+      "ĠÄij ứng",
+      "ãģĹãģŁ ãĤĬ",
+      "Ġ×Ĺ×Ļ ×Ļ",
+      "Ġë IJľ",
+      "ĠëIJľ ëĭ¤",
+      "Ġм еждÑĥ",
+      "à¸ŀวà¸ģ à¹Ģà¸Ĥา",
+      "ĠB ắc",
+      "ล ำ",
+      "ë° ±",
+      "ĠíĻ ķ",
+      "มาà¸ģ ม",
+      "มาà¸ģม าย",
+      "бан к",
+      "à¸Ńา à¸ģาร",
+      "Ġh Ãł",
+      "Ġ׾ ׳",
+      "à¸Ń à¸Ń",
+      "Ġë°Ķ ë¡ľ",
+      "л ом",
+      "m ática",
+      "ĠØŃ Ø¯",
+      "اب ت",
+      "à¸Ĺีà¹Ī à¸Ļีà¹Ī",
+      "Ġco ÅĽ",
+      "ÙģÙĬ دÙĬ",
+      "ÙģÙĬدÙĬ ÙĪ",
+      "ĠмеÑģÑĤ о",
+      "Ġph út",
+      "มาà¸ģ à¸ģวà¹Īา",
+      "×IJ פ",
+      "ب ÙIJ",
+      "ĠPh ú",
+      "ì± Ħ",
+      "ĠÙĪ سÙĦÙħ",
+      "à¸Īี à¸Ļ",
+      "поÑĤ ÑĢеб",
+      "Ġ×Ĺ×ĵ ש×ķת",
+      "Ø´ ÙĪ",
+      "Ġעצ ×ŀ×ķ",
+      "ĠعÙħÙĦ ÙĬØ©",
+      "à¸Ħุà¸ĵ à¸łà¸²à¸ŀ",
+      "ãģ¾ãģĻ ãģĮ",
+      "دع ÙĪ",
+      "طر ÙĤ",
+      "à¹Ħมà¹Ī à¸ķà¹īà¸Ńà¸ĩ",
+      "ë² Ķ",
+      "ìĬ ¹",
+      "Ġk ÃŃch",
+      "ĠìĹĨ ëĬĶ",
+      "ĠÑĤ ам",
+      "ĠÙĨ ØŃÙĪ",
+      "ĠاÙĦÙĤ اÙĨÙĪÙĨ",
+      "×Ĺ ×ķ×Ŀ",
+      "Ġk ız",
+      "Ġ×ĵ ×Ļף",
+      "ĠвÑĢем ени",
+      "ãģ£ãģŁ ãĤĬ",
+      "ĠØ´ Ùĩر",
+      "ĠìĦľ ë¹ĦìĬ¤",
+      "×¢ ש×Ķ",
+      "Ġgi ác",
+      "ĠاÙĦسÙĦ اÙħ",
+      "Ġ×IJ ש",
+      "ĠполÑĥÑĩ а",
+      "à¸Īัà¸Ķ à¸ģาร",
+      "к оÑĢ",
+      "Ġ×Ķ×ĺ ×ķ×ij",
+      "ราย à¸ģาร",
+      "주 ìĿĺ",
+      "à¹ģà¸ķà¹Ī ละ",
+      "Ġê·¸ëŁ° ëį°",
+      "à¸Ĺีà¹Ī à¹Ģà¸Ľà¹ĩà¸Ļ",
+      "Ġת ×ķ×ļ",
+      "بÙĬ اÙĨ",
+      "Ð Ļ",
+      "oÅĽci Äħ",
+      "ÑĤ ок",
+      "ĠÃ Ķ",
+      "ĠÃĶ ng",
+      "à¹Ħมà¹Ī à¹ĥà¸Ĭà¹Ī",
+      "ãģ¿ ãģ¦",
+      "ÐŁ о",
+      "ĠЧ ÑĤо",
+      "íĻ ©",
+      "×ĺ ×ij×¢",
+      "меÑĤ ÑĢ",
+      "Ġ×ij ×ŀ×Ķ",
+      "Ġ×ij×ŀ×Ķ ׾",
+      "Ġ×ij×ŀ×Ķ׾ ×ļ",
+      "Ñĩ ÑĮ",
+      "ק ש×Ķ",
+      "з нак",
+      "знак ом",
+      "uj ÄĻ",
+      "×Ļצ ר",
+      "ĠاÙĦÙħ ÙĦÙĥ",
+      "ı yla",
+      "×IJ×ŀ ת",
+      "à¸Ľ ิà¸Ķ",
+      "×IJ ×Ĺ×ĵ",
+      "ر اد",
+      "Ġm áºŃt",
+      "ëĭ¤ ëĬĶ",
+      "Ġl ạnh",
+      "ש׾ ×ķש",
+      "ØŃ Ø¯ÙĬØ«",
+      "ت ز",
+      "å¹´ ãģ®",
+      "Ġк ваÑĢ",
+      "ĠкваÑĢ ÑĤиÑĢ",
+      "ä½ľ ãĤĬ",
+      "رÙĪ ب",
+      "ов ан",
+      "ĠТ е",
+      "à¸Īำ à¸ģ",
+      "à¸Īำà¸ģ ัà¸Ķ",
+      "ب اط",
+      "×Ĵ ת",
+      "Ġм аÑĪ",
+      "ĠмаÑĪ ин",
+      "×Ļצ ×Ķ",
+      "ãģ» ãģ¨",
+      "ãģ»ãģ¨ ãĤĵãģ©",
+      "ÃŃ do",
+      "ĠÑı зÑĭк",
+      "à¸ļ ิà¸Ļ",
+      "สà¸ĸาà¸Ļ à¸Ĺีà¹Ī",
+      "ĠìĹ ´",
+      "ãĤ¦ ãĤ§",
+      "Ġc Ãł",
+      "п ан",
+      "åı£ ãĤ³ãĥŁ",
+      "Ġر د",
+      "اÙĤ ت",
+      "ĠÙĥ ب",
+      "ĠÙĥب ÙĬرة",
+      "ÑģÑĤ ал",
+      "ש×ŀ ×Ĺ",
+      "pos ición",
+      "ĠÙħÙĦÙĬ ÙĪÙĨ",
+      "ĠìĿ´ ìķ¼",
+      "ĠìĿ´ìķ¼ 기",
+      "Ġh út",
+      "ĠÅĽw iat",
+      "Ġë°© ë²ķ",
+      "ĠÑģв еÑĤ",
+      "Ġвиде о",
+      "ĠاÙĦÙĨ ظاÙħ",
+      "Ġtr á»Ŀi",
+      "ĠëĮĢ íķ´ìĦľ",
+      "ר ×ŀת",
+      "ت داÙĪÙĦ",
+      "×ķר ×ĵ",
+      "ת ×ŀ",
+      "ת×ŀ ×ķ׳×ķת",
+      "Ġ×ŀ ף",
+      "Ġдв а",
+      "Ġ×Ķק ×ķ",
+      "æĹ¥ ãģ«",
+      "Ġ×Ķ×Ĵ ×Ļ×¢",
+      "à¹Ģà¸ŀิà¹Īม à¹Ģà¸ķิม",
+      "Ùħار س",
+      "Ġê²ĥ ìŀħëĭĪëĭ¤",
+      "ãģªãģĦ ãģ¨",
+      "Ġnhi á»ĩt",
+      "ëIJ ©ëĭĪëĭ¤",
+      "Ġ×ij׳ ×ķש×IJ",
+      "Ġê°Ģ ìŀ¥",
+      "Ġv ợ",
+      "ĠÄij óng",
+      "צ×Ļ׾ ×ķ×Ŀ",
+      "ê´Ģ ê³Ħ",
+      "в аÑı",
+      "×IJ ×Ļ×ĸ",
+      "×IJ×Ļ×ĸ ×Ķ",
+      "ĠÙĨ ظاÙħ",
+      "ÙħØŃ Ø§Ùģظ",
+      "Ġt ải",
+      "기 ëıĦ",
+      "à¸Ľà¸±à¸Ī à¸Īุ",
+      "à¸Ľà¸±à¸Īà¸Īุ à¸ļัà¸Ļ",
+      "׼ ×ĵ×ķר",
+      "ĠìķĦ ìĿ´",
+      "׼׳ ×Ļס",
+      "à¹Ģ à¸ķร",
+      "à¹Ģà¸ķร ียม",
+      "Ġngo ại",
+      "ĠدÙĪÙĦ ار",
+      "Ġr ẻ",
+      "Ġkh Äĥn",
+      "عد د",
+      "ش عب",
+      "czy Äĩ",
+      "ĠاÙĦ Ùĥر",
+      "ĠÑĩеловек а",
+      "ĠÙĪ Ø¥ÙĨ",
+      "×IJ ×ĺ",
+      "Ġth Æ¡",
+      "ĠاÙĦ رÙĬاض",
+      "оп ÑĢедел",
+      "опÑĢедел ен",
+      "×Ķ ×ŀש×ļ",
+      "ĠÐĿ ово",
+      "з Ñĭва",
+      "ĠاÙĦدÙĪÙĦ ÙĬ",
+      "ĠÄij áp",
+      "Ġк ÑĢед",
+      "ĠкÑĢед иÑĤ",
+      "ов ого",
+      "Ġm ôn",
+      "à¸Ľà¸£à¸° à¹Ĥย",
+      "à¸Ľà¸£à¸°à¹Ĥย à¸Ĭà¸Ļ",
+      "à¸Ľà¸£à¸°à¹Ĥยà¸Ĭà¸Ļ à¹Į",
+      "ÑģÑĤ е",
+      "ĠTh á»ĭ",
+      "د ÙĬØ©",
+      "×ŀצ ×ķ",
+      "Ùģ ات",
+      "ק ×ĵ×Ŀ",
+      "ìĿ´ëĿ¼ ê³ł",
+      "ÙĪ Ø®",
+      "Ġ×Ĺ ×ĸ",
+      "ĠÑĦоÑĤ о",
+      "׾ ×Ļת",
+      "ت Ùİ",
+      "ÙĪ بر",
+      "й ÑĤи",
+      "ĠÃ¶ÄŁ ren",
+      "Ġ×Ķ×ĸ ×ķ",
+      "Ġv á»įng",
+      "ÙĤÙĪ Ø©",
+      "ĠT ây",
+      "ĠÐĿ и",
+      "Ġש ×ķ×ij",
+      "ãģ¨è¨Ģ ãĤıãĤĮ",
+      "ãģ© ãĤĵãģª",
+      "׊צ×Ļ",
+      "ï½ ľ",
+      "Ġ×ķ×Ķ ×ķ×IJ",
+      "ä¸Ģ ãģ¤",
+      "ĠÑģÑĤо иÑĤ",
+      "ni Äħ",
+      "×ĺר ×Ļ",
+      "ĠдеÑĤ ей",
+      "нÑı ÑĤÑĮ",
+      "ĠÑģдел аÑĤÑĮ",
+      "Ġë§İ ìĿ´",
+      "ä½ķ ãģĭ",
+      "ãģĽ ãĤĭ",
+      "à¹Ħ หม",
+      "à¸ķิà¸Ķ à¸ķà¹Īà¸Ń",
+      "Ġ×ij ת×Ĺ",
+      "Ġ×ijת×Ĺ ×ķ×Ŀ",
+      "ìĻ Ħ",
+      "ì§Ģ ëĬĶ",
+      "ÑģÑĤ аÑĤ",
+      "ÑıÑģ н",
+      "ü b",
+      "Ġth ả",
+      "Ġ×ij×IJ×ŀ ת",
+      "Ġt uyến",
+      "×ĵ ×Ļר×Ķ",
+      "Ġ×IJ ×Ļש×Ļ",
+      "×ĸ׼ ר",
+      "ãģ° ãģĭãĤĬ",
+      "Ġx ét",
+      "׼ ×Ļ×ķ",
+      "׼×Ļ×ķ ×ķף",
+      "diÄŁ ini",
+      "ĠاÙĦÙħ ÙĪضÙĪع",
+      "Ġh áºŃu",
+      "à¸Īาà¸ģ à¸ģาร",
+      "×ijס ×Ļס",
+      "Ġ×ŀ×Ĵ ×Ļ×¢",
+      "×ij ×Ļ×¢",
+      "ĠÙĪ جÙĩ",
+      "à¹ģà¸Ķ à¸ĩ",
+      "à¸Ļ าà¸ĩ",
+      "ĠÅŀ a",
+      "ì ¡´",
+      "ë¡ Ģ",
+      "à¸ķ ะ",
+      "Ġ×Ķ×Ĺ×Ļ ×Ļ×Ŀ",
+      "Ùģ ÙĬد",
+      "ãģ§ãģĻ ãģĭãĤī",
+      "ê· ľ",
+      "ź ni",
+      "ĠлÑİ Ð´ÐµÐ¹",
+      "Ġyüz de",
+      "ıy orum",
+      "ĠاÙĦ بØŃر",
+      "e ño",
+      "п аÑĢ",
+      "ÙĬ ÙĤØ©",
+      "об ÑĢ",
+      "ר ×ķ×ļ",
+      "ت ÙĪÙĤع",
+      "ĠاÙĦØ´ ÙĬØ®",
+      "åĪĿ ãĤģãģ¦",
+      "ĠÑĤ елеÑĦ",
+      "ĠÑĤелеÑĦ он",
+      "Ġth ôi",
+      "Ġ×Ļ׼×ķ׾ ×Ļ×Ŀ",
+      "ĠÅŁ irk",
+      "ĠÅŁirk et",
+      "Ġìļ°ë¦¬ ê°Ģ",
+      "ĠÄij ông",
+      "Ġת ×ķ×ĵ×Ķ",
+      "ÑģмоÑĤÑĢ еÑĤÑĮ",
+      "ĠÙĦ ÙĩÙħ",
+      "Ġ׾ ׼",
+      "ĠN ó",
+      "ĠØŃ Ø§ÙĦØ©",
+      "ãģĦ ãģij",
+      "קר ×ķ",
+      "az ı",
+      "ãĤ³ ãĥ¼",
+      "ĠÙĦÙĦ ت",
+      "s ınız",
+      "ĠH ải",
+      "기 ìĪł",
+      "ยัà¸ĩ à¹Ħมà¹Ī",
+      "ëĭ¤ ê³ł",
+      "פ ×Ĺ",
+      "Ġ׾×Ĵ ×ij×Ļ",
+      "Ġع ÙĨÙĩ",
+      "Ġк аз",
+      "Ġказ ино",
+      "ب ÙĪر",
+      "ÑĦ еÑĢ",
+      "Ġê°Ļ ìĿ´",
+      "تس جÙĬÙĦ",
+      "ĠاÙĦÙħ رÙĥز",
+      "ĠTh ái",
+      "д аÑĤÑĮ",
+      "×ŀ×Ļ ×Ļ׾",
+      "Ġpay laÅŁ",
+      "ãģ¤ ãģ®",
+      "à¹Ģร ืà¸Ń",
+      "n ça",
+      "׳ ×ķ×Ĺ",
+      "Ġ×IJ פ×Ļ׾×ķ",
+      "ãģ¨ èĢĥãģĪ",
+      "ãģ¨ãģĹãģ¦ ãģ¯",
+      "à¹Ģà¸Ī à¸Ń",
+      "×ŀ פ",
+      "Ġg iriÅŁ",
+      "л иÑĤ",
+      "ÑĤ елÑı",
+      "Ñij н",
+      "æ°Ĺ ãģ«",
+      "Ġg ó",
+      "Ġgó p",
+      "åĪĩ ãĤĬ",
+      "Ġ×Ķ ×Ĺ×ĵש",
+      "ж ал",
+      "Ġ×ĵ עת",
+      "éģķ ãģĨ",
+      "à¹Ģà¸Ĥà¹īา à¹Ħà¸Ľ",
+      "Ġס ר×ĺ",
+      "e ña",
+      "æĸ° ãģĹãģĦ",
+      "ر Ùİ",
+      "ĠÐIJ ÑĢ",
+      "Ġph ản",
+      "à¸Īะ à¹Ħà¸Ķà¹ī",
+      "Ġ×ijצ ×ķר×Ķ",
+      "Ø´ اÙĩ",
+      "شاÙĩ د",
+      "ÙĪر د",
+      "à¹Ģà¸Ļืà¹Īà¸Ńà¸ĩ à¸Īาà¸ģ",
+      "или ÑģÑĮ",
+      "à¹ģละ à¸ģาร",
+      "Ġ×Ķ ×ĸ׼",
+      "Ġ×Ķ×ĸ׼ ×ķ×Ļ×ķת",
+      "ei ÃŁ",
+      "ãĥ ¨",
+      "ìĥ Ī",
+      "ĠÃĩ a",
+      "Æ ¯",
+      "ש ×Ĵ",
+      "ÙĬÙĨ Ø©",
+      "ร à¹īà¸Ńà¸ĩ",
+      "ãĤµ ãĥ³",
+      "ÑĢоÑģÑģ ий",
+      "ÑĢоÑģÑģий Ñģк",
+      "a ÄŁa",
+      "ĠнаÑĩ ина",
+      "Ġص ÙĦÙī",
+      "à¸Ĺุà¸ģ à¸Ħà¸Ļ",
+      "íļĮ ìĤ¬",
+      "Ġли ÑĨ",
+      "Ø´ ÙĬر",
+      "ĠØ´ÙĬ Ø¡",
+      "ÙĬÙĨ ا",
+      "Ġפ ×Ĺ×ķת",
+      "Ġiçer is",
+      "Ġiçeris inde",
+      "ĠØ£ ØŃÙħد",
+      "Ġże by",
+      "ì´ Ŀ",
+      "Ġп оказ",
+      "Ġи менно",
+      "หà¸Ļัà¸ĩ ส",
+      "หà¸Ļัà¸ĩส ืà¸Ń",
+      "ĠÑĤÑĢ е",
+      "สัà¸ĩ à¸Ħม",
+      "Ø¥ ÙIJ",
+      "ãģĮ å¿ħè¦ģ",
+      "ÙĬÙij Ø©",
+      "פ צ",
+      "íĭ °",
+      "ĠÙħ جاÙĦ",
+      "׳ פש",
+      "к ан",
+      "×Ĺ ×ķפ",
+      "×Ĺ×ķפ ש",
+      "ì²ĺ ëŁ¼",
+      "ов аÑı",
+      "з ов",
+      "Ġh ạ",
+      "Ġdzi ÄĻki",
+      "×Ļר ×ķ",
+      "Ġ׾ ×ŀצ",
+      "Ġ׾×ŀצ ×ķ×IJ",
+      "×Ļ×ĵ ×ķ",
+      "Ġs ợ",
+      "Ġ׾×Ķ ×Ĵ×Ļ×¢",
+      "ק ×ij×¢",
+      "Ġchi á»ģu",
+      "ãĥŀ ãĤ¤",
+      "Ġd Ãłng",
+      "à¹ģà¸Ł à¸Ļ",
+      "Ġü ye",
+      "×Ļ׳ ×Ĵ",
+      "à¹Ģรีย à¸ģ",
+      "ç§ģ ãģĮ",
+      "th é",
+      "ĠÑĦ илÑĮ",
+      "ĠÑĦилÑĮ м",
+      "ĠNg Ãły",
+      "Ġж ен",
+      "Ġжен Ñīин",
+      "ج ÙĬد",
+      "n ç",
+      "à¸Ľ รา",
+      "×Ļ×ŀ ×ķ",
+      "Ġn á»ģn",
+      "×IJ ×ķ׾×Ŀ",
+      "Ġвозмож ноÑģÑĤÑĮ",
+      "Ġëĭ¤ ìĭľ",
+      "è¦ĭ ãģŁ",
+      "à¸ĸ à¸Ļ",
+      "à¸ĸà¸Ļ à¸Ļ",
+      "mız ı",
+      "ĠÙħ جÙħÙĪعة",
+      "c jÄħ",
+      "ĠÐł Ф",
+      "à¸ģำ หà¸Ļ",
+      "à¸ģำหà¸Ļ à¸Ķ",
+      "ĠìŬ 기",
+      "land ı",
+      "ни ÑĨ",
+      "ÑģÑĤв е",
+      "Ġ×ĵ ×ijר×Ļ×Ŀ",
+      "Ġsk ÅĤad",
+      "ãĤĬ ãģ¾ãģĹãģŁ",
+      "ĠоÑĤ кÑĢÑĭÑĤ",
+      "нÑı ÑĤ",
+      "ĠÑģво ей",
+      "à¸Ī ิà¸ķ",
+      "ĠкаÑĩеÑģÑĤв е",
+      "Ġet tiÄŁi",
+      "ìĤ¬ íķŃ",
+      "ĠاÙĦÙĬ ÙħÙĨ",
+      "иÑĩеÑģки й",
+      "ë¸ Į",
+      "Ġ×ij×IJר ×¥",
+      "Ġا سÙħ",
+      "Ġиз веÑģÑĤ",
+      "r ão",
+      "Ġatt ivitÃł",
+      "à¹Ģà¸Ľà¹ĩà¸Ļ à¸ģาร",
+      "ĠاÙĦد Ùĥت",
+      "ĠاÙĦدÙĥت ÙĪر",
+      "ĠÙĪاØŃد Ø©",
+      "ĠÑģ ÑĩеÑĤ",
+      "ĠпÑĢ иÑĩ",
+      "ĠпÑĢиÑĩ ин",
+      "ĠÙĪز ارة",
+      "Ġh uyá»ĩn",
+      "ĠÙĥ تاب",
+      "à¹ģà¸Ļ à¹Īà¸Ļ",
+      "à¹ģà¸Ļà¹Īà¸Ļ à¸Ńà¸Ļ",
+      "Ġgün ü",
+      "г ÑĢÑĥз",
+      "ĠاÙĦØ® اص",
+      "Ġgör ül",
+      "׾ ×ŀ×ĵ",
+      "Ġìłķ ëıĦ",
+      "×ķ×ij ×Ļ׾",
+      "Ġ×ŀק צ×ķ×¢×Ļ",
+      "ĠоÑģоб енно",
+      "à¸Ľà¸£à¸° à¸ģา",
+      "à¸Ľà¸£à¸°à¸ģา ศ",
+      "aca ģını",
+      "ë¶ ģ",
+      "à¸łà¸¹ มิ",
+      "ĠÑį лекÑĤ",
+      "ĠÑįлекÑĤ ÑĢо",
+      "Ġק ש×Ķ",
+      "سÙĦ Ø·",
+      "à¸Ĭà¸Ļ ะ",
+      "×¢ ×Ļ׾",
+      "ĠЧ е",
+      "à¹ģà¸Ļ à¹Ī",
+      "lı ģ",
+      "lıģ ın",
+      "Ġ×ŀ×¢ ×¨×Ľ×ª",
+      "好ãģį ãģª",
+      "มาà¸ģ à¸Ĥึà¹īà¸Ļ",
+      "×ŀ×¢ ×ijר",
+      "ĠاÙĦÙħ غرب",
+      "ĠпеÑĢ и",
+      "ĠпеÑĢи од",
+      "Ġnh ạc",
+      "ا ÙĪÙĬ",
+      "ĠÙĪ عÙĦÙī",
+      "أخ ذ",
+      "ĠC ô",
+      "תר ×ij×ķת",
+      "×Ĵ ×Ķ",
+      "Ġktóre j",
+      "×IJ ×Ļת",
+      "×ij ×ķ×IJ",
+      "д елÑĮ",
+      "รี วิ",
+      "รีวิ ว",
+      "ж Ñĥ",
+      "Ġ×ij×Ĺ ×ķ",
+      "еÑĪ ÑĮ",
+      "ĠØ£ ÙĦÙģ",
+      "ĠاÙĦÙĪ Ø·ÙĨÙĬ",
+      "ĠاÙĦÙħÙĨ Ø·ÙĤØ©",
+      "nÄħ Äĩ",
+      "Ġthi ên",
+      "иÑĩеÑģк ой",
+      "ĠاÙĦÙħ ÙĦ",
+      "Ġع Ùħ",
+      "ס פר",
+      "Ġnh óm",
+      "ÙĪص Ùģ",
+      "ĠCh úng",
+      "Ġر ÙĤÙħ",
+      "ãģ¾ãģĹãģŁ ãģĮ",
+      "al ité",
+      "ล ม",
+      "ĠëĤ´ ê°Ģ",
+      "׾ק ×ķ×Ĺ",
+      "ĠS Æ¡n",
+      "pos ição",
+      "mi ÄĻ",
+      "Ġtr ánh",
+      "ĠÄIJ á»Ļ",
+      "׼ ×Ĺ",
+      "ãģĤ ãģ£ãģ¦",
+      "à¸Ńย à¹Īา",
+      "Ġ×ŀ×Ĺ ×Ļר",
+      "Ġ×Ķ ×Ļת×Ķ",
+      "à¸Ľ à¹Īา",
+      "à¸Ńืà¹Īà¸Ļ à¹Ĩ",
+      "Ø´ ÙĤ",
+      "×ł×¡ ×Ļ",
+      "ë¦ ¼",
+      "ãģ¦ãģĹãģ¾ ãģĨ",
+      "Ġ×ŀ צ×ij",
+      "ãģ« åĩº",
+      "ÙħÙĪا Ø·ÙĨ",
+      "ยัà¸ĩ มี",
+      "алÑĮ нÑĭе",
+      "san ız",
+      "Ø¥ سرائÙĬÙĦ",
+      "ĠvÃł i",
+      "ì¤ Ħ",
+      "ãģ¨æĢĿ ãģ£ãģ¦",
+      "×Ļ ×ķ׳×Ļ",
+      "çĶŁ ãģį",
+      "Ġs âu",
+      "Ñĩ иÑģÑĤ",
+      "Ġl á»ħ",
+      "ĠGi á",
+      "à¸Ńุ à¸Ľ",
+      "à¸Ńà¸¸à¸Ľ à¸ģร",
+      "à¸Ńà¸¸à¸Ľà¸ģร à¸ĵà¹Į",
+      "Ġnh ẹ",
+      "r ö",
+      "ס ×ĺ×Ļ",
+      "ãģķãĤĵ ãģĮ",
+      "Ġd ầu",
+      "ع Ùİ",
+      "ت را",
+      "×Ĵ×ĵ ׾",
+      "Ġtécn ica",
+      "׼ ׳×Ļ×Ŀ",
+      "תק ש",
+      "תקש ×ķרת",
+      "Ġн его",
+      "ét ait",
+      "Ġm á»ģm",
+      "Ñģ еÑĤ",
+      "Ġnh áºŃt",
+      "Ġ×ŀ ×¢×ľ",
+      "Ġ×Ķ×¢ ×ij×ķ×ĵ",
+      "Ġ×Ķ×¢×ij×ķ×ĵ ×Ķ",
+      "Ġ×Ĵ ×Ļ׾",
+      "ãģ¯ ãģªãģĦ",
+      "ائ ØŃ",
+      "Ġз деÑģÑĮ",
+      "×IJ ×Ļ׳×ĺר",
+      "Ùħ ÙIJ",
+      "Ġ×Ļ ×Ĺ×ĵ",
+      "ر اÙģ",
+      "ì²ĺ 리",
+      "×ĵ ×¢×ķת",
+      "ì¹ ľ",
+      "ĠТ о",
+      "ĠTh ế",
+      "ì¶ ©",
+      "Ġ׳׼ ×ķף",
+      "عÙĬ Ø´",
+      "ни з",
+      "Ġج اÙĨب",
+      "×ŀק צ×ķ×¢",
+      "à¹Ĥ à¸ĭ",
+      "Ñģ ÑĥÑĤ",
+      "ìĸ´ ìļĶ",
+      "ãĤĴè¦ĭ ãģ¦",
+      "ار د",
+      "Ġaç ıl",
+      "ĠاÙĦØŃ ÙĬاة",
+      "à¸ģà¹ĩ à¹Ħà¸Ķà¹ī",
+      "ãģĿãĤĮ ãĤĴ",
+      "عض ÙĪ",
+      "Ġг ÑĢаж",
+      "ĠгÑĢаж дан",
+      "à¸Īะ à¸ķà¹īà¸Ńà¸ĩ",
+      "ĠìĿ´ 룬",
+      "ĠìĿ´ëŁ¬ íķľ",
+      "Ġtr ách",
+      "ÙĨ Ùİ",
+      "Ġkı sa",
+      "Ã Ķ",
+      "ÑĪ ка",
+      "ãģ® 人",
+      "ĠÐŁ оÑģ",
+      "ĠÐŁÐ¾Ñģ ле",
+      "Ñĥ лÑĮ",
+      "ÙĪا جÙĩ",
+      "ÙĤ رب",
+      "à¸Ľà¸ıิ à¸ļัà¸ķิ",
+      "ê° Ļ",
+      "Ġ×ŀ ׳",
+      "ĠÑģво и",
+      "بر اÙħج",
+      "Ġر ÙĪ",
+      "пÑĢ од",
+      "пÑĢод аж",
+      "Ġby ÅĤy",
+      "วั ย",
+      "Ġgör ün",
+      "ĠÃ Ī",
+      "ÑİÑī им",
+      "ĠÑĤак ой",
+      "Ùģ ÙĪر",
+      "ĠÙģ عÙĦ",
+      "Ġб ел",
+      "ëIJ ł",
+      "er ÃŃa",
+      "ĠÑģво Ñİ",
+      "Ġl ã",
+      "Ġlã nh",
+      "à¹Ģà¸ŀืà¹Īà¸Ń à¹ĥหà¹ī",
+      "ÙĤ ÙĨ",
+      "تط ÙĪÙĬر",
+      "Ġsay ı",
+      "ĠÑģ ейÑĩаÑģ",
+      "Ġ×IJ×Ĺר ת",
+      "ק ×ķפ×Ķ",
+      "ק×ķר ס",
+      "Ġس Ùħ",
+      "Ġ×ĺ ×Ļפ×ķ׾",
+      "ìĿ´ëĿ¼ ëĬĶ",
+      "دراس ة",
+      "èµ· ãģĵ",
+      "×Ĺ ×Ļ׳",
+      "×Ĺ×Ļ׳ ×ķ×ļ",
+      "×ĵ ק",
+      "Ġë§ ŀ",
+      "Ġком анд",
+      "ĠÐij о",
+      "Ġиг ÑĢÑĭ",
+      "à¸ļ ี",
+      "ĠØ£ Ùİ",
+      "в ен",
+      "ĠاÙĦج دÙĬد",
+      "ĠÙĦ Ø¥",
+      "Ġ×ķ×IJ ׳×Ļ",
+      "Ġ×Ķס ×Ļ",
+      "иÑĩеÑģк ого",
+      "رÙĪ ØŃ",
+      "à¸ģาร ศึà¸ģษา",
+      "ĠTr Æ°á»Ŀng",
+      "иг ÑĢа",
+      "ıl ması",
+      "Ġм аÑģÑģ",
+      "ãģ¨ãģį ãģ«",
+      "à¸Ĺีà¹Ī à¸ľà¹Īาà¸Ļ",
+      "à¸Ĺีà¹Īà¸ľà¹Īาà¸Ļ มา",
+      "ĠاÙĦساب ÙĤ",
+      "Ġ×ŀ×¢ ×ĺ",
+      "в аÑĤÑĮ",
+      "m Ã¼ÅŁ",
+      "Ġ׾ ׼×ļ",
+      "Ġt á»ĭch",
+      "Ùģ ÙĩÙħ",
+      "تد رÙĬب",
+      "Ø´ Ùĥ",
+      "Ġ×ij ×ŀ×Ļ",
+      "Ġ×ij×ŀ×Ļ ×ķ×Ĺ×ĵ",
+      "ÙĤØ· اع",
+      "ãģª ãģĹ",
+      "×ķצ ×Ļ×IJ",
+      "ĠÙĪ سÙĬ",
+      "з Ñĥ",
+      "Ġy at",
+      "Ġyat ırım",
+      "ë§ İ",
+      "Ġth ắng",
+      "ãģĬ 客",
+      "ãģĬ客 æ§ĺ",
+      "ĠThi ên",
+      "ãģ«å¯¾ ãģĹãģ¦",
+      "ÑĢ иÑģ",
+      "ÙĨت ائ",
+      "ÙĨتائ ج",
+      "Ġ×ŀ שר",
+      "Ġ×ŀשר ×ĵ",
+      "Ġتع اÙĦ",
+      "ĠتعاÙĦ Ùī",
+      "ש ׳×Ļ",
+      "Ùĩ اÙħ",
+      "×IJ׳ ש×Ļ×Ŀ",
+      "Ġżyc ia",
+      "ĠÑĢÑĥб лей",
+      "ÙĬ ض",
+      "Ġkat ıl",
+      "ĠÙħ ÙĪضÙĪع",
+      "Ġvard ır",
+      "ĠÙħÙĨ Ø·ÙĤØ©",
+      "ĠTr ần",
+      "Ġв еÑģ",
+      "ü p",
+      "Ùħ ÙĪÙĨ",
+      "ÑĪ ли",
+      "Ġn óng",
+      "Ø® ÙĦÙģ",
+      "ĠС ÑĤа",
+      "Ġд оÑĢ",
+      "ĠдоÑĢ ог",
+      "ĠwÅĤa ÅĽnie",
+      "eÄŁ in",
+      "Ġhi á»ĥm",
+      "ĠС ам",
+      "ê»ĺ ìĦľ",
+      "ĠÑĦ а",
+      "ãģ» ãģĨ",
+      "ãģ»ãģĨ ãģĮ",
+      "×ķפ ×Ļ×¢",
+      "ê° Ī",
+      "د ÙĪÙĦ",
+      "Ġthu ê",
+      "Ġch á»Ĺ",
+      "Ġëĭ¹ ìĭł",
+      "ãģij ãĤĮ",
+      "ãģijãĤĮ ãģ©",
+      "ë³´ íĺ¸",
+      "ãģķãĤĮ ãģ¦ãģĦãģ¾ãģĻ",
+      "Ġнад о",
+      "ĠìĤ¬ëŀĮ ëĵ¤",
+      "à¹Ģà¸Ĥ à¸ķ",
+      "สม ัย",
+      "z ÅĤ",
+      "ت ÙĪر",
+      "Ġש ת×Ļ",
+      "v ê",
+      "Ġ×ijת ×ķ×ļ",
+      "à¸Ĭ ัย",
+      "ãģĦ ãģ£ãģŁ",
+      "ìĿ ij",
+      "Ġt ầ",
+      "Ġtầ ng",
+      "ש ׼ר",
+      "Ġê¸ Ģ",
+      "Ġ×Ķש ׳×Ķ",
+      "Ġا ÙĨÙĩ",
+      "ç«ĭ ãģ¡",
+      "r és",
+      "füh ren",
+      "ر ØŃÙħ",
+      "ê· ¹",
+      "ĠâĢ «",
+      "Ġsu ất",
+      "à¸Ł ิ",
+      "ÙĬ Ùĩا",
+      "ĠاÙĦ اتØŃاد",
+      "Ġt uyá»ĥn",
+      "ãģ¾ ãĤĭ",
+      "Ġm ại",
+      "Ġng ân",
+      "ãĤ° ãĥ©",
+      "欲 ãģĹãģĦ",
+      "س ار",
+      "ãĤĤãģ® ãģ§ãģĻ",
+      "ки е",
+      "Ġseç im",
+      "åħ¥ ãĤĬ",
+      "ãģªãģ© ãĤĴ",
+      "ÑĤ ÑĢи",
+      "ĠÑģп еÑĨ",
+      "ĠØ£ د",
+      "Ġод но",
+      "ÑĪ ел",
+      "ãĥĩ ãĥ¼ãĤ¿",
+      "ãĤ· ãĤ¹ãĥĨ",
+      "ãĤ·ãĤ¹ãĥĨ ãĥł",
+      "è¡Į ãģį",
+      "ãģ¨æĢĿ ãģ£ãģŁ",
+      "à¹Ģà¸ģิà¸Ķ à¸Ĥึà¹īà¸Ļ",
+      "ĠÑĤ ож",
+      "ĠÑĤож е",
+      "Ġs ạch",
+      "ĠÑģ ÑĢок",
+      "Ġкли енÑĤ",
+      "ĠÙħØ´ رÙĪع",
+      "Ġalt ında",
+      "Ġì ·¨",
+      "ä¸Ń ãģ®",
+      "ãģķãģĽ ãĤĭ",
+      "ãģĻ ãģ¹",
+      "ãģĻãģ¹ ãģ¦",
+      "ê°ľ ë°ľ",
+      "ĠÄij êm",
+      "ãģªãģĦ ãģ®ãģ§",
+      "ì² ł",
+      "×¢ ×ij×ĵ",
+      "Ġd ấu",
+      "à¸Ħà¸Ļ à¸Ĺีà¹Ī",
+      "ĠC ách",
+      "تع ÙĦÙĬÙħ",
+      "Ġh ại",
+      "ãĤ» ãĥķãĥ¬",
+      "ĠÙĨÙģس Ùĩ",
+      "ĠíĨµ íķ´",
+      "ÑĪ ло",
+      "Ġнап ÑĢав",
+      "ĠнапÑĢав лен",
+      "ÑĢÑĥ Ñĩ",
+      "íĶ Į",
+      "Ġ×ijר ×Ļ×IJ",
+      "ãģ® ãģ¿",
+      "ãģ«ãģĬ ãģĦãģ¦",
+      "×ij ׳ק",
+      "ãĤ¨ ãĥ³",
+      "Ø«ÙĦ اث",
+      "Ġm ỹ",
+      "ĠÑģай ÑĤе",
+      "Ġе мÑĥ",
+      "ت غÙĬ",
+      "تغÙĬ ÙĬر",
+      "خص ÙĪص",
+      "ÑĤе ли",
+      "Ġ×ķ׾ ׼ף",
+      "פע ×Ŀ",
+      "Ġпо ÑįÑĤомÑĥ",
+      "ر اÙĨ",
+      "иÑĤел ей",
+      "пиÑģ ан",
+      "×¢ ×¥",
+      "ĠìĤ¬ ìĹħ",
+      "Ùħ ز",
+      "جÙħ ÙĬع",
+      "ë©´ ìĦľ",
+      "à¸ľà¸¥à¸´à¸ķ à¸łà¸±",
+      "à¸ľà¸¥à¸´à¸ķà¸łà¸± à¸ĵ",
+      "à¸ľà¸¥à¸´à¸ķà¸łà¸±à¸ĵ à¸ij",
+      "à¸ľà¸¥à¸´à¸ķà¸łà¸±à¸ĵà¸ij à¹Į",
+      "ĠпÑĢ имеÑĢ",
+      "ãĤŃ ãĥ¼",
+      "l â",
+      "Ġch Äĥm",
+      "缮 ãģ®",
+      "ãģĦ ãģĭ",
+      "ãģ¨è¨Ģ ãģĨ",
+      "×ĸ ×ķ×Ĵ",
+      "Ġ×ij ×ĵ×Ļ",
+      "Ġ×ij×ĵ×Ļ ×ķק",
+      "ãģĬ åºĹ",
+      "à¸ķà¸Ńà¸Ļ à¸Ļีà¹ī",
+      "Ġph á»iji",
+      "п ÑĤ",
+      "สà¸Ļ าม",
+      "Ø· ÙĪ",
+      "ص اØŃ",
+      "صاØŃ Ø¨",
+      "ĠD ü",
+      "ĠDü nya",
+      "Ġп ока",
+      "п ал",
+      "ĠÄij ảo",
+      "ĠاÙĦÙģ ÙĪر",
+      "ĠاÙĦÙģÙĪر Ùĥس",
+      "Ġmá u",
+      "кÑĢ еп",
+      "ĠاÙĦس اعة",
+      "ĠгоÑĢ ода",
+      "Ùģ صÙĦ",
+      "ай ÑĤе",
+      "Ġд ог",
+      "Ġдог овоÑĢ",
+      "ĠØ¥ Ø°",
+      "Ġ×ij׼׾ ׾",
+      "ÙĬ تÙĩ",
+      "×Ĵ ×ijר",
+      "Ġbir ç",
+      "Ġbirç ok",
+      "문 íĻĶ",
+      "ãģĿãģĨ ãģª",
+      "را ØŃ",
+      "ĠÙħ رة",
+      "ĠденÑĮ ги",
+      "f ä",
+      "à¸Ĥà¹īา ว",
+      "ĠÑģов ÑĢем",
+      "ĠÑģовÑĢем енн",
+      "׾×Ĺ ×¥",
+      "èī¯ ãģı",
+      "ĠÙģ Ø£",
+      "Ġ×ķ ×ĸ×Ķ",
+      "Ġз ани",
+      "Ġзани ма",
+      "Ġê°Ģì§Ģ ê³ł",
+      "Ġh Æ¡i",
+      "ãģªãģ® ãģĭ",
+      "ãĥĨ ãĥ¬ãĥĵ",
+      "Ġר ×ij×ķת",
+      "à¸ķ ี",
+      "Ġ×ijש ×ł×ª",
+      "ĠT ại",
+      "Ġthu áºŃn",
+      "Ñģ ел",
+      "Ñij м",
+      "dzi Äĩ",
+      "ĠÑģ ка",
+      "ĠÑģка Ñĩ",
+      "ĠÑģкаÑĩ аÑĤÑĮ",
+      "×ķ×ŀ ×ķ",
+      "г ла",
+      "Ġмин ÑĥÑĤ",
+      "åĩº ãģĻ",
+      "Ġ×Ĺ×Ļ ×Ļ×ij",
+      "Ġת ×Ĵ×ķ×ij×Ķ",
+      "à¸£à¸¹à¸Ľ à¹ģà¸ļà¸ļ",
+      "ни ÑĨа",
+      "ĠÄ° n",
+      "ĠØ£ ع",
+      "Ġض ÙħÙĨ",
+      "Ùħ ثاÙĦ",
+      "ĠyaÅŁ an",
+      "ĠìĹ° 구",
+      "ĠL ê",
+      "ש׾ ×Ĺ",
+      "ãģı ãģªãĤĭ",
+      "ìĹĨ ìĿ´",
+      "ĠÑĤ ÑĢи",
+      "ĠÑĩаÑģÑĤ о",
+      "Ġоб ÑĢаÑĤ",
+      "п ло",
+      "د خ",
+      "دخ ÙĪÙĦ",
+      "س Ùĩ",
+      "à¸Ń าà¸ģ",
+      "à¸Ńาà¸ģ าศ",
+      "Ġ׼ ×ĸ×Ķ",
+      "Ġ×Ķ×¢ סק",
+      "ĠاÙĦØ£ ÙĨ",
+      "å¹´ ãģ«",
+      "×¢ ש×ķ",
+      "Ġש ×¢×ķת",
+      "Ġm Ãłn",
+      "×IJר ×Ļ",
+      "sı yla",
+      "Ùģر ÙĤ",
+      "ни Ñħ",
+      "Ġت ست",
+      "è¦ĭ ãģ¦",
+      "ØŃا ÙĪÙĦ",
+      "×IJ ×Ļ׼×ķת",
+      "ĠbaÅŁ ladı",
+      "st Äħ",
+      "stÄħ pi",
+      "à¸Ĺีà¹Ī à¹Ģรา",
+      "ÙĤر ر",
+      "ج اب",
+      "Ġ×ijר ×ķר",
+      "à¹Ģà¸Ĥà¹īา à¹ĥà¸Ī",
+      "×ŀ׊קר",
+      "al ım",
+      "Ġס ×Ļפ×ķר",
+      "ãģ§ãģĤ ãĤĮãģ°",
+      "Ġש×ŀ ×ķר×ķת",
+      "Ġ×ķ ×ŀ×Ķ",
+      "ãģĵ ãģĿ",
+      "id ée",
+      "ä¸ĭ ãģķãģĦ",
+      "تÙĨا ÙĪÙĦ",
+      "Ġ ลà¹īาà¸Ļ",
+      "Ġìļ°ë¦¬ ëĬĶ",
+      "اÙĨ ا",
+      "ÑģÑĤ ой",
+      "б оÑĤ",
+      "ĠyaÅŁ am",
+      "kö y",
+      "Ø¥ ÙĦ",
+      "ÑĢ Ñĭв",
+      "기 ìĹħ",
+      "Ġ×Ķ×ŀ ×ĵ",
+      "Ġ×Ķ×ŀ×ĵ ×Ļ׳×Ķ",
+      "د ب",
+      "×¢ ×Ļ׳×Ļ",
+      "×ŀ ת×Ĺ",
+      "Ġפ ר×Ļ",
+      "ãĥĭ ãĥ¼",
+      "اÙħ ÙĬ",
+      "Ġnh ằm",
+      "ãĤĮ ãģªãģĦ",
+      "ت عرÙģ",
+      "Ġë§Ī ìĿĮ",
+      "ìĵ °",
+      "Ġh ấp",
+      "ר×Ĵ ×Ļ׾",
+      "ب Ùİ",
+      "Ġr Äĥng",
+      "gl Äħd",
+      "ĠÑģиÑģÑĤем Ñĭ",
+      "Ġkh óa",
+      "ãģ§ãģĻ ãĤĪãģŃ",
+      "大ãģį ãģı",
+      "기 를",
+      "Ġké o",
+      "ÙĪ Ø¡",
+      "ج اÙħ",
+      "جاÙħ ع",
+      "Ġ×¢ ×Ļצ×ķ×ij",
+      "t éri",
+      "Ġת ש",
+      "Ġ×IJ ×ij×Ļ",
+      "ĠCh Æ°Æ¡ng",
+      "à¸ļริ à¹Ģว",
+      "à¸ļริà¹Ģว à¸ĵ",
+      "ãģ¤ ãģı",
+      "Ġ×Ĺ ×ķ׾",
+      "עת ×Ļ×ĵ",
+      "ש ×Ļ×ŀ×Ķ",
+      "ëĤ ¨",
+      "Ġש×IJ ×Ļף",
+      "ĠÙĪاÙĦ Ø¥",
+      "ÑĦ а",
+      "Ġkh ám",
+      "Ġ×ĺ ×ķ×ij×Ķ",
+      "ĠвÑĭ Ñģ",
+      "ĠвÑĭÑģ око",
+      "ĠاÙĦØŃ Ø¯ÙĬØ«",
+      "人 ãĤĤ",
+      "d Ã¼ÄŁÃ¼",
+      "×Ļ×Ĺ ×ķ×ĵ",
+      "تع ÙĦÙĬ",
+      "تعÙĦÙĬ ÙĤ",
+      "l ö",
+      "تØŃ Ø¯ÙĬد",
+      "н его",
+      "ĠÑĥд об",
+      "Ġ׾ ×ŀ×Ļ",
+      "Ġר ×ķצ×Ļ×Ŀ",
+      "Ġج اء",
+      "Ġ×ij ×ĸ×ŀף",
+      "à¸Ľà¸ģ à¸ķิ",
+      "é«ĺ ãģı",
+      "à¸Ľà¸¥ า",
+      "Ġart ık",
+      "Ġbug ün",
+      "ק ׳×Ļ",
+      "Ġkho á",
+      "ĠÙħ رÙĥز",
+      "ĠìŀIJ 기",
+      "در جة",
+      "×ŀש ר×ĵ",
+      "Ġgi ấy",
+      "Ġch óng",
+      "ק פ",
+      "ÙĬب Ø©",
+      "ĠczÄĻ sto",
+      "в али",
+      "Ùĥ ب",
+      "ìŁ ģ",
+      "ส à¸ļาย",
+      "à¸Ľà¸£à¸°à¸Ĭา à¸Ĭà¸Ļ",
+      "×Ĵ ×ķ×£",
+      "ëŁ ī",
+      "ãģ® ãģĵãģ¨",
+      "ล à¸Ń",
+      "Ġngh á»ī",
+      "åŃIJ ãģ©",
+      "åŃIJãģ© ãĤĤ",
+      "à¹Ħà¸Ķ à¹īà¸Ńย",
+      "à¹Ħà¸Ķà¹īà¸Ńย à¹Īาà¸ĩ",
+      "×ĵ ×¢",
+      "ĠاÙĦت Ùī",
+      "ĠÑģов еÑĤ",
+      "Ġqual itÃł",
+      "åĩº ãģĹ",
+      "ĠÑĢÑĥк ов",
+      "ĠÑĢÑĥков од",
+      "ราย ละà¹Ģà¸Ńียà¸Ķ",
+      "ãģªãģĭ ãģªãģĭ",
+      "기 ê´Ģ",
+      "Ġ×Ĺ ×ķש",
+      "Ġ×Ĺ×ķש ×ij",
+      "л оÑĤ",
+      "à¸Ļะ à¸Ħรัà¸ļ",
+      "ק×ij ×ķצ×Ķ",
+      "Ġth ái",
+      "Ġש ×ij×Ķ",
+      "ĠÑĪ кол",
+      "ĠÙĦ ÙĥÙĦ",
+      "à¹ĥà¸Ļ à¸Ĭà¹Īวà¸ĩ",
+      "ĠÙħ ÙĥاÙĨ",
+      "ë ķĮ",
+      "Ġc ải",
+      "ĠCh ÃŃ",
+      "ÑĥÑĩ а",
+      "ìĿ µ",
+      "Ġx ảy",
+      "à¸Ĭà¸Ļ ิà¸Ķ",
+      "Ġc áºŃu",
+      "к ÑĢов",
+      "ss é",
+      "ĠÙĨ ÙĪع",
+      "ĠТ а",
+      "Ø® Ùħس",
+      "פ×ķס ×ĺ",
+      "Ġm ắc",
+      "ĠÄij em",
+      "à¸ģาร à¹ĥà¸Ĭà¹ī",
+      "ר ×ķס",
+      "ĠÐĽ е",
+      "Ġth á»Ń",
+      "รà¹Īาà¸ĩ à¸ģาย",
+      "üz ü",
+      "æĹ¥æľ¬ ãģ®",
+      "ê³¼ ìłķ",
+      "ש ×Ļ×IJ",
+      "ĠìŀĪ ê³ł",
+      "×ij ×ķ׾",
+      "ìķ ħ",
+      "ĠÙĪاÙĦ ا",
+      "ĠÐĽ и",
+      "ĠвÑģ Ñij",
+      "Ġużytk ow",
+      "×Ĺ ×ķ׾",
+      "ر Ùģض",
+      "Ġson uç",
+      "ãģĦ ãģ¾ãģĽãĤĵ",
+      "ìĤ¬ ìĹħ",
+      "ëĪ Ħ",
+      "ÑĤ ек",
+      "Ġud ziaÅĤ",
+      "л ез",
+      "Ġ×Ķ×Ļ ×Ļת×Ļ",
+      "ãĤīãĤĮ ãģ¦",
+      "Ùħس ؤÙĪÙĦ",
+      "ر ار",
+      "ÑĤ ан",
+      "ĠÄij Ãło",
+      "Ġר ×ķ×ij",
+      "Ġ×ijש×ij ×Ļ׾",
+      "ä»ĬåĽŀ ãģ¯",
+      "ãĤ¸ ãĥ¥",
+      "Ġ×¢ ×ijר",
+      "ãģĽ ãģ¦",
+      "п олÑĮ",
+      "ak lı",
+      "Ġk ÃŃnh",
+      "د ت",
+      "лож ение",
+      "ĠاÙĦÙħ ص",
+      "ĠاÙĦÙħص رÙĬ",
+      "à¸Īริà¸ĩ à¹Ĩ",
+      "ĠاÙĦشر ÙĥØ©",
+      "ĠÄij á»ı",
+      "ãĥĽ ãĥĨ",
+      "ãĥĽãĥĨ ãĥ«",
+      "Ñį кон",
+      "Ñįкон ом",
+      "ĠÙĪ عÙĨ",
+      "Ġת ׳",
+      "Ġ×ª×ł ×IJ×Ļ",
+      "ĠاÙĦدÙĪÙĦ ÙĬØ©",
+      "Ġì§Ģ ìĹŃ",
+      "ãģ§ãģĻ ãģĭ",
+      "Ġв аÑĢи",
+      "ĠваÑĢи анÑĤ",
+      "ĠاÙĦع رب",
+      "ел а",
+      "Ġt Æ°á»Ľng",
+      "sk Äħ",
+      "Ġm ặc",
+      "ส ัà¸ģ",
+      "ãĥĵ ãĥ¼",
+      "Ġ×ij ×Ĵ׾",
+      "Ġ×ij×Ĵ׾ ׾",
+      "ãĥķãĤ¡ ãĥ³",
+      "×ij ×Ļצ",
+      "×ij×Ļצ ×ķ×¢",
+      "ли ÑģÑĤ",
+      "à¸Ł ุ",
+      "à¸Łà¸¸ à¸ķ",
+      "à¸Łà¸¸à¸ķ à¸ļà¸Ńล",
+      "à¸Ŀ à¹Īาย",
+      "ìŀIJ ìĿĺ",
+      "Ġس ÙĪÙģ",
+      "Ġש ×Ķת",
+      "Ġê± ¸",
+      "×¢ ×ij×ķ×ĵ",
+      "ãģĻãĤĭ ãģĵãģ¨ãģĮ",
+      "ĠÑĩа ÑģÑĤÑĮ",
+      "ãĤ¢ ãĥ¡ãĥª",
+      "ãĤ¢ãĥ¡ãĥª ãĤ«",
+      "Ġtak ım",
+      "Ġs Ỽ",
+      "ĠsỼ m",
+      "שר ×Ķ",
+      "è¨Ģ ãģĨ",
+      "л ан",
+      "ì» ¤",
+      "׼ ׳×Ķ",
+      "ÙĪÙģ ÙĬ",
+      "íĹ Ī",
+      "lu ÄŁu",
+      "ĠëĮĢ íķ´",
+      "Ġ׾×ij ×Ļת",
+      "Ġ×Ķר×IJש ×ķ׳×Ķ",
+      "ص Ùħ",
+      "Ġsö yled",
+      "Ġsöyled i",
+      "à¸Ľ าà¸ģ",
+      "Ġard ından",
+      "ãģĪ ãģŁ",
+      "à¸Ĺัà¹Īว à¹Ħà¸Ľ",
+      "Ġ׳×ķס ×£",
+      "б олÑĮ",
+      "ãĤĵãģ§ãģĻ ãģijãģ©",
+      "ĠлиÑĪ ÑĮ",
+      "Ġ×ij ×IJ×Ļ",
+      "ĠбÑĭ ÑģÑĤÑĢо",
+      "ส ัà¸Ļ",
+      "Ġ×ij פ׳×Ļ",
+      "л еÑĩ",
+      "ĠاÙĦØ® بر",
+      "Ġsó c",
+      "Ġth ú",
+      "Ġп ÑıÑĤ",
+      "ãģĬ é¡ĺ",
+      "ãģĬé¡ĺ ãģĦ",
+      "ÑĤ ин",
+      "ãģ«ãģ¤ãģĦãģ¦ ãģ¯",
+      "פ ף",
+      "Ġдв ÑĥÑħ",
+      "à¸į ีà¹Ī",
+      "à¸įีà¹Ī à¸Ľ",
+      "à¸įีà¹Īà¸Ľ ุ",
+      "à¸įีà¹Īà¸Ľà¸¸ à¹Īà¸Ļ",
+      "оп еÑĢ",
+      "ĠاÙĦب شر",
+      "ĠاÙĦÙħ اÙĦ",
+      "ıyor uz",
+      "تØŃ ÙħÙĬÙĦ",
+      "à¸ģ ะ",
+      "éĸĵ ãģ«",
+      "×Ĺ ×ķש",
+      "ĠNg uyên",
+      "ãģĦãģ¦ ãģĦãĤĭ",
+      "дÑĥ ÑĪ",
+      "ש פע",
+      "ÑĪ Ñĥ",
+      "å®Ł éļĽãģ«",
+      "ĠÑĢай он",
+      "ĠCh á»ī",
+      "ÙĨ صر",
+      "Ġìļ ´",
+      "Ġìļ´ ìĺģ",
+      "Ġ×Ķ×ĵ ×Ļף",
+      "ØŃد د",
+      "ر ز",
+      "ĠاÙĦد Ùħ",
+      "ĠPh áp",
+      "ÑĤ ÑģÑı",
+      "è¦ĭ ãģĪ",
+      "Ġti á»ĥu",
+      "Ġs á»Ńa",
+      "а ÑİÑĤÑģÑı",
+      "ĠB á",
+      "Ġ×ķ ׼׾",
+      "Ð ĸ",
+      "ÑĪ им",
+      "ìĿ´ ëĬĶ",
+      "л ев",
+      "d ık",
+      "Ġprés ente",
+      "Ġara ç",
+      "صد ÙĤ",
+      "Ġпом ог",
+      "ĠاÙĦشر ÙĤ",
+      "ĠÙĪاÙĦ Ø°ÙĬ",
+      "رÙĬ ا",
+      "×ij ׳×ķת",
+      "Ġng á»ĵi",
+      "ר ×ķפ",
+      "ר×ķפ ×IJ",
+      "Ġth ấp",
+      "ãĤĦ ãģ¯",
+      "ãĤĦãģ¯ ãĤĬ",
+      "ĠاÙĦج دÙĬدة",
+      "éĿŀ常 ãģ«",
+      "ÙĬÙĦ ÙĬ",
+      "ìª ½",
+      "تع اÙħÙĦ",
+      "ãģł ãģ¨æĢĿãģĦãģ¾ãģĻ",
+      "Ùħ Ùħ",
+      "иÑĤе ли",
+      "ãĤµãĤ¤ ãĤº",
+      "اد ات",
+      "ĠاÙĦÙħ اÙĦÙĬØ©",
+      "Ùĥات ب",
+      "к ли",
+      "веÑĢ Ñħ",
+      "ни Ñĩ",
+      "Ġ×ľ×¢ ×ij×ķ×ĵ",
+      "׾ ×Ļ×Ķ",
+      "ØŃ Ùİ",
+      "ãĤ¤ ãĥĻ",
+      "ãĤ¤ãĥĻ ãĥ³ãĥĪ",
+      "Ġת ×Ĵ×ķ×ij×ķת",
+      "ÑĦ он",
+      "ĠдÑĢÑĥг ие",
+      "×IJ ×ĸ×ķר",
+      "Ġper ò",
+      "ìķ ŀ",
+      "åĢŁ ãĤĬ",
+      "ר צ×Ļ",
+      "×IJ ×ĸ",
+      "алÑĮ нÑĭÑħ",
+      "Ġê²ĥ ìľ¼ë¡ľ",
+      "ĠпÑĢав о",
+      "ĠاÙĦØ£ رض",
+      "à¹Ģà¸Ĺ à¸Ħ",
+      "à¹Ģà¸Ĺà¸Ħ à¹Ĥà¸Ļ",
+      "à¹Ģà¸Ĺà¸Ħà¹Ĥà¸Ļ à¹Ĥล",
+      "à¹Ģà¸Ĺà¸Ħà¹Ĥà¸Ļà¹Ĥล ย",
+      "à¹Ģà¸Ĺà¸Ħà¹Ĥà¸Ļà¹Ĥลย ี",
+      "צ ר×Ļ",
+      "ĠÐļ Ñĥ",
+      "ıl ma",
+      "決 ãĤģ",
+      "ا ÙĪ",
+      "Ġ×ĵ ק×ķת",
+      "à¸Ħร ู",
+      "ĠÙħست ÙĪÙī",
+      "à¸Ľ à¹īà¸Ńà¸ĩ",
+      "à¸Ľà¹īà¸Ńà¸ĩ à¸ģัà¸Ļ",
+      "×ĵ ×ķ×ŀ×Ķ",
+      "ĠÑģ егоднÑı",
+      "س ÙĪÙĤ",
+      "ר×Ĺ ×ķ×ij",
+      "ĠØ¥ دارة",
+      "Ñħ ож",
+      "éģİ ãģİ",
+      "à¸Ħ à¸Ń",
+      "нÑĥ л",
+      "×ķ׼ ×Ķ",
+      "ÙĪ اÙģÙĤ",
+      "׼׾ ׾",
+      "Ġ×Ķ ×ĵ×ķ",
+      "Ġl Ä©nh",
+      "Ġkh ảo",
+      "×IJ×ŀ צע",
+      "ë¨ ¸",
+      "Ġ׼ ×Ļצ",
+      "Ġ׼×Ļצ ×ĵ",
+      "Ġдолж нÑĭ",
+      "หว ัà¸ĩ",
+      "ãĥĩ ãĤ¶",
+      "ãĥĩãĤ¶ ãĤ¤ãĥ³",
+      "Ġng á»Ŀ",
+      "ä¸Ń ãģ«",
+      "à¸ģลัà¸ļ มา",
+      "جÙħ اÙĦ",
+      "à¸Ķัà¸ĩ à¸ģลà¹Īาว",
+      "س ÙĥÙĨ",
+      "س ÙĨ",
+      "Ġözellik le",
+      "з еÑĢ",
+      "rz ÄĻ",
+      "×ŀ ×ķר×Ķ",
+      "Ġl ạ",
+      "×ŀ ×Ļ׳×Ļ",
+      "ר ×Ļת",
+      "ãģĿãĤĮ ãģĮ",
+      "ãģĭ ãĤĮ",
+      "ĠÙĬÙħÙĥÙĨ Ùĥ",
+      "öff entlich",
+      "г ан",
+      "ĠاÙĦØŃ ÙĦ",
+      "ĠmiÄĻd zy",
+      "ĠÑĩа ÑģÑĤи",
+      "ujÄħ cy",
+      "ĠbaÄŁ lı",
+      "ĠiliÅŁ ki",
+      "Ùģ اء",
+      "ãĥª ãĥ³ãĤ°",
+      "Ġhã ng",
+      "ĠконÑĤ ÑĢ",
+      "ĠконÑĤÑĢ ол",
+      "к оп",
+      "ש ×Ļ×¢",
+      "ש×Ļ×¢ ×ķר",
+      "ĠÐĴ аÑĪ",
+      "Ġ×Ķ תק",
+      "ÙħÙĨ ع",
+      "ĠpolÃŃt ico",
+      "Ġг олов",
+      "ĠØ¥ ÙĬ",
+      "Ø¥ ÙĨتاج",
+      "à¸ļ ิ",
+      "Ġг овоÑĢ",
+      "ĠговоÑĢ иÑĤ",
+      "Ġph á»ķ",
+      "ĠÑģем ÑĮ",
+      "ãģ¯ ãģĤãĤĬãģ¾ãģĽãĤĵ",
+      "ĠÙĪ است",
+      "×ŀש פ×ĺ",
+      "з ем",
+      "×ŀ×ĵ ×ijר",
+      "Ġíģ °",
+      "ĠìĿ´ ë²Ī",
+      "ê°Ģ ëĬĶ",
+      "Ġì§Ģ ìĽIJ",
+      "Ġca ÅĤy",
+      "Ġgeli ÅŁtir",
+      "Ñģк ое",
+      "pos é",
+      "Ġkh ô",
+      "à¸ķิà¸Ķ à¸ķาม",
+      "miss ão",
+      "Ġ׾ ×ŀר",
+      "Ġ׾×ŀר ×ķת",
+      "Ġb ó",
+      "à¸ķรวà¸Ī สà¸Ńà¸ļ",
+      "Ġngh á»ģ",
+      "Ġб из",
+      "Ġбиз неÑģ",
+      "ÑģÑĤ еÑĢ",
+      "ÙĪ Ùİ",
+      "楽 ãģĹãģ",
+      "楽ãģĹãģ ¿",
+      "ãģĵãĤĮ ãģĭãĤī",
+      "wiÄħ zan",
+      "ส à¸Ńà¸Ļ",
+      "Ùħ ÙĪر",
+      "׳×ĵ ׾",
+      "Ġ×Ķ×IJ ×ĵ×Ŀ",
+      "Ġм олод",
+      "ØŃ Ùħا",
+      "ØŃÙħا ÙĬØ©",
+      "ÑģÑĤ ÑĢан",
+      "Ġbu á»ķi",
+      "ת×Ļ ×Ļ×Ŀ",
+      "abile ceÄŁi",
+      "L Ä°",
+      "à¹Ģย à¸Ńะ",
+      "à¸Ī ร",
+      "س ÙĥاÙĨ",
+      "à¸Ļ ัà¸Ķ",
+      "Ġm ấy",
+      "ĠÐij а",
+      "s ÅĤaw",
+      "ĠÙģ ÙĦا",
+      "ĠкоÑĤоÑĢ ой",
+      "Ġпло Ñī",
+      "ĠплоÑī ад",
+      "ãĤĤ ãģĤãĤĬ",
+      "sz czÄĻ",
+      "×Ļפ ×ķ",
+      "ש×ŀ ת",
+      "owa ÅĤa",
+      "Ġn ông",
+      "צ×ij ×IJ",
+      "ĠìŀĪ ìĹĪ",
+      "ãģ¾ ãģ¨",
+      "ãģ¾ãģ¨ ãĤģ",
+      "ÙĤÙĪ ات",
+      "ãģ¿ ãĤĵãģª",
+      "Ġ׼ ×ŀ×¢×ĺ",
+      "Ġx úc",
+      "ï¼ Ĩ",
+      "r ÄĻ",
+      "rÄĻ cz",
+      "×ĵ ×ŀ×Ļ",
+      "Ġt áºŃn",
+      "à¸Ķ วà¸ĩ",
+      "ê²½ ìłľ",
+      "п ÑĥÑĤ",
+      "أ ربع",
+      "Ġ×ŀ שת×ŀש",
+      "ãĤ¿ãĤ¤ ãĥĹ",
+      "Ġìłľ ê°Ģ",
+      "Ġ׾ ׼ף",
+      "ĠобÑĢаз ом",
+      "ÙĬÙĥ ا",
+      "w ÅĤ",
+      "wÅĤ asn",
+      "ĠاÙĦÙĪØ·ÙĨ ÙĬØ©",
+      "بÙĬ ب",
+      "×ŀ ׾×Ļ",
+      "к ÑĢаÑĤ",
+      "기 ìĹIJ",
+      "ÙĤ اد",
+      "ĠÙĦ دÙī",
+      "à¸Ħวาม รูà¹ī",
+      "×ŀ×ĵ×Ļ׳ ×Ļ×ķת",
+      "ê² ¨",
+      "Ġíĺ Ħìŀ¬",
+      "ש ת×Ļ",
+      "м ол",
+      "Ġmá i",
+      "à¸ŀิ ม",
+      "à¸ŀิม à¸ŀ",
+      "à¸ŀิมà¸ŀ à¹Į",
+      "หล วà¸ĩ",
+      "Ġx uyên",
+      "×Ĺ ×¡×¨",
+      "رÙĪ ÙĨ",
+      "ãģĿãģĨ ãģĦãģĨ",
+      "ãģĿãĤĮ ãģŀ",
+      "ãģĿãĤĮãģŀ ãĤĮ",
+      "Ġ׼ ש×Ķ",
+      "ÐŁ ÑĢав",
+      "×ŀ×ij צע",
+      "ع رب",
+      "Ġbü yü",
+      "פ×Ļת ×ķ×Ĺ",
+      "à¸Ī à¸ļ",
+      "ĠØ£ Ùĥبر",
+      "שר ת",
+      "×ŀ׼ ש×Ļר",
+      "ĠÙĪ Ùħع",
+      "ãģ® ãģŁãĤģãģ«",
+      "à¸Ļ ัà¸ļ",
+      "ì° °",
+      "ãĥª ãĥķãĤ©",
+      "ãĥªãĥķãĤ© ãĥ¼ãĥł",
+      "Ġc Æ°á»Ŀng",
+      "ĠìłĢ íĿ¬",
+      "ÙħÙĨظ ÙħØ©",
+      "Ġhiç bir",
+      "ãģ§ãģ¯ ãģĤãĤĬãģ¾ãģĽãĤĵ",
+      "ร à¸Ńย",
+      "ëIJľ ëĭ¤",
+      "ãģĻãģIJ ãģ«",
+      "к ла",
+      "Ġürün ler",
+      "Ġki á»ĥu",
+      "ĠëĤĺ ëĬĶ",
+      "ÑĤ ки",
+      "Ñģ им",
+      "Ġchá»ī nh",
+      "ãĤĤ ãģªãģĦ",
+      "ศ รี",
+      "æĽ¿ ãģĪ",
+      "ta ÅŁ",
+      "Ġب ÙĥÙĦ",
+      "Ġ×ķ ×Ļש",
+      "vis ão",
+      "ä¼ Ŀ",
+      "ä¼Ŀ ãģĪ",
+      "ÙĦ د",
+      "׾ ×Ļ×ŀ",
+      "׾×Ļ×ŀ ×ķ×ĵ",
+      "t ória",
+      "د Ùij",
+      "اÙħ ر",
+      "Ġê·¸ëłĩ ê²Į",
+      "Ġmateria ÅĤ",
+      "à¸Ĺ รา",
+      "à¸Ĺรา à¸ļ",
+      "ãģ®æĸ¹ ãģĮ",
+      "ãģ¦ ãģįãģŁ",
+      "ض غ",
+      "ضغ ط",
+      "ĠÙĬ عÙĨÙĬ",
+      "ел о",
+      "×IJ×Ķ ×ij×Ķ",
+      "×¢ ×ŀ",
+      "ÅŁ ık",
+      "ìŀIJ ëĬĶ",
+      "ãĤ¿ ãĥ³",
+      "Ġb áºŃt",
+      "×ŀשפ ×Ĺ×Ķ",
+      "к ÑĢи",
+      "б ли",
+      "สั à¸ķ",
+      "สัà¸ķ วà¹Į",
+      "ĠسÙĨ ÙĪات",
+      "ĠPh Æ°Æ¡ng",
+      "ãģ¦ãģĹãģ¾ ãģ£ãģŁ",
+      "ãģª ãģľ",
+      "Ġ×ij×IJ ×ķ",
+      "Ġc án",
+      "س جÙĦ",
+      "Ġl ẽ",
+      "ãĤ± ãĥ¼ãĤ¹",
+      "Ġק ×Ļ×ij׾",
+      "à¸ļà¸Ĺ à¸Ħวาม",
+      "Ġ×ķ ׼ף",
+      "ĠпÑĢедÑģÑĤав лен",
+      "Ġn á»iji",
+      "Ġcoment ário",
+      "ени ем",
+      "Ġtá» ı",
+      "l Ãł",
+      "Ġש×Ķ ×Ļ×Ķ",
+      "Ñģл ав",
+      "ĠاÙĦ ÙĪÙĦا",
+      "ĠاÙĦÙĪÙĦا ÙĬات",
+      "ÙĦج ÙĨØ©",
+      "ק×ķר ×IJ",
+      "бÑĭ ÑĤ",
+      "Ġì ¦",
+      "Ġì¦ ī",
+      "ãģ§ãģĻ ãģĹ",
+      "หรืà¸Ń à¹Ħมà¹Ī",
+      "за ÑīиÑĤ",
+      "ÙģÙĦ سطÙĬÙĨ",
+      "Ġmi á»ħn",
+      "à¹Ģย à¹ĩà¸Ļ",
+      "ĠçalÄ±ÅŁ an",
+      "×Ļ×Ĵ ×Ķ",
+      "ĠE ÄŁ",
+      "ĠEÄŁ itim",
+      "ãĥĥãĤ· ãĥ¥",
+      "Ġоп Ñĭ",
+      "ĠопÑĭ ÑĤ",
+      "ر غ",
+      "رغ ب",
+      "ĠÑģво иÑħ",
+      "à¸Ľà¸£à¸° à¸ķ",
+      "à¸Ľà¸£à¸°à¸ķ ู",
+      "Ġ×ŀ×IJ ×ĵ",
+      "׼ ×ķ׳×Ļ×Ŀ",
+      "à¸Ļ ี",
+      "ĠвÑĭ Ñħод",
+      "ãģ®ä¸Ń ãģ«",
+      "פ ׾×IJ",
+      "ĠÙĪ ÙĦÙĬس",
+      "פ×ķר ס",
+      "פ×ķרס ×Ŀ",
+      "Ùħ سÙĦÙħ",
+      "Ġng ôi",
+      "×ĵ ×ŀ×ķת",
+      "ãĤĴ使 ãģ£ãģ¦",
+      "ĠпомоÑī ÑĮÑİ",
+      "أ سر",
+      "бл ок",
+      "ÙĤ Ùĩ",
+      "ãģĹãģ¾ ãģĦ",
+      "ãģ¨ ãģĹãģŁ",
+      "Ġп еÑģ",
+      "ãĥī ãĥ«",
+      "×Ĺ ×Ŀ",
+      "ãģĹãģª ãģĮãĤī",
+      "ĠÐŁ ÑĢед",
+      "ãĥģãĤ§ ãĥĥãĤ¯",
+      "å¼· ãģĦ",
+      "ש ×Ļר×ķת",
+      "д аеÑĤ",
+      "×Ļ×ij ×ķ",
+      "Ġgen ç",
+      "ил аÑģ",
+      "илаÑģ ÑĮ",
+      "ĠبÙĦ د",
+      "æĤ ª",
+      "æĤª ãģĦ",
+      "Ġ×ŀ שת",
+      "æ§ĺ ãĢħ",
+      "æ§ĺãĢħ ãģª",
+      "à¸ĺรรม à¸Ĭาà¸ķิ",
+      "ĠÙĥ اÙħÙĦ",
+      "ĠاÙĦس Ùħ",
+      "×ij×ĺ ×Ļ×Ĺ",
+      "c á",
+      "g ência",
+      "ãĤ¹ãĤ¿ ãĥ¼",
+      "à¸Ĺำ à¸ģาร",
+      "×Ļ׾ ת",
+      "Ġ×Ļ ×ķצ×IJ",
+      "w ój",
+      "à¸ļุ à¸Ħ",
+      "à¸ļุà¸Ħ à¸Ħล",
+      "ع تÙħ",
+      "عتÙħ د",
+      "ãģĿãĤĮ ãģ«",
+      "ĠاÙĦت ارÙĬØ®",
+      "ÙĤر اء",
+      "Ġyönet im",
+      "ק שר",
+      "ĠÑģп оÑĢÑĤ",
+      "Ġר×IJש ×ķף",
+      "Ġseñ al",
+      "Ġch ắn",
+      "çĦ¡ ãģĦ",
+      "ĠдоÑģÑĤ аÑĤ",
+      "ĠдоÑģÑĤаÑĤ оÑĩно",
+      "Ġá gua",
+      "à¸ģร à¸ĵ",
+      "à¸ģรà¸ĵ ี",
+      "Ġ×ŀש ×ķ",
+      "Ġtr ải",
+      "ë² Į",
+      "ujÄħ cych",
+      "Ùģر د",
+      "à¹ĥ à¸ģล",
+      "à¹ĥà¸ģล à¹ī",
+      "ãĤĭ ãģ®ãģ¯",
+      "ר×ķ ×ķ×Ĺ",
+      "ÙĨ Ùĥ",
+      "ĠاÙĦÙĨ ÙĤ",
+      "ãģ®ãģ§ ãģĹãĤĩãģĨ",
+      "ãģ®ãģ§ãģĹãĤĩãģĨ ãģĭ",
+      "Ùħ عرÙģ",
+      "ÙħعرÙģ Ø©",
+      "ÑĥÑī е",
+      "Ġ×ij×¢ ×Ļקר",
+      "ت صÙĦ",
+      "Ġ×Ķ×IJ ר",
+      "Ġ×Ķ×IJר ×¥",
+      "ĠÅŀ i",
+      "à¸Ĥา à¸Ķ",
+      "íŀ ĺ",
+      "ãģªãĤĵ ãģ¨",
+      "ĠìĤ¬ëŀ ij",
+      "l Ã¼ÄŁÃ¼",
+      "ب اء",
+      "ĠاÙĦØ¢ خر",
+      "Ġfam ÃŃlia",
+      "ĠTh áng",
+      "Ñī ениÑı",
+      "ãĤ¯ ãĥŃ",
+      "ĠTh ứ",
+      "æĽ¸ ãģį",
+      "ен ной",
+      "ìŀ ¡",
+      "бл аг",
+      "благ о",
+      "п ов",
+      "à¹ģ ว",
+      "à¸ĩ à¸Ħà¹Į",
+      "à¸Ńัà¸Ļ à¸Ķัà¸ļ",
+      "ãģĤ ãģĴ",
+      "ร à¹īาย",
+      "ün ün",
+      "Ġ×Ļ׼×ķ׾ ×Ķ",
+      "з он",
+      "ĠÐľ и",
+      "маÑĤ еÑĢиал",
+      "Ġë³´ ë©´",
+      "ØŃÙģ ظ",
+      "ê Ìģ",
+      "ãģ« ãģĻãĤĭ",
+      "Ġת ×IJ",
+      "Ġ×Ķס ×ķ",
+      "ĠÑģÑĤ оÑĢ",
+      "ĠÑģÑĤоÑĢ он",
+      "ãĥĪ ãĥĥãĥĹ",
+      "ÅĤo ÅĽÄĩ",
+      "ëħ ¼",
+      "ëĵ Ŀ",
+      "ĠÙĪاÙĦ ع",
+      "ì¶ Ķ",
+      "Ġ×Ļצ ×IJ",
+      "ĠÑĢаз дел",
+      "алÑĮ наÑı",
+      "×IJ׳ ש×Ļ",
+      "spo ÅĤ",
+      "spoÅĤ ec",
+      "spoÅĤec zn",
+      "Ø¥ عÙĦ",
+      "إعÙĦ اÙĨ",
+      "ÙĤÙĪ Ùī",
+      "íķĺë©´ ìĦľ",
+      "تط ÙĪر",
+      "Ġsi êu",
+      "Ỽ t",
+      "д ви",
+      "дви ж",
+      "Ġqu ần",
+      "k ıl",
+      "ĠпÑĢи зна",
+      "ĠH ã",
+      "ĠHã y",
+      "ĠباÙĦ ت",
+      "man ın",
+      "ãĤ« ãĥ«",
+      "Ġk á»·",
+      "ק ׾×Ļ",
+      "ëIJĺ ì§Ģ",
+      "تعÙĦ Ùħ",
+      "ìĭľ ìĦ¤",
+      "ìĭ ¶",
+      "íĺ ¼",
+      "Ùĥ ÙĬÙģ",
+      "売 ãĤĬ",
+      "วิ à¸Ĭา",
+      "б ал",
+      "ĠØ£ ØŃ",
+      "Ġдолж ен",
+      "รา à¸ĩ",
+      "ราà¸ĩ วั",
+      "ราà¸ĩวั ล",
+      "Ùħ اء",
+      "ج ار",
+      "Å ļ",
+      "Ġ×ŀ×IJ ×ĸ",
+      "ר ×ŀ×Ķ",
+      "ãģĭãĤĤãģĹãĤĮ ãģªãģĦ",
+      "ét ude",
+      "czÄħ c",
+      "Ġg ór",
+      "×ł×¡ ×Ķ",
+      "Ùħ ÙĬد",
+      "ĠÐŁ еÑĢе",
+      "أ خر",
+      "ãģĿãģ® å¾Į",
+      "à¹Ģà¸Ķียว à¸ģัà¸Ļ",
+      "×ŀ ×Ĵ×ķ",
+      "×ŀ×Ĵ×ķ ×ķף",
+      "д ов",
+      "mas ına",
+      "×¢ ׳×Ķ",
+      "ãĤ± ãĥĥãĥĪ",
+      "ס ע",
+      "סע ×Ļ×£",
+      "ĠT Æ°",
+      "Ġt óc",
+      "íĻľ ëıĻ",
+      "ĠÐŀ д",
+      "ĠÐŀд нако",
+      "Ġdol ayı",
+      "ؤ Ùĥد",
+      "ê³Ħ íļį",
+      "׾ ר",
+      "в еÑĩ",
+      "Ġkh ợi",
+      "Ġth ủy",
+      "×ĵ ף",
+      "ร à¸ģ",
+      "à¸ļั à¸ķร",
+      "à¹Ģà¸ģ à¹Īา",
+      "ĠاÙĦØ« اÙĦ",
+      "ĠاÙĦثاÙĦ Ø«",
+      "Ġpod rá",
+      "ער ×Ļ",
+      "ÙĨج اØŃ",
+      "Ġkh ắc",
+      "ì¸ ¡",
+      "Ä° M",
+      "ãĤ» ãĥĥãĥĪ",
+      "ż enia",
+      "Ġ׾×Ĺ ×ijר",
+      "er Ãł",
+      "ì ´Ī",
+      "Ġkü ç",
+      "Ġküç ük",
+      "ات ÙĩÙħ",
+      "à¸ĭ à¹Į",
+      "Ùħشار ÙĥØ©",
+      "ĠاÙĦ بط",
+      "Ġd ây",
+      "ен нÑĭм",
+      "à¸Ĺีà¹Ī à¹Ħมà¹Ī",
+      "ÙĤ Ùİ",
+      "Ġv ượt",
+      "Ġtr ì",
+      "Ġwp ÅĤyw",
+      "A Åŀ",
+      "з о",
+      "ĠاÙĦس ÙĬد",
+      "à¸Ĺะ à¹Ģล",
+      "ĠÑģодеÑĢж а",
+      "ع Ø·ÙĬ",
+      "ĠاÙĦع ÙĨ",
+      "èĢħ ãģĮ",
+      "à¹Ģ หà¸Ļ",
+      "à¹Ģหà¸Ļ ืà¸Ń",
+      "Ġb ÃŃ",
+      "Ġüzer inden",
+      "ĠV Å©",
+      "Ġnu ôi",
+      "ÙĨ Ùħ",
+      "алÑĮ ного",
+      "×¢ ×Ļף",
+      "ØŃ Ø¶Ø±",
+      "ĠоÑĤ дел",
+      "ëª ĩ",
+      "ìķ ¡",
+      "ĠÙĦدÙĬ Ùĩ",
+      "ìĻ ľ",
+      "Ġse ktör",
+      "Ġвозмож но",
+      "ĠÐĶ ж",
+      "Ġh ô",
+      "äºĭ ãģĮ",
+      "иÑĢов ание",
+      "алÑĮ ной",
+      "Ġ미 êµŃ",
+      "ر ØŃÙĦ",
+      "ĠÑįк Ñģ",
+      "пÑĢав лÑı",
+      "Ġnh á»Ŀ",
+      "ĠÄij ẩ",
+      "ĠÄijẩ y",
+      "Ùģ Ùĥر",
+      "ĠÙĪØ£ ضاÙģ",
+      "ãĥIJ ãĤ¹",
+      "ת×ķ׼ ׳×Ļת",
+      "ÑĤел ей",
+      "ĠØ¥ÙĦÙĬ Ùĩ",
+      "ãģ¨è¨Ģ ãģ£ãģ¦",
+      "Ġдв е",
+      "Ġch ấp",
+      "ĠL ö",
+      "à¸Ħล ิ",
+      "à¸Ħลิ à¸Ľ",
+      "Ġس ÙĪر",
+      "ĠسÙĪر ÙĬا",
+      "×ŀ×Ĺ ×ķ",
+      "st ä",
+      "д об",
+      "Ġni á»ĩm",
+      "ãģ® 大",
+      "פר×ķ ×Ļק",
+      "פר×ķ×Ļק ×ĺ",
+      "ĠCh âu",
+      "Ġ×ŀ×Ķ ×Ŀ",
+      "Ñģк им",
+      "ĠполÑĥÑĩ иÑĤÑĮ",
+      "ÙĬ ÙĪÙħ",
+      "Ø« ÙĪر",
+      "פ×ķ׾ ×Ļ×ĺ",
+      "פ×ķ׾×Ļ×ĺ ×Ļ",
+      "ĠмеÑģÑı ÑĨ",
+      "åħ¨ ãģ¦",
+      "ĠاÙĦÙħ جÙĦس",
+      "ĠاÙĦت اÙĦÙĬ",
+      "Ġ׊ר",
+      "åIJij ãģij",
+      "׼ ×ŀ×Ķ",
+      "б ед",
+      "أ عض",
+      "أعض اء",
+      "ÙĪÙĦ د",
+      "วà¹Īา à¸Īะ",
+      "Ġb ánh",
+      "à¸Ļิ ย",
+      "à¸Ļิย ม",
+      "à¸Ľà¸£à¸° à¸ģัà¸Ļ",
+      "ÑģÑĤав иÑĤÑĮ",
+      "à¸ŀ à¸Ļัà¸Ļ",
+      "ĠÑį ÑĦÑĦ",
+      "ĠÑįÑĦÑĦ екÑĤив",
+      "Ġав ÑĤоÑĢ",
+      "ĠÄIJ Äĥng",
+      "Ġth Æ°á»Łng",
+      "ãĤĴ æĦŁãģĺ",
+      "à¸ģัà¸ļ à¸ģาร",
+      "å¾Į ãģ«",
+      "Ġya ÄŁ",
+      "ست اÙĨ",
+      "Ġli á»ģn",
+      "ãģĦ ãģ¾",
+      "i êu",
+      "à¹Ĥà¸Ķ à¸Ļ",
+      "ĠÙĦ Ø°ÙĦÙĥ",
+      "à¹Ĥรà¸ĩ à¹Ģรียà¸Ļ",
+      "צ ×Ļ×Ĵ",
+      "ĠاÙĦÙħ عÙĦÙĪÙħات",
+      "ç§ģ ãģŁãģ¡",
+      "à¸Ĺีà¹Ī à¸Ħุà¸ĵ",
+      "ãģ«ãģª ãģ£ãģ¦ãģĦãĤĭ",
+      "×ŀ×ĵ ×Ļ׳×Ķ",
+      "ס ׼×Ŀ",
+      "Ġв не",
+      "à¸ŀ à¸Ļัà¸ģà¸ĩาà¸Ļ",
+      "ÑĢ ей",
+      "à¹Ģà¸Īà¹īา หà¸Ļà¹īาà¸Ĺีà¹Ī",
+      "ĠHi á»ĩn",
+      "Ġméd ico",
+      "ĠتØŃ ÙĤÙĬÙĤ",
+      "ÑĮ ÑĤе",
+      "miÅŁ ti",
+      "ÙĤÙĬ ادة",
+      "ãĤı ãģĭãĤĬ",
+      "มา à¸Īาà¸ģ",
+      "ëħ Ģ",
+      "ãģ«éĸ¢ ãģĻãĤĭ",
+      "×IJר×Ĵ ×ķף",
+      "m ètre",
+      "Ġעצ ×ŀ×Ļ",
+      "ĠCh úa",
+      "รูà¹ī à¸Ī",
+      "รูà¹īà¸Ī ัà¸ģ",
+      "ì£ Ħ",
+      "ëĭ µ",
+      "à¹ģà¸Ĺ à¹ī",
+      "Ġgeç en",
+      "Ġlan ça",
+      "ĠاÙĦ بØŃØ«",
+      "×ĵ ×ŀ×ķ",
+      "ãģ¯ ãģĺ",
+      "ãģ¯ãģĺ ãĤģ",
+      "Ġdön Ã¼ÅŁ",
+      "è¿ij ãģı",
+      "à¹Ģส ม",
+      "à¹Ģสม à¸Ń",
+      "ëĿ ½",
+      "Ġü ç",
+      "á» ŀ",
+      "ÑĪ аÑı",
+      "à¸Ĺ ร",
+      "ØŃ ÙĤÙĬÙĤØ©",
+      "à¸Ĥà¸Ńà¸ĩ à¸ģาร",
+      "Ġ무 ìĹĩ",
+      "Ġ×Ķ ׼ר",
+      "ĠاÙĦص ÙĬÙĨ",
+      "ĠлÑİ Ð´Ð¸",
+      "à¸ķ าย",
+      "ب ÙĪÙĦ",
+      "Ġvi êm",
+      "Ġthi á»ĩu",
+      "à¸ģ à¸Ķ",
+      "Ġ׾ ×ĵ×ijר",
+      "פ ׳×Ķ",
+      "×IJר ×ij×¢",
+      "س Ùī",
+      "ĠاÙĦسÙĬ اس",
+      "ĠاÙĦسÙĬاس ÙĬØ©",
+      "yd ı",
+      "ÙĪØŃد Ø©",
+      "ĠдеÑıÑĤелÑĮ ноÑģÑĤи",
+      "Ġ×ķ×Ķ ×ŀ",
+      "п еÑĩ",
+      "пеÑĩ аÑĤ",
+      "иÑĢов аниÑı",
+      "ĠÑģ ог",
+      "ĠÑģог лаÑģ",
+      "Ġ׼ ×ĵ",
+      "Ġ׼×ĵ ×IJ×Ļ",
+      "ĠиÑģполÑĮзов аÑĤÑĮ",
+      "ס פ×ķר×ĺ",
+      "Ġil çe",
+      "exp érience",
+      "ĠTh á»Ŀi",
+      "Ä° K",
+      "à¹Ħà¸Ł à¸Łà¹īา",
+      "ëĵ¤ ìĹIJê²Į",
+      "à¸Ľà¸£à¸° à¹Ģà¸ł",
+      "à¸Ľà¸£à¸°à¹Ģà¸ł à¸Ĺ",
+      "Ġmü mk",
+      "Ġmümk ün",
+      "Ġ×IJ×ķת ׳×ķ",
+      "ìĦ± ìĿĦ",
+      "ĠìĿ´ ìľł",
+      "زÙĬ ارة",
+      "Ġolduk ça",
+      "r ób",
+      "ĠØ£ ÙĨا",
+      "Ġ×Ķ ×ij×Ļ",
+      "Ñģ ен",
+      "×¢ ×Ļקר",
+      "×Ļ×ĵ ×ķ×¢",
+      "d zÄħ",
+      "Ùħ عÙĦÙĪÙħات",
+      "ش اب",
+      "Ġpar ça",
+      "à¸Ļะ à¸Ħะ",
+      "ب اس",
+      "ĠÑĤоÑĢ г",
+      "ĠÑĤоÑĢг ов",
+      "Ġ×Ĺ ×ĵר",
+      "׼ ר×ĺ",
+      "׼ר×ĺ ×Ļס",
+      "ĠA yrıca",
+      "ÃªÌ £",
+      "ìľ ¨",
+      "ĠÑĤак ие",
+      "Ġ×ŀצ ×ķ×Ļ",
+      "ãĥ©ãĥ³ ãĤŃãĥ³ãĤ°",
+      "ש×Ļ×ķ ×ķק",
+      "åīį ãģ®",
+      "ĠB ảo",
+      "Ñī Ñĥ",
+      "æĹ© ãģı",
+      "ĠPh òng",
+      "à¸ŀระ ราà¸Ĭ",
+      "פ ×Ĺ×ķת",
+      "Ġг л",
+      "Ġгл аз",
+      "à¸Ĺ à¹Īา",
+      "Ġd ạy",
+      "ÑĢ оÑģÑĤ",
+      "à¹Ĥà¸Ķย à¹Ģà¸īà¸ŀาะ",
+      "Ġqu áºŃn",
+      "Ġ×Ĺ×ijר ×ķת",
+      "m ême",
+      "mÄ±ÅŁ tı",
+      "ĠاÙĦت داÙĪÙĦ",
+      "Ġn ạn",
+      "Ġ×Ķ ×ĵ×Ļ",
+      "ĠاÙĦØ· رÙĬÙĤ",
+      "×Ĵ ×ķת",
+      "Ġ×Ķ ×ĵר×ļ",
+      "ujÄħ ce",
+      "Ġch ữ",
+      "ãĤĤãģ® ãģ®",
+      "ë° Ľ",
+      "ãģķãĤĵ ãģ¯",
+      "Ġyard ım",
+      "ĠاÙĦع Ùħ",
+      "Ġì§Ħ íĸī",
+      "Ġ×Ļ ×Ĺ",
+      "Ġ×Ļ×Ĺ ×¡×Ļ",
+      "ĠاÙĦÙħ دÙĬÙĨØ©",
+      "Ġc ú",
+      "à¸ģี ฬ",
+      "à¸ģีฬ า",
+      "Ġni ên",
+      "mis ión",
+      "׳×Ļס ×Ļ",
+      "׳×Ļס×Ļ ×ķף",
+      "Ġвоз ÑĢаÑģÑĤ",
+      "Ġ×¢×ķש ×Ķ",
+      "ĠÙħ دÙĬر",
+      "Ñı ÑģÑĮ",
+      "ØŃ Ø¬Ùħ",
+      "íĻĺ ê²½",
+      "ĠاÙĦØ£ خرÙī",
+      "u ÃŁer",
+      "ĠاÙĦعاÙĦÙħ ÙĬØ©",
+      "ĠNg á»įc",
+      "êµIJ íļĮ",
+      "ä¸Ĭ ãģ§",
+      "×Ļ×Ķ ×ķ×ĵ",
+      "×Ļ×Ķ×ķ×ĵ ×Ļ×Ŀ",
+      "Ùħس اعدة",
+      "Ġжиз нÑĮ",
+      "ĠпоÑĤ омÑĥ",
+      "ĠاÙĦÙħ ÙħÙĦ",
+      "ĠاÙĦÙħÙħÙĦ ÙĥØ©",
+      "ĠG ör",
+      "ر ÙIJ",
+      "×ŀק ×ķ×ŀ×ķת",
+      "åĩºæĿ¥ ãĤĭ",
+      "ÑĦ ÑĤ",
+      "ĠìĿ´ ìłľ",
+      "ĠÑĢ ем",
+      "ĠÑĢем онÑĤ",
+      "ת ×ķ×ļ",
+      "æĻĤ ãģ¯",
+      "ãĤīãĤĮ ãģªãģĦ",
+      "alt ı",
+      "家 ãģ®",
+      "ĠاÙĦØ¥ عÙĦاÙħ",
+      "리 ëĬĶ",
+      "ãģĭãĤī ãģ¯",
+      "ĠH ạ",
+      "ãģĤ ãģ®",
+      "×ĵ×Ļ ×ķף",
+      "رÙĬ س",
+      "Ġsoci etÃł",
+      "ĠاÙĦÙĥ بÙĬر",
+      "Ġ×ij ×ŀס",
+      "Ġ×ij×ŀס ×Ĵר",
+      "Ġ×ij×ŀס×Ĵר ת",
+      "ĠìŀĪ ìľ¼ë©°",
+      "Ġn ặng",
+      "Ùĩ Ùī",
+      "ĠB Ãł",
+      "×ŀר ×ķ",
+      "Ġj ÄĻ",
+      "ĠjÄĻ zy",
+      "ĠjÄĻzy k",
+      "Ġ׼ ×ŀ×ķ×ijף",
+      "×¢ ׾×Ķ",
+      "à¸Ĺีà¹Ī à¹Ħà¸Ķà¹ī",
+      "ãģ¾ ãģĹãĤĩãģĨ",
+      "×ŀס פר",
+      "Т Ðŀ",
+      "سÙĬاس Ø©",
+      "Ġкажд Ñĭй",
+      "ë² ł",
+      "t ım",
+      "y á»ĩn",
+      "ร ีà¹Ī",
+      "ĠдеÑĤ Ñģк",
+      "วิà¸ĺี à¸ģาร",
+      "m ówi",
+      "×ĺ×¢ ×Ŀ",
+      "×Ķצ׾ ×Ĺ×Ķ",
+      "ض ÙĬÙģ",
+      "ĠÑħоÑĤ Ñı",
+      "ãĤĵãģ§ ãģĦãĤĭ",
+      "à¸Ħา à¸Ķ",
+      "à¸Ħร à¸ļ",
+      "Ġк ÑĥÑĢÑģ",
+      "ĠbaÅŁ arı",
+      "×ijר ×ķ",
+      "ÙĬع Ø©",
+      "ĠÐĿ Ñĥ",
+      "à¸Ħวาม à¹Ģà¸Ľà¹ĩà¸Ļ",
+      "Ġ׾ ×ŀש׾",
+      "Ġì¢ĭ ìĿĢ",
+      "Ùħؤس س",
+      "Ùħؤسس ات",
+      "Ġpréc is",
+      "Ġth ảo",
+      "à¸ģà¹ĩ à¸Ħืà¸Ń",
+      "Ġש ׼׾",
+      "führ ung",
+      "ãģĦ ãģ§",
+      "à¹ģละ มี",
+      "à¸ģà¹ĩ มี",
+      "Ġש ש",
+      "м ел",
+      "Ġкни г",
+      "ĠباÙĦ ÙĨ",
+      "ĠباÙĦÙĨ سبة",
+      "Ġald ı",
+      "ÑĤ ай",
+      "Ġ×Ĺ×ĵ ש×Ļ×Ŀ",
+      "å®Ł ãģ¯",
+      "ع ÙĪا",
+      "ĠìĿĺ 미",
+      "из м",
+      "ÑĢабоÑĤ аÑĤÑĮ",
+      "Ùģ ص",
+      "Ġ×ij׳ ×ķסף",
+      "ãģ¨ãģĹãģ¦ ãĤĤ",
+      "à¹Ģà¸Ľà¹ĩà¸Ļ à¸Ĺีà¹Ī",
+      "ĠÑģлед ÑĥеÑĤ",
+      "èĢĥãģĪ ãģ¦",
+      "Ġ׼ ×Ļ×ķ×Ŀ",
+      "ÑģÑĤ Ñĭ",
+      "׼׾׼ ׾×Ļ",
+      "æµģ ãĤĮ",
+      "ãĤĴ ãģ¤ãģij",
+      "Ñĩ аÑĤ",
+      "×Ļ׼ ×ķף",
+      "×Ļר ×Ļ",
+      "ları yla",
+      "ãĤ¤ ãĥ¡",
+      "ãĤ¤ãĥ¡ ãĥ¼ãĤ¸",
+      "׳×ĸ ק",
+      "Ġci ò",
+      "Ġs ın",
+      "Ġsın ır",
+      "à¸Ļ à¸Ħร",
+      "к аÑĤ",
+      "Ġl á»Ĺi",
+      "ëŀ Į",
+      "تÙģ اص",
+      "تÙģاص ÙĬÙĦ",
+      "ëĨ ĵ",
+      "ĠÙħ ض",
+      "il miÅŁ",
+      "بار Ùĥ",
+      "ÐĿ Ðĺ",
+      "Ġth ẩm",
+      "Ġ×IJ×ķת ×ļ",
+      "ĠпÑĢин им",
+      "ĠпÑĢиним а",
+      "Ġyö nt",
+      "Ġyönt em",
+      "Ġ×ŀק ×ij׾",
+      "Ġktó rego",
+      "ê· Ģ",
+      "شر Ùģ",
+      "د اÙħ",
+      "ãģĦãĤį ãģĦãĤį",
+      "ĠAl ém",
+      "Ġgör ü",
+      "Ġgörü nt",
+      "Ġgörünt ü",
+      "د س",
+      "ÑĪ ки",
+      "г ÑĢад",
+      "Ġl ạc",
+      "Ġs ữa",
+      "ãĤīãĤĮ ãģ¾ãģĻ",
+      "o Ãłi",
+      "Ñī ен",
+      "ãģĭ ãģªãģĦ",
+      "Ġп оп",
+      "Ġпоп Ñĥ",
+      "ĠпопÑĥ лÑıÑĢ",
+      "ĠاÙĦÙħ ÙĪÙĤع",
+      "rä g",
+      "ï¼ ¡",
+      "íķ Ħ",
+      "ãĤĴè¦ĭ ãĤĭ",
+      "اÙħ ا",
+      "ĠاÙĦØŃ Ø±Ø¨",
+      "ĠÐŁ а",
+      "Ġ׾ ×IJתר",
+      "Ġt á»ijc",
+      "×ij ׾×Ķ",
+      "ر ئÙĬس",
+      "в Ñĥ",
+      "ÙĬ دÙĬ",
+      "каз ан",
+      "Ġ׊ש×ij×ķף",
+      "h ôtel",
+      "×¢ ×ķ׳×Ķ",
+      "ب ÙĨÙĬ",
+      "×ŀ ×ķ׾",
+      "Ġд нÑı",
+      "éĽ£ ãģĹãģĦ",
+      "вед ениÑı",
+      "Ġ×ķ ×ŀת",
+      "н апÑĢимеÑĢ",
+      "ÙĤ ابÙĦ",
+      "Ġrésult at",
+      "ĠÑĢазвиÑĤ иÑı",
+      "ر Ùij",
+      "ìłĦ 문",
+      "ĠاÙĦÙħ زÙĬد",
+      "ĠìľĦ íķ´ìĦľ",
+      "ëĨ į",
+      "íĻ ķ",
+      "ĠThi ết",
+      "íĮ ¨",
+      "malı dır",
+      "Ġcz ÅĤ",
+      "ĠczÅĤ owie",
+      "ĠczÅĤowie k",
+      "ĠÙĦ بÙĨ",
+      "ĠÙĦبÙĨ اÙĨ",
+      "üs ü",
+      "ãģªãĤĵ ãģł",
+      "Ġżyc ie",
+      "ĠÑħоÑĢоÑĪ о",
+      "æĸ¹ ãģ«",
+      "ëĭ¤ ë©´",
+      "иÑĩеÑģ каÑı",
+      "ער ×Ļ׼",
+      "ער×Ļ׼ ת",
+      "ãģ¾ãģĽãĤĵ ãģ§ãģĹãģŁ",
+      "ĠÑģоб ой",
+      "Ġg á»Ĺ",
+      "Ġдел аÑĤÑĮ",
+      "da Äĩ",
+      "аÑĢ а",
+      "róż ni",
+      "à¹Ģล ีà¹ī",
+      "à¹Ģลีà¹ī ย",
+      "à¹Ģลีà¹īย à¸ĩ",
+      "à¸Ŀ าà¸ģ",
+      "Ġت ÙĤ",
+      "ĠتÙĤ دÙĬ",
+      "ĠتÙĤدÙĬ Ùħ",
+      "หà¸Ļ ุà¹Īม",
+      "Ġmü cade",
+      "Ġmücade le",
+      "ì§Ģ 를",
+      "ãĤ¤ ãĤ¹",
+      "ĠØ£ ساس",
+      "jÄħce go",
+      "ĠÅŁ eh",
+      "н ÑĤеÑĢ",
+      "ÑĨи Ñİ",
+      "ï» »",
+      "ÑİÑī его",
+      "à¹Ĥà¸Ľà¸£ à¹ģ",
+      "à¹Ĥà¸Ľà¸£à¹ģ à¸ģรม",
+      "Ġmie Äĩ",
+      "ØŃÙĥÙĪÙħ Ø©",
+      "ãģ§ãģĹãģŁ ãģĮ",
+      "×Ļס ×Ķ",
+      "ãĤĤãģ® ãĤĴ",
+      "Ġ×ŀ ×IJת",
+      "สุà¸Ķ à¸Ĺà¹īาย",
+      "Ġc Å©",
+      "ÙĨ سب",
+      "ĠпÑĢ оÑĩ",
+      "Ġд ней",
+      "ĠÑįÑĤи Ñħ",
+      "׾ ×ŀת",
+      "нÑı Ñı",
+      "Ñį к",
+      "Ġì§Ģ ëĤľ",
+      "มหา วิà¸Ĺยา",
+      "มหาวิà¸Ĺยา ล",
+      "มหาวิà¸Ĺยาล ัย",
+      "d ão",
+      "ĠMá y",
+      "ĠêµŃ ê°Ģ",
+      "à¸ļุ รี",
+      "×Ĵ ×Ļ׾",
+      "ĠÑĤÑĭ ÑģÑı",
+      "ĠÑĤÑĭÑģÑı Ñĩ",
+      "Ùģ Ùĥ",
+      "ĠÐĺ Ñģ",
+      "è¡Į ãĤıãĤĮ",
+      "פר ×ĵ",
+      "ãģ¤ ãģį",
+      "à¸Ħร à¸Ńà¸ļ",
+      "à¸Ħรà¸Ńà¸ļ à¸Ħรัว",
+      "à¸Ĥึà¹īà¸Ļ มา",
+      "ä»ĬæĹ¥ ãģ¯",
+      "ĠìĤ¬ëŀĮ ìĿ´",
+      "עצ ×ŀ×Ķ",
+      "п оÑĢ",
+      "ĠK ỳ",
+      "Ġ Æ¡n",
+      "Ġth Äĥm",
+      "Ùģ اÙĤ",
+      "ãģļ ãģ«",
+      "Ġ׾ קר",
+      "Ġ׾קר ×ķ×IJ",
+      "اÙģ ÙĬØ©",
+      "Ùħ Ùİا",
+      "г аÑĢ",
+      "ص ÙĦا",
+      "صÙĦا Ø©",
+      "Ġ×ŀ ×ĸ×Ķ",
+      "lı ģını",
+      "Ġ×IJ ×Ļ׳×Ķ",
+      "к ÑĢо",
+      "Ġng Æ°Æ¡i",
+      "Ġв ним",
+      "Ġвним ание",
+      "jÄħ cy",
+      "ÙĢÙĢÙĢÙĢ ÙĢ",
+      "Ñģ Ñħод",
+      "ãģªãĤĵ ãģĭ",
+      "×ŀ ×Ļ׾",
+      "Ġ×Ķ×IJ ×Ĺ",
+      "ãĤı ãģªãģĦ",
+      "ع سÙĥر",
+      "ĠìĦ¸ ê³Ħ",
+      "ĠÑĩ его",
+      "ĠÑģÑĢед ÑģÑĤва",
+      "ĠÐł аÑģ",
+      "ãģª ãģģ",
+      "ÙĨ Ùģس",
+      "ר×Ļ ×ķף",
+      "Ñģ Ñĥд",
+      "ĠìĿ¸ ê°Ħ",
+      "ĠاÙĦÙħ ÙĤبÙĦ",
+      "ÙĨ عÙħ",
+      "تÙĪ Ùģر",
+      "ש ×ij×¢",
+      "ı lm",
+      "ılm Ä±ÅŁ",
+      "Ġ×ľ×ª ת",
+      "تص Ùģ",
+      "×Ķפ ×ķ×ļ",
+      "à¹ĥà¸Ļ à¸Ľà¸µ",
+      "ìĿ´ ê³ł",
+      "Ùģ ÙĪز",
+      "à¸ľà¸¥ à¸ĩาà¸Ļ",
+      "ĠGi áo",
+      "à¸ļà¸Ńà¸ģ วà¹Īา",
+      "Ġd Ä±ÅŁ",
+      "ĠdÄ±ÅŁ ında",
+      "ì£ ½",
+      "Ġdzie ÅĦ",
+      "к ÑĨии",
+      "и ÑĨе",
+      "ãģ® ä¸Ģ",
+      "ع ش",
+      "пÑĢ еÑģÑģ",
+      "หà¸Ļ à¹Īà¸Ńย",
+      "ลัà¸ģษ à¸ĵะ",
+      "Ġpossibilit Ãł",
+      "à¹Ħà¸Ķà¹īรัà¸ļ à¸ģาร",
+      "หย ุà¸Ķ",
+      "Ġphi ên",
+      "çĶŁ ãģ¾ãĤĮ",
+      "Ø· ÙĪÙĦ",
+      "ÑĦ ин",
+      "f ür",
+      "ØŃ ÙĬاة",
+      "íĸ ĪìĬµëĭĪëĭ¤",
+      "׼ ׳×ķת",
+      "à¸Ľà¸£à¸° ส",
+      "à¸Ľà¸£à¸°à¸ª à¸ļ",
+      "à¸Ľà¸£à¸°à¸ªà¸ļ à¸ģารà¸ĵà¹Į",
+      "ëIJĺ ìĹĪ",
+      "Ġkaż dy",
+      "Ġl uyá»ĩn",
+      "ĠоÑĢганиз аÑĨии",
+      "å°ij ãģªãģı",
+      "ÑģÑĤÑĢо ен",
+      "Ġtécn ico",
+      "ק ×Ķ׾",
+      "Ġ×ķ×IJ ×Ĺ",
+      "ĠعÙĦÙĬ Ùĥ",
+      "Ñī ение",
+      "Ġ×Ķ ×Ļ׾×ĵ×Ļ×Ŀ",
+      "ÙĪس ائÙĦ",
+      "Ġ×ķ ×Ķת",
+      "تÙħ ÙĬز",
+      "ĠÑģ казал",
+      "Ġпол и",
+      "Ġ×Ķ×ŀ ס",
+      "ÙĦÙij Ùİ",
+      "Ùħؤس سة",
+      "Ġ×ŀ ×Ļ×ĵ",
+      "ãģ£ ãģ¡",
+      "ĠëĦĪ 무",
+      "à¸ŀ ี",
+      "Ġt ặng",
+      "Ġt ấn",
+      "ר ש×Ŀ",
+      "Ġméd ica",
+      "Ġ×¢ ×ķ×ŀ",
+      "Ġ×¢×ķ×ŀ ×ĵ",
+      "ÑĦ оÑĢ",
+      "Ùħر Ø©",
+      "Ġvat anda",
+      "Ġvatanda ÅŁ",
+      "Ġдел о",
+      "à¸Ļ ม",
+      "ãģ¨ åIJĮãģĺ",
+      "Ùģ Ùī",
+      "Ñģ оÑĢ",
+      "Ġ×Ķס ר×ĺ",
+      "Ġép oca",
+      "ìłķ ì±ħ",
+      "ĠÑģвÑıз ан",
+      "ض رب",
+      "ĠÙĦ ÙĨا",
+      "Ġuży wa",
+      "ĠاÙĦج ÙĬØ´",
+      "Ñİ ÑĢ",
+      "×ijס ×ķ×£",
+      "Ġм Ñĥ",
+      "ĠмÑĥ зÑĭк",
+      "bilit é",
+      "Ġma ç",
+      "س Ùİ",
+      "ت ÙĦÙĥ",
+      "ãģ ¬",
+      "ÙĬ ÙĦا",
+      "ÑĪ ла",
+      "ÙĢÙĢ ÙĢ",
+      "Ġод ной",
+      "зв ан",
+      "ĠÑģ ÑĢаз",
+      "ĠÑģÑĢаз Ñĥ",
+      "ÙĨ ظÙħ",
+      "را Ùĩ",
+      "ĠÙĦÙĩ ذا",
+      "׼ ×ķר",
+      "Ġ×Ķש ×ij×ķ×¢",
+      "Ġ×Ķש ת",
+      "ĠQu ảng",
+      "ãĥ« ãĥ¼",
+      "ãģĪ ãģªãģĦ",
+      "×ĺ ×IJ",
+      "Ġmi á»ģn",
+      "ĠPh áºŃt",
+      "ĠاÙĦس ÙĪÙĤ",
+      "Ä Ĥ",
+      "ĠاÙĦج Ùħع",
+      "ĠاÙĦجÙħع Ø©",
+      "ÑİÑī ей",
+      "a ÅĤem",
+      "عت ÙĤد",
+      "Ø£ ÙĦÙħ",
+      "Ñģ ке",
+      "ĠìĿ´ íķ´",
+      "ÙĨس Ø®",
+      "è¨Ģ ãģĦ",
+      "д обав",
+      "سب ÙĤ",
+      "×¢×ķר ר",
+      "ÑĤи п",
+      "ãģĿãģĵ ãģ§",
+      "vis ión",
+      "عÙĪد Ø©",
+      "ë¨ ¹",
+      "×ŀ ×ĸר×Ĺ",
+      "ĠØ¥ ØŃ",
+      "Ġ׾×ij ×Ļף",
+      "Ġ׾צ ×IJת",
+      "Ġyard ı",
+      "Ġyardı mc",
+      "Ġyardımc ı",
+      "Ä° Z",
+      "ק פ×Ķ",
+      "tr é",
+      "liÄŁ ini",
+      "клÑİÑĩ а",
+      "Ġüret im",
+      "Ġa yrı",
+      "ĠkiÅŁ iler",
+      "à¸Ħ à¹īà¸Ļ",
+      "à¸Ħà¹īà¸Ļ หา",
+      "ĠS á»±",
+      "Ġ׼ ס",
+      "Ġ×Ľ×¡ ×£",
+      "ĠÑĤак иÑħ",
+      "ĠXu ân",
+      "Ġл ег",
+      "Ġлег ко",
+      "Ø«ÙĤ اÙģØ©",
+      "ÐĿ Ðŀ",
+      "ãĤ¹ãĤ¿ ãĥĥ",
+      "ãĤ¹ãĤ¿ãĥĥ ãĥķ",
+      "åIJĪ ãģĦ",
+      "Ġ×Ķש ×Ļ×ŀ×ķש",
+      "man ız",
+      "ĠÐĴ аÑģ",
+      "g ün",
+      "ìľĦìĽIJ íļĮ",
+      "Ġwsp óln",
+      "ĠÑģв ое",
+      "í ĥģ",
+      "à¹Ģà¸Ļ ีย",
+      "ÙĪب Ø©",
+      "в Ñıз",
+      "ı dır",
+      "ëIJĺ ìĹĪëĭ¤",
+      "ĠdeÄŁi ÅŁtir",
+      "ãĤĭ ãģĵãģ¨ãģĮ",
+      "Ġ×Ĺ×ĵ ש×Ķ",
+      "ãĤīãĤĮ ãģ¦ãģĦãĤĭ",
+      "×Ĺ×Ļ ×Ļ×ij",
+      "ĠÐļ аÑĢ",
+      "׳×Ļת ×ķ×Ĺ",
+      "Ġק×ĺ ף",
+      "ר ×ĸ",
+      "ÙĪ غ",
+      "èªŃ ãģ¿",
+      "Ġت ÙĤÙĪÙħ",
+      "ĠÙĥ اÙĦ",
+      "à¸Ŀ ึà¸ģ",
+      "Ġë°ľ ìĥĿ",
+      "ológ ico",
+      "ر اع",
+      "à¹ģà¸ģà¹ī à¹Ħà¸Ĥ",
+      "ĠÑĢабоÑĤ Ñĥ",
+      "ÙĨÙij Ùİ",
+      "à¸Ńยูà¹Ī à¸Ĺีà¹Ī",
+      "ĠاÙĦØ« اÙĨÙĬØ©",
+      "ĠNh ân",
+      "Ñħ ваÑĤ",
+      "ö ne",
+      "Ġع دة",
+      "à¹ģ สà¸ĩ",
+      "ÑĤ оп",
+      "пÑĥÑģ ка",
+      "شر اء",
+      "ĠÐļ ом",
+      "Ġפע ×ķ׾×Ķ",
+      "ìĤ¬ ìĿ´",
+      "ìĤ¬ìĿ´ íĬ¸",
+      "è¡Į ãģ£ãģ¦",
+      "Ġ×Ķ ×Ķת",
+      "ĠÑģÑĤ оÑĢо",
+      "ĠÑģÑĤоÑĢо нÑĭ",
+      "در س",
+      "à¸ĭ ู",
+      "à¸ķà¹Ī ำ",
+      "ĠØ£ بÙĬ",
+      "под об",
+      "ãģ« ãģ¦",
+      "ار تÙģاع",
+      "ĠÙħ ؤ",
+      "ик ов",
+      "ge führt",
+      "มืà¸Ń à¸ĸืà¸Ń",
+      "ĠÙĦ ÙĤد",
+      "ĠØ£ÙĨ Ùij",
+      "سÙĬ طر",
+      "ãģ¾ãģļ ãģ¯",
+      "ס ×ĵ",
+      "Ñģк олÑĮко",
+      "ãģ¿ãģŁãģĦ ãģª",
+      "×ĵר ×Ĵ",
+      "×¢ ×Ļ×ĵ",
+      "à¹ĥหà¹ī à¸ļริà¸ģาร",
+      "ĠÐĶ и",
+      "×ij×¢ ×Ļ×ķת",
+      "Ġ×Ķ×Ĺ ×ķ",
+      "пиÑģ ÑĮ",
+      "ĠاÙĦØ® ÙĦ",
+      "б ав",
+      "ĠÄ° lk",
+      "ĠاÙĦØ® Ùħ",
+      "ĠاÙĦØ®Ùħ ÙĬس",
+      "ĠÙĬ ÙĤÙĪÙħ",
+      "æĻĤ ãģ®",
+      "ĠsÅĤ ow",
+      "ĠØ£ ÙĩÙħ",
+      "Ø®ÙĦ ÙĤ",
+      "ĠØ£ صبØŃ",
+      "Ġchứ a",
+      "Ġth ác",
+      "Ùģ اÙĦ",
+      "Ġch á»Ŀ",
+      "ĠاÙĦØ® ار",
+      "ĠاÙĦخار ج",
+      "ĠاÙĦخارج ÙĬØ©",
+      "ط ائر",
+      "Ġt Ãł",
+      "ĠtÃł u",
+      "à¸ģล à¹īà¸Ńà¸ĩ",
+      "ĠاÙĦÙħر Ø£",
+      "ĠاÙĦÙħرأ Ø©",
+      "åħ¨ ãģı",
+      "ĠÃĸ n",
+      "çļĦ ãģ«ãģ¯",
+      "Ġpiè ce",
+      "×Ĵ ×Ļ×ij",
+      "ĠاÙĦ ÙĪاÙĤع",
+      "ä»Ĭ ãģ®",
+      "ĠاÙĦÙħ ÙĤ",
+      "cz nÄħ",
+      "Ùģع اÙĦ",
+      "ен ного",
+      "ĠÑĦак ÑĤ",
+      "ìĭł ì²Ń",
+      "ĠÐŀ ни",
+      "ĠاÙĦبÙĦ اد",
+      "ов иÑĩ",
+      "ëı Į",
+      "ÑĦ ÑĥнкÑĨи",
+      "Ġìĸ´ ëĬIJ",
+      "ãĥķãĤ© ãĥ¼",
+      "d ÃŃ",
+      "ил оÑģÑĮ",
+      "Ùħ Ùī",
+      "ĠاÙĦØ£ÙħرÙĬ Ùĥ",
+      "ĠاÙĦØ£ÙħرÙĬÙĥ ÙĬØ©",
+      "×ĺ ×Ļפ×ķ׾",
+      "íĶĦ ë¡ľê·¸",
+      "íĶĦë¡ľê·¸ ëŀ¨",
+      "Ġש ×ķ׳×ķת",
+      "Ø´ ÙħÙĦ",
+      "ĠпаÑĢ а",
+      "Ġ×Ķ×Ĺ ×ķק",
+      "ÙĪز ارة",
+      "ãģ¨ ãģĻãĤĭ",
+      "Ġqu ảng",
+      "ĠaÄŁ ır",
+      "ĠاÙĦÙĦ ج",
+      "ĠاÙĦÙĦج ÙĨØ©",
+      "ê¸ ´",
+      "ĠT ân",
+      "ج ÙħÙĦ",
+      "д ол",
+      "à¹ģà¸ŀ à¸Ĺย",
+      "à¹ģà¸ŀà¸Ĺย à¹Į",
+      "Ġר×IJ ש×Ļ",
+      "Ñī ей",
+      "Ġçev re",
+      "Ġкомп лекÑģ",
+      "Ġ×ij ×ŀש×ļ",
+      "Ġalt ın",
+      "ĠØ£ عÙħاÙĦ",
+      "ĠÑģво его",
+      "ãĤĪ ãģĦ",
+      "×Ĺ׾ ×Ļ×ĺ",
+      "×ŀ׳ ×¢",
+      "Ġר ×ij×Ķ",
+      "ĠØ£ÙĬضا Ùĭ",
+      "×ĸ ׾",
+      "ĠاÙĦسÙĬ اسÙĬ",
+      "æĢĿ ãģĨ",
+      "קר ק",
+      "קרק ע",
+      "ĠاÙĦÙģ رÙĬÙĤ",
+      "б иÑĤ",
+      "ק ׳×Ķ",
+      "ĠØ¥ ÙĨÙĩ",
+      "ĠÐĴ ам",
+      "Ðł Ðŀ",
+      "ãĥĪ ãĥª",
+      "å¿ħè¦ģ ãģª",
+      "Ġch âu",
+      "ç¶ļ ãģij",
+      "Ġçöz üm",
+      "gÅĤ ow",
+      "ع ÙĤÙĦ",
+      "売 ãĤĭ",
+      "i ết",
+      "à¸Ĭิ à¹īà¸Ļ",
+      "ĠØŃÙĤ ÙĪÙĤ",
+      "Ø·ÙĦ ع",
+      "ĠÄij en",
+      "ĠÙĥ اÙģØ©",
+      "ãģ® ãģĶ",
+      "Ġë ¬",
+      "Ġë¬ ¼",
+      "Ġ물 ë¡ł",
+      "Ġرس ÙĪÙĦ",
+      "з ам",
+      "зам ен",
+      "Ġkullan ıcı",
+      "×¢ ×ķ׾",
+      "èī² ãĢħ",
+      "ÑĪи ÑĢ",
+      "Ġ׊ש",
+      "Ġwy gl",
+      "Ġwygl Äħda",
+      "ש ×Ļ×ŀ×ķש",
+      "å¿ĺ ãĤĮ",
+      "×¢ ×Ļצ×ķ×ij",
+      "ĠاÙĦس ÙĪرÙĬ",
+      "å°ij ãģªãģĦ",
+      "Ġпо иÑģк",
+      "สำ à¸Ļัà¸ģà¸ĩาà¸Ļ",
+      "Ġ×ŀצ ×ĵ",
+      "Ġmü ÅŁ",
+      "ĠmÃ¼ÅŁ ter",
+      "ĠmÃ¼ÅŁter i",
+      "ĠÙħÙĨ ÙĩÙħ",
+      "à¸ķำ à¹ģ",
+      "à¸ķำà¹ģ หà¸Ļ",
+      "à¸ķำà¹ģหà¸Ļ à¹Īà¸ĩ",
+      "ÅĽ mie",
+      "Ġש ×ł×ª",
+      "Ġ×Ķ פ×Ļ",
+      "פר ש",
+      "×¢×ijר ×Ļת",
+      "สà¸Ļ ัà¸ļ",
+      "สà¸Ļัà¸ļ สà¸Ļุ",
+      "สà¸Ļัà¸ļสà¸Ļุ à¸Ļ",
+      "è¨Ģ ãģ£ãģ¦",
+      "à¸ģาร à¸Īัà¸Ķ",
+      "ĠMo że",
+      "из аÑĨии",
+      "ứ t",
+      "ĠÙĪب عد",
+      "ĠdeÄŁ ild",
+      "ĠdeÄŁild ir",
+      "Ġת ×ŀ",
+      "Ġ×ŀ×ŀ ׳×ķ",
+      "話 ãĤĴ",
+      "ĠÑĨ ена",
+      "Ġth úc",
+      "×Ļ×ŀ ×ķף",
+      "ĠB áo",
+      "ãĤĴ åıĸãĤĬ",
+      "å®ī ãģĦ",
+      "Ġ×¢×ķש ×Ļ×Ŀ",
+      "èĩªåĪĨ ãģĮ",
+      "l ée",
+      "ãĤĭ ãģ®ãģ§",
+      "иÑĢÑĥ еÑĤ",
+      "ãģ¦ ãĤĭ",
+      "ست ر",
+      "ĠاÙĦØŃ ÙĬ",
+      "×Ļ׾ ×ķת",
+      "Ġ×Ĺ ×ij",
+      "ÙĤر Ø£",
+      "تÙħ ÙĥÙĨ",
+      "س ائÙĦ",
+      "prü f",
+      "ãģĭ ãģijãģ¦",
+      "ĠÑģоб ÑģÑĤвенно",
+      "ĠìľĦ íķĺìŬ",
+      "׾ ×Ļ×ĺ",
+      "ãģĮ å¤ļãģı",
+      "ÙĬت Ùĩا",
+      "ç«ĭ ãģ¦",
+      "ม à¸Ńà¸ļ",
+      "ìĭľ ìŀ¥",
+      "оÑĢ а",
+      "Ġs avaÅŁ",
+      "×ĺ×Ļ×ij ×Ļ",
+      "×ij ׳×ķ",
+      "Ùħا ذا",
+      "기 ê°Ħ",
+      "ãģªãģ© ãģ§",
+      "Ġ×ŀ ת×Ĺ×Ļ׾",
+      "Ġnhi á»ħ",
+      "Ġnhiá»ħ m",
+      "ка ÑĢ",
+      "каÑĢ ÑĤ",
+      "Ġ׾×Ķ שת×ŀש",
+      "׳ ×Ļ×Ĺ",
+      "اد ÙĬØ©",
+      "ราย à¸ĩาà¸Ļ",
+      "Ġprzy kÅĤad",
+      "Ñī ий",
+      "ØŃض ÙĪر",
+      "Ġh ôn",
+      "Ã Ŀ",
+      "ת ×ķצ×IJ×ķת",
+      "راب ط",
+      "Ġb ếp",
+      "ĠполÑĥÑĩ и",
+      "åĩºä¼ļãģĦ ç³»",
+      "à¸Ľà¸¥ à¹Īà¸Ńย",
+      "ĠاÙĦØ´ باب",
+      "اÙĩ ÙĦ",
+      "ä»Ĭ ãģ¾ãģ§",
+      "رج ع",
+      "ãĤ¶ ãĥ¼",
+      "ÙĤ Ùģ",
+      "ĠGro ÃŁ",
+      "ĠíļĮ ìĽIJ",
+      "اج ر",
+      "Ġ×ij×ŀ קר×Ķ",
+      "Ġseg urança",
+      "fü hl",
+      "ãģ¦ ãģĦãģı",
+      "หม à¸Ń",
+      "ĠкоÑĤоÑĢ ом",
+      "ĠN Äĥm",
+      "ĠdÅĤ ugo",
+      "ÙħÙĨ ØŃ",
+      "ש×ķ ×ķ×Ļ",
+      "ĠØ£ÙĬ اÙħ",
+      "ส à¸łà¸²à¸ŀ",
+      "r zÄħ",
+      "شر Ùĥات",
+      "ãĤĴ èĢĥãģĪ",
+      "д аÑĢ",
+      "à¸Ľà¸£à¸° à¸Ĭุม",
+      "Ġ×ķ×IJ ×ĸ",
+      "i á»ĩn",
+      "Ġt Æ°Æ¡i",
+      "ש ×Ļ×Ĺ",
+      "à¸Ń à¹Īà¸Ńà¸Ļ",
+      "æĽ¸ ãģĦãģ¦",
+      "Ġng ữ",
+      "×ij×Ļ×ĺ ×Ĺ",
+      "×ij×Ļ×ĺ×Ĺ ×ķף",
+      "Ġs ẵ",
+      "Ġsẵ n",
+      "ì§Ģ ëıĦ",
+      "ĠпÑĢ еп",
+      "ĠпÑĢеп аÑĢаÑĤ",
+      "Ġна ÑĥÑĩ",
+      "ĠÃľ nivers",
+      "ĠÃľnivers ites",
+      "ĠÃľniversites i",
+      "Ġ×Ĵ×ĵ ×ķ׾×Ķ",
+      "Ġ×Ķ ×ł×ª",
+      "Ġ×Ķ×ł×ª ×ij×¢",
+      "ãģ§ãģĤ ãģ£ãģŁ",
+      "Ġmies iÄħ",
+      "ĠmiesiÄħ c",
+      "г ÑĢам",
+      "гÑĢам м",
+      "Ġبش Ø£ÙĨ",
+      "ĠÑħ ÑĢ",
+      "ק ×Ļ×ĵ",
+      "ק×Ļ×ĵ ×ķ×Ŀ",
+      "Ø´ Ùĥر",
+      "Ġ á»ķ",
+      "Ġá»ķ n",
+      "ãģĮãģĤ ãģ£ãģ¦",
+      "ãģķãĤĮ ãģ¾ãģĻ",
+      "Ġ×Ĺ ×ķ×ĵ",
+      "Ġ×Ĺ×ķ×ĵ ש×Ļ×Ŀ",
+      "ÙħÙĪا جÙĩ",
+      "ÙħÙĪاجÙĩ Ø©",
+      "أش خاص",
+      "ب غ",
+      "à¹Ģรียà¸Ļ รูà¹ī",
+      "ãģĹãģ¦ ãģĦãģı",
+      "Ġs ạn",
+      "å¿ħ ãģļ",
+      "׳ ×Ļ×Ĵ",
+      "׳×Ļ×Ĵ ×ķ×ĵ",
+      "باÙĦ غ",
+      "׊ש×ŀ",
+      "×Ĺש×ŀ ׾",
+      "Ġnap raw",
+      "Ġnapraw dÄĻ",
+      "Ø´Ùĩ اد",
+      "×IJ ×ķ×Ķ",
+      "×IJ×ķ×Ķ ×ij",
+      "и ÑĨÑĭ",
+      "Ġ×Ķ ר׼×ij",
+      "ëŀ ij",
+      "Ġת ×¢",
+      "Ġ×Ķ ×Ļש",
+      "Ġ×Ķ×Ļש ר×IJ",
+      "Ġ×Ķ×Ļשר×IJ ׾×Ļ",
+      "Ø£ ÙħÙĨ",
+      "ÑİÑī аÑı",
+      "sk ór",
+      "LER Ä°",
+      "Ġ×Ķ×IJ×Ĺר ×ķף",
+      "×¢ ׳ק",
+      "ĠÙĪ ÙĥÙĦ",
+      "ãģĵãģĵ ãģ§",
+      "Ġqu án",
+      "liÄŁ in",
+      "à¸ģà¸İ หมาย",
+      "Ø· Ùħ",
+      "Ø£ جÙĩ",
+      "أجÙĩ زة",
+      "ĠEr doÄŁan",
+      "ãģ§ ãģĬ",
+      "Ġв ÑĢа",
+      "ĠвÑĢа Ñĩ",
+      "ĠPh ó",
+      "à¸Ĭั à¹Īว",
+      "à¸Ĭัà¹Īว à¹Ĥม",
+      "à¸Ĭัà¹Īวà¹Ĥม à¸ĩ",
+      "Ġph úc",
+      "×Ļפ ×ķת",
+      "×¢×Ļ ×ķף",
+      "Ġduż o",
+      "ãĥģ ãĥ¼ãĥł",
+      "ĠÙĬ Ùİ",
+      "Ġзад аÑĩ",
+      "Ġ×Ĵ×ij×ķ×Ķ ×Ķ",
+      "Ġ׼ ׼׾",
+      "лож ен",
+      "ét at",
+      "Ġng Äĥn",
+      "èµ· ãģį",
+      "ĠTi ến",
+      "ص عب",
+      "Ġexperi ência",
+      "Ø® Ùħ",
+      "à¸ģาร à¸Ĺำà¸ĩาà¸Ļ",
+      "س ÙĬد",
+      "ĠD á»±",
+      "ĠкоÑĤоÑĢ ого",
+      "lad ıģı",
+      "Ġkh á»ķ",
+      "Ġê³Ħ ìĨį",
+      "Ñī ик",
+      "สà¹Īวà¸Ļ à¸ķัว",
+      "з оÑĢ",
+      "ÙĨ Ùı",
+      "Ġ à¸Ķัà¸ĩ",
+      "Ġà¸Ķัà¸ĩ à¸Ļัà¹īà¸Ļ",
+      "Ġc ấu",
+      "ĠÄij á»ijc",
+      "о ÑĦ",
+      "ĠاÙĦØ£ عÙħاÙĦ",
+      "ãģªãģı ãģ¦ãĤĤ",
+      "×ķ׼ ×Ļ×Ŀ",
+      "à¹ģ à¸Ľ",
+      "ĠB ên",
+      "ãĥ¯ ãĥ³",
+      "Ġgi ám",
+      "ĠÅŀ u",
+      "Ġd áng",
+      "ع ÙĦÙĬ",
+      "à¹Ģà¸ģ ษ",
+      "à¹Ģà¸ģษ à¸ķร",
+      "ÙĪج ب",
+      "н нÑĭе",
+      "ÙĤ ضاء",
+      "à¸Ħว à¸ļ",
+      "à¸Ħวà¸ļ à¸Ħุ",
+      "à¸Ħวà¸ļà¸Ħุ ม",
+      "ãģ¤ ãģ¤",
+      "ĠVi á»ĩc",
+      "×ŀ×ij ×ĺ",
+      "ש×Ļת ×ķ×£",
+      "Ġв едÑĮ",
+      "k aza",
+      "kaza ÅĤ",
+      "à¸ķำ รวà¸Ī",
+      "ãĤ¿ ãĥ«",
+      "Ġпов Ñĭ",
+      "ĠповÑĭ ÑĪен",
+      "ĠS ợ",
+      "ĠìĦ¤ ëªħ",
+      "ĠÃĩ ünkü",
+      "ìĥĿ íĻľ",
+      "Ö ¾",
+      "ãĤĮ ãģ¦ãģĦãĤĭ",
+      "Ġ×ij ר×IJש",
+      "ר ×ķ×Ĵ",
+      "Ġо ÑĦи",
+      "ĠоÑĦи ÑĨиалÑĮн",
+      "ĠÑĥ ÑģÑĤанов",
+      "ĠÑĥÑģÑĤанов лен",
+      "ĠاÙĦÙħ صر",
+      "ĠاÙĦÙħصر ÙĬØ©",
+      "ĠÐŁÐ¾ ÑįÑĤомÑĥ",
+      "ÙĨ صÙģ",
+      "ĠÙĪاÙĦ ÙĨ",
+      "Ġh Ãłi",
+      "à¸Ħ ิ",
+      "ĠApr ès",
+      "ì³ IJ",
+      "à¹Ģà¸ĭ ีย",
+      "×ĵ ×ŀ×Ķ",
+      "activ ité",
+      "à¸Ħิà¸Ķ วà¹Īา",
+      "ÑĤ ÑĢен",
+      "à¹Ģ ฮ",
+      "ãĥı ãĤ¤",
+      "ãģĮ å¢ĹãģĪ",
+      "ен наÑı",
+      "Ġìĺ¤ ëĬĺ",
+      "ãĥ¢ ãĥ³",
+      "Ġкон еÑĩно",
+      "ĠÙħÙĤ ابÙĦ",
+      "cl é",
+      "Ġh ü",
+      "Ġth ẳng",
+      "ìłģ ìĿ´",
+      "ĠÐIJ лекÑģ",
+      "ĠÐIJлекÑģ ан",
+      "ĠÐIJлекÑģан дÑĢ",
+      "ãĥŀãĥ³ ãĤ·ãĥ§ãĥ³",
+      "ãģ²ãģ¨ ãģ¤",
+      "ãģª ãģĬ",
+      "à¹Ģà¸Īà¹īา à¸Ĥà¸Ńà¸ĩ",
+      "ëĵľ 리",
+      "ش اء",
+      "ĠsaÄŁ lık",
+      "ĠÅŁ imdi",
+      "×Ļ×IJ ׾",
+      "تأ Ø«ÙĬر",
+      "أ سب",
+      "أسب اب",
+      "ĠвÑĭполн ен",
+      "л ок",
+      "ש ×Ļ×ij×Ķ",
+      "Ġl ắm",
+      "ĠTr Æ°á»Ľc",
+      "Ġ×Ķ×¢ ׾",
+      "리 를",
+      "ĠÑĢ еж",
+      "ĠÑĢеж им",
+      "int é",
+      "inté gr",
+      "×Ĵ ׳×Ļ",
+      "ĠاÙĦØ´ عر",
+      "Ġmil hões",
+      "Ġpeque ño",
+      "ãĤ³ ãĥ¼ãĤ¹",
+      "×ķ׼ ×Ĺ",
+      "à¹Ģà¸Ĭ à¹īา",
+      "شر ÙĤ",
+      "Ġh Æ°Æ¡ng",
+      "รัà¸IJ à¸ļาล",
+      "à¸ģล าย",
+      "à¸ģลาย à¹Ģà¸Ľà¹ĩà¸Ļ",
+      "Ġпод Ñħод",
+      "תש ×ķ×ij×Ķ",
+      "ãģıãģª ãģ£ãģ¦",
+      "ĠاÙĦØ£Ùħ Ùħ",
+      "ĠH á»įc",
+      "ĠwspóÅĤ pr",
+      "ĠwspóÅĤpr ac",
+      "Ñĩ Ñĥв",
+      "ÑĩÑĥв ÑģÑĤв",
+      "ÃŃst ico",
+      "à¹Ģà¸ģ าะ",
+      "ìĽ Ģ",
+      "Ġназ ад",
+      "ãĤĭ ãĤĪãģĨãģ«",
+      "ĠС Ш",
+      "ĠСШ ÐIJ",
+      "м он",
+      "ĠAs ÃŃ",
+      "×ķר ×Ĵ",
+      "полн ен",
+      "×ŀס ׾",
+      "×ŀ×¡×ľ ×ķ׾",
+      "à¹Ģลืà¸Ń à¸Ķ",
+      "à¹Ģริà¹Īม à¸ķà¹īà¸Ļ",
+      "ĠاÙĦØ¥ Ùħ",
+      "ĠاÙĦØ¥Ùħ ارات",
+      "צ×Ķ ר",
+      "ãĥ¡ãĥª ãĥĥãĥĪ",
+      "ĠпоÑĤ ом",
+      "в из",
+      "ĠÙģ ترة",
+      "å¾Į ãģ®",
+      "ÐĿ ÐIJ",
+      "×ŀס ר",
+      "ÙĬر ÙĬ",
+      "pr é",
+      "Ġte ÅŁek",
+      "ĠteÅŁek kür",
+      "Ġöd eme",
+      "د اÙĨ",
+      "ãģ¾ ãģĹãģ¦",
+      "缮 ãģ«",
+      "ĠÑĤ еÑĩение",
+      "l ard",
+      "lard ır",
+      "à¹Ģรา à¸Īะ",
+      "ס פ×Ļ",
+      "ĠÙĪÙĥ Ø°ÙĦÙĥ",
+      "Ġh át",
+      "Ġt á»Ļc",
+      "à¸Ħุ ย",
+      "Ġb ức",
+      "ØŃ ÙĬÙĨ",
+      "èģŀ ãģĦãģ¦",
+      "Ùħؤ شر",
+      "ĠNh Æ°",
+      "Ġмен ее",
+      "ละ à¸Ħร",
+      "Ñģ ин",
+      "ĠÑĢ ек",
+      "ĠÑĢек л",
+      "ĠÑĢекл ам",
+      "ĠÙģ ÙĩÙĪ",
+      "Ġ׾ ×ĸ",
+      "×Ļ׳ ×ķת",
+      "ĠÅŁ art",
+      "ÑģÑĤав ка",
+      "Ġíı¬ íķ¨",
+      "ãģ«è¡Į ãģı",
+      "ï¼ Ŀ",
+      "ĠпозволÑı еÑĤ",
+      "Ġת×ķ׼ ׾×ķ",
+      "ов ал",
+      "صÙĦ Ø©",
+      "Ġ׾ש ׳×ķת",
+      "ĠÐĺ гÑĢ",
+      "ÙħÙĨتج ات",
+      "Ġsat Ä±ÅŁ",
+      "Ñģ ко",
+      "ĠاÙĦØ«ÙĦاث اء",
+      "Ġ×Ķ×ĵ×ijר ×Ļ×Ŀ",
+      "ãģĹãģ¾ ãģĹãĤĩãģĨ",
+      "بÙĤ Ùī",
+      "åĬĽ ãĤĴ",
+      "ĠÃĩ ok",
+      "ãĥģ ãĥ¥",
+      "à¹Ģà¸Ĭ ืà¹īà¸Ń",
+      "ยุ à¸Ħ",
+      "ศา ล",
+      "Ġק×ķ×ĵ ×Ŀ",
+      "×ĸר ×Ļ×Ŀ",
+      "ãģ® åł´åIJĪ",
+      "ĠìķĬ ìķĺ",
+      "ãģĤãĤĬãģ¾ãģĻ ãģĮ",
+      "×IJ שר",
+      "è¡Į ãģı",
+      "ãģ» ãģĭ",
+      "æ°Ĺ ãģ«ãģªãĤĭ",
+      "й деÑĤ",
+      "íķĺìĺĢ ëĭ¤",
+      "ستÙħر ار",
+      "ĠÐŁÑĢ е",
+      "ĠÑģ боÑĢ",
+      "ĠìķĦ 무",
+      "ç§ģ ãĤĤ",
+      "ع ص",
+      "Ġн иÑĩ",
+      "ĠниÑĩ его",
+      "ĠпÑĢи ем",
+      "ק ×ķ×ŀ",
+      "ĠìĪĺ ëıĦ",
+      "Ġì ¡´",
+      "Ġì¡´ ìŀ¬",
+      "ĠØ£ Ø«ÙĨ",
+      "ĠأثÙĨ اء",
+      "ĠÙĪاÙĦ ØŃ",
+      "ãģĮ ãģ§ãģįãĤĭ",
+      "Ġת ×Ķ",
+      "Ġת×Ķ ×Ļ×Ķ",
+      "ר ף",
+      "ĠÑģвÑıз и",
+      "×Ĵ שת",
+      "Ñģп екÑĤ",
+      "ס ×ij×Ļ×ij",
+      "ס×ij×Ļ×ij ×Ķ",
+      "ĠíķĦìļĶ íķľ",
+      "ت خصص",
+      "Ġж ив",
+      "Ġжив оÑĤ",
+      "ĠMay ıs",
+      "تع ا",
+      "تعا ÙĪÙĨ",
+      "ĠعÙĨ Ùĩا",
+      "ów ki",
+      "ĠاÙĦÙģÙĦسطÙĬÙĨ ÙĬ",
+      "ãģłãģijãģ§ ãģªãģı",
+      "ìĿ¸ ì§Ģ",
+      "ĠاÙĦس ÙĪد",
+      "ĠاÙĦسÙĪد اÙĨ",
+      "إجراء ات",
+      "Ġkö tü",
+      "Ġ×Ļ תר",
+      "×Ĵ ×Ļש×Ķ",
+      "Ġצ ×ķר×ļ",
+      "รà¸ĸ ย",
+      "รà¸ĸย à¸Ļà¸ķà¹Į",
+      "Ñħ оÑĤ",
+      "Ðł ÐIJ",
+      "ÙĪ Ø·ÙĨ",
+      "Ġsay ısı",
+      "ס ×Ĺר",
+      "Ùħ ÙĪÙĦ",
+      "ãĤĴæĮģ ãģ£ãģ¦",
+      "ع اÙĨ",
+      "Ġt á»Ļi",
+      "ĠвÑĭ ÑĪе",
+      "Ġt ầm",
+      "ãĥĪ ãĥ¬",
+      "×Ļצ ×ķ",
+      "ม ุม",
+      "س ÙĪد",
+      "ìłĦ ìŀIJ",
+      "ãĤµ ãĥŃãĥ³",
+      "ìĤ° ìĹħ",
+      "ĠоÑģнов ан",
+      "Ø® Ùģض",
+      "רצ ×Ķ",
+      "بÙĬ ض",
+      "×ķÖ ¹",
+      "ס×Ļ ×Ļ×¢",
+      "Ġש ×IJ×Ļ",
+      "ĠاÙĦÙĤر Ø¢ÙĨ",
+      "ĠТак же",
+      "×ŀש ×ŀ×¢×ķת",
+      "س ÙĩÙĦ",
+      "Ġ×Ķ ׳×Ķ",
+      "ãĤĴ ãģĹãģ¦ãģĦãĤĭ",
+      "×Ļ ×Ļס",
+      "×Ķ ×ķ×IJ",
+      "ĠB ÃŃ",
+      "Ġмал о",
+      "ĠëĶ°ëĿ¼ ìĦľ",
+      "Ġר ×Ĺ×ij",
+      "ãģĮ é«ĺãģĦ",
+      "ÙĪ اس",
+      "ìĤ ¼",
+      "׳ ×¢",
+      "ãģ£ ãģ¡ãĤĥ",
+      "ĠT üm",
+      "à¸Ńีà¸ģ à¸Ķà¹īวย",
+      "ãģĹãģ¦ ãģıãģłãģķãģĦ",
+      "ÙĨØ´ اط",
+      "ãĥĹ ãĥ©ãĥ³",
+      "али ÑģÑĮ",
+      "×ĵ ×ľ×ª",
+      "Ġwc zeÅĽ",
+      "ĠwczeÅĽ niej",
+      "ĠÑįÑĤ им",
+      "Ġthá»ĭ t",
+      "à¸ļ ัà¸į",
+      "à¸ļัà¸į à¸Ĭี",
+      "ãģļ ãģ£ãģ¨",
+      "ÑĢ ин",
+      "Ġswo jÄħ",
+      "íķĺëĬĶ ëį°",
+      "Ġë§Įëĵ¤ ìĸ´",
+      "تش Ùĥ",
+      "تشÙĥ ÙĬÙĦ",
+      "ائ Ùĩ",
+      "Ġ׾פ ×Ĺ×ķת",
+      "ãĥĭ ãĥ¥",
+      "ãĥĭãĥ¥ ãĥ¼ãĤ¹",
+      "׼×IJ ף",
+      "ãģ§ãģį ãģŁ",
+      "зв он",
+      "Ġsta ÅĤ",
+      "×Ĺ×ijר ת×Ļ",
+      "ĠØ£ عÙĦÙĨ",
+      "à¹ģà¸ļà¸ļ à¸Ļีà¹ī",
+      "بد ء",
+      "ãĤģ ãģŁ",
+      "Ġ×ŀש ×ŀ×¢×ķת",
+      "Ġ×ŀש×ŀ×¢×ķת ×Ļ",
+      "ör ü",
+      "Ġh ạnh",
+      "z ähl",
+      "ĠL ý",
+      "Ġ×ij ×Ķת",
+      "Ġ×ij×Ķת ×IJ×Ŀ",
+      "б аÑĢ",
+      "ì¦ Ī",
+      "ä»ĬåĽŀ ãģ®",
+      "Ġy ü",
+      "Ġyü ks",
+      "Ġyüks el",
+      "ãĤ½ ãĥ¼",
+      "ãģĤ ãĤĮ",
+      "ת ׾×ŀ×Ļ×ĵ",
+      "ãģ¤ ãģª",
+      "×ij ׳×Ļ×Ŀ",
+      "Ġx ếp",
+      "ĠмÑĥж Ñĩин",
+      "ĠاÙĦÙĥ تاب",
+      "׼ ×ŀ×ķת",
+      "Ġç e",
+      "Ġçe ÅŁ",
+      "ĠçeÅŁ it",
+      "ĠçeÅŁit li",
+      "×ĵ ×Ļר×ķת",
+      "à¸ļุ à¸į",
+      "ĠاÙĦØ¥ ÙĦÙĥ",
+      "ĠاÙĦØ¥ÙĦÙĥ ترÙĪ",
+      "ĠاÙĦØ¥ÙĦÙĥترÙĪ ÙĨÙĬ",
+      "ĠباÙĦØ¥ ض",
+      "ĠباÙĦإض اÙģØ©",
+      "Ġyö nel",
+      "Ġyönel ik",
+      "mys ÅĤ",
+      "à¸Ķà¹īวย à¸ģาร",
+      "à¸ģาร à¸Ĺำ",
+      "ов Ñĭм",
+      "Ø£ زÙħØ©",
+      "æİ¢ ãģĹ",
+      "íļ ¨",
+      "Ġ×ķ×IJ ×Ŀ",
+      "Ġnghi êm",
+      "ÑĪ ин",
+      "ка л",
+      "Ġcrian ças",
+      "èĩªåĪĨ ãģ§",
+      "Ġн ай",
+      "Ġнай ÑĤи",
+      "ĠS á»ij",
+      "ĠÃ¶ÄŁrenc iler",
+      "ãĥ¶ æľĪ",
+      "Ñģ ан",
+      "ĠJ á",
+      "ĠkonuÅŁ ma",
+      "شر ط",
+      "ëĪ Ī",
+      "ar rière",
+      "ضر ÙĪرة",
+      "ãĥĶ ãĥ³",
+      "ע שר",
+      "аÑĢ ÑĮ",
+      "جÙħ اع",
+      "Ġdé co",
+      "Ġ×Ļ×Ķ ×ķ×ĵ×Ļ",
+      "à¸ŀ ลาà¸Ķ",
+      "ĠÙĬ ÙĥÙĨ",
+      "Ġج اÙħعة",
+      "Ø· بÙĤ",
+      "Ġbo ÅŁ",
+      "×ķ ×ķ×IJ",
+      "×ŀ×ĵ ×¢",
+      "ק×ij×ķצ ת",
+      "פ ×Ļר",
+      "jÄħc ym",
+      "ÙħØ´ ا",
+      "Ùħشا ÙĥÙĦ",
+      "צ פ×ķף",
+      "إ ست",
+      "×ŀ׼ ר",
+      "سÙħ ع",
+      "Ġкак ой",
+      "ÑĤ воÑĢ",
+      "ØŃ Ø¬",
+      "Ùģر ض",
+      "пÑĢав лен",
+      "Ġник ак",
+      "Ġmi á»ĩ",
+      "Ġmiá»ĩ ng",
+      "ü ÃŁ",
+      "иÑĢов ал",
+      "׾ ×ŀ×ķת",
+      "次 ãģ®",
+      "ÙĦ Ø·",
+      "à¸ķ ัà¸Ļ",
+      "×Ķ ת×Ĺ×Ļ׾",
+      "Ġfoto ÄŁ",
+      "ĠfotoÄŁ raf",
+      "طر ØŃ",
+      "à¸Ńà¸Ńà¸ģ à¹Ħà¸Ľ",
+      "Ġy ên",
+      "Ġп ок",
+      "Ġпок Ñĥп",
+      "ĠпокÑĥп а",
+      "ÑĨ Ñĥ",
+      "Ġкомп ÑĮÑİ",
+      "ĠкомпÑĮÑİ ÑĤеÑĢ",
+      "ĠاÙĦÙĥ رÙĬÙħ",
+      "تص Ùħ",
+      "تصÙħ ÙĬÙħ",
+      "Ġоказ а",
+      "Ġzar ówn",
+      "Ġzarówn o",
+      "ëĮĢ ì¶ľ",
+      "ãĤ»ãĥ³ ãĤ¿ãĥ¼",
+      "Ġjako ÅĽci",
+      "æĤ ©",
+      "æĤ© ãģ¿",
+      "Ø£ÙĨ ÙĪ",
+      "Ø£ÙĨÙĪ اع",
+      "ë¹ ł",
+      "Ġìłķ ë§IJ",
+      "Ġk ẻ",
+      "ĠÑģай ÑĤа",
+      "Ġ×Ķ ער×ij",
+      "Ùĩ ز",
+      "pres ión",
+      "ĠÑģÑĤ ен",
+      "ãģ£ãģ¦ ãĤĭ",
+      "Ġhız lı",
+      "Ðļ ÐIJ",
+      "×ŀשפ ×Ĺת",
+      "ĠÙĨ Ùĩا",
+      "ĠÙĨÙĩا ÙĬØ©",
+      "ãģ¾ ãģĦ",
+      "о ÑħÑĢан",
+      "ร à¹īà¸Ńย",
+      "ล ึà¸ģ",
+      "ĠÙĪب اÙĦ",
+      "ãĤĤãģ® ãģĮ",
+      "ר׼ ×Ļ×ij",
+      "ãĤ¤ ãĥ¤",
+      "س ؤ",
+      "سؤ اÙĦ",
+      "ĠÙĦØ£ÙĨ Ùĩ",
+      "ĠkonuÅŁ tu",
+      "Ðļ ÑĥпиÑĤÑĮ",
+      "Ġש×IJת ×Ķ",
+      "ĠÙĪاÙĦ س",
+      "Ġmożliwo ÅĽci",
+      "Ġpró b",
+      "ëĶ °",
+      "ãģ© ãĤĮ",
+      "ĠÐľ ин",
+      "ĠоÑĢганиз м",
+      "ãģ«å¯¾ ãģĻãĤĭ",
+      "ĠPr é",
+      "Ġpriv é",
+      "ch è",
+      "ãģĦãģŁãģł ãģį",
+      "สà¸Ļุ à¸ģ",
+      "ajÄħ ce",
+      "ĠD zi",
+      "ĠDzi ÄĻki",
+      "ÅĤat w",
+      "r än",
+      "rän k",
+      "æĿ¥ ãģŁ",
+      "Ġ×Ķ×Ļ×Ķ ×ķ×ĵ×Ļ",
+      "ãĤ¬ ãĥ¼",
+      "ĠÑĢаР´",
+      "ĠÑĢад и",
+      "к ÑĤив",
+      "Ø£ Ùĩد",
+      "Ø£Ùĩد اÙģ",
+      "ש ×IJ×Ļר",
+      "ãģ¦ ãģĦãģªãģĦ",
+      "Ġfr üh",
+      "Ġок ол",
+      "Ġокол о",
+      "Ġreg ião",
+      "ĠÑĩиÑģ ле",
+      "Ġpon iew",
+      "Ġponiew aż",
+      "ìĦ¼ íĦ°",
+      "Ġb ầu",
+      "Ġê ·",
+      "Ġê· ľ",
+      "Ġê·ľ ìłķ",
+      "ĠH òa",
+      "ĠÑĤ оÑĤ",
+      "ãĤĤ å¤ļãģĦ",
+      "ĠاÙĦإسÙĦاÙħ ÙĬØ©",
+      "ãģĭ ãģĦ",
+      "Ñį н",
+      "ĠÑĥказ ан",
+      "ĠÑĤак ое",
+      "ï¼ ³",
+      "ëĮĢ íķĻ",
+      "Ġgen iÅŁ",
+      "ĠاÙĦØ® ÙĬ",
+      "ĠاÙĦØ®ÙĬ ارات",
+      "ãĤĴè¡Į ãģĨ",
+      "ש ×ŀ×Ķ",
+      "ĠLÃł m",
+      "ÙĪÙĨ ÙĬ",
+      "Ġ×IJ ׾×Ļ×ķ",
+      "Ä ĺ",
+      "à¹Ħมà¹Ī สามารà¸ĸ",
+      "人 ãģ¨",
+      "بر ز",
+      "×Ļס ×ķ×ĵ",
+      "×Ĵ ׾×Ļ",
+      "ĠÙĬ ÙĨا",
+      "ĠÙĬÙĨا ÙĬر",
+      "ĠкаÑĢÑĤ ин",
+      "Ġt ôn",
+      "à¹Ģ à¸ģร",
+      "à¸Ħ à¸Ķี",
+      "Ġ׾×IJ ×ķר×ļ",
+      "ãĤĤãĤī ãģĨ",
+      "ãģĭ ãģĭãĤĭ",
+      "ани и",
+      "Ġara ÅŁtırma",
+      "ÙĦاØŃ Ø¸",
+      "ãģĦ ãĤĦ",
+      "ĠT Ãłi",
+      "Ġ à¸Ļà¸Ńà¸ģà¸Īาà¸ģ",
+      "Ġà¸Ļà¸Ńà¸ģà¸Īาà¸ģ à¸Ļีà¹ī",
+      "ĠÄIJ ảng",
+      "ãģ£ãģ¦ ãģįãģŁ",
+      "Ġà¸ĭึà¹Īà¸ĩ à¹Ģà¸Ľà¹ĩà¸Ļ",
+      "Ġt ả",
+      "Ġmożliwo ÅĽÄĩ",
+      "ĠS ản",
+      "ĠÄ° ki",
+      "Ġc ắt",
+      "س Ø£ÙĦ",
+      "Ġbak ım",
+      "ش ب",
+      "à¸ķ ีà¹ī",
+      "à¸ŀ ยาย",
+      "à¸ŀยาย าม",
+      "สั à¸Ľ",
+      "à¸ªà¸±à¸Ľ à¸Ķา",
+      "à¸ªà¸±à¸Ľà¸Ķา หà¹Į",
+      "ë° Ģ",
+      "еÑĢ Ñĭ",
+      "Ġc ánh",
+      "Ġthu ế",
+      "ت بع",
+      "ãģ«åħ¥ ãĤĮ",
+      "Ñİ ÑģÑĮ",
+      "íļĮ ìĿĺ",
+      "ç°¡ åį",
+      "ç°¡åį ĺ",
+      "ç°¡åįĺ ãģ«",
+      "Ġtr úc",
+      "ĠاÙĦÙĥ ÙĪÙĬ",
+      "ĠاÙĦÙĥÙĪÙĬ ت",
+      "ãĤıãģij ãģ§ãģĻ",
+      "ĠÑģв об",
+      "ĠÑģвоб од",
+      "ĠÑĥÑĩаÑģÑĤ ник",
+      "สิ à¹īà¸Ļ",
+      "ĠпÑĢо ÑĦеÑģÑģиона",
+      "ĠпÑĢоÑĦеÑģÑģиона лÑĮн",
+      "Ñģп оÑĢ",
+      "×Ĺ ×ķ×ij×Ķ",
+      "Ùħع ÙĨÙī",
+      "ĠاÙĦÙģ ترة",
+      "สูà¸ĩ สุà¸Ķ",
+      "ãĤı ãģļ",
+      "ĠÄij è",
+      "ĠÄijè n",
+      "æ¯Ķ ãģ¹",
+      "า à¸ĺิ",
+      "Ġmoż emy",
+      "à¹ģ à¸ĭ",
+      "à¸Īะ à¹Ħมà¹Ī",
+      "Ġs ắp",
+      "Ðļ Ðŀ",
+      "Ġprá ctica",
+      "ÙĪÙĥ اÙĦØ©",
+      "è¾¼ ãĤĵãģ§",
+      "ológ ica",
+      "Ġе Ñī",
+      "ĠеÑī Ñij",
+      "تع دÙĬÙĦ",
+      "ĠØ£ Ùĥد",
+      "Ġצר ×Ļ׼",
+      "Ġצר×Ļ׼ ×Ļ×Ŀ",
+      "Ø« Ùħ",
+      "Ġк ÑĢÑĥ",
+      "ĠкÑĢÑĥ п",
+      "×ij×Ļק ×ķרת",
+      "Ġì¡° ê¸Ī",
+      "ãģ¨ãģį ãģ¯",
+      "Ġb ạc",
+      "ĠÑĢаÑģ пол",
+      "ĠÑĢаÑģпол ож",
+      "ĠÑĢаÑģполож ен",
+      "ز ÙĬÙĨ",
+      "ĠÐļ ÑĢоме",
+      "ĠاÙĦÙĨ ظر",
+      "×Ķ ×ķ×ĵ",
+      "ĠاÙĦس بت",
+      "ãģ¨æĢĿ ãģĦ",
+      "Ġpa ÅĦst",
+      "ĠpaÅĦst w",
+      "ĠÙĦÙĬ ست",
+      "ĠбÑĥд Ñĥ",
+      "à¸Ĺัà¸Ļ à¸Ĺี",
+      "ร าม",
+      "ØŃ ØµÙĪÙĦ",
+      "ãģĹãģ¦ãģıãĤĮ ãĤĭ",
+      "ĠاÙĦØ¥ سرائÙĬÙĦ",
+      "ĠاÙĦإسرائÙĬÙĦ ÙĬ",
+      "ãģĵãĤĮ ãģ¾ãģ§",
+      "ìĤ¬ 를",
+      "Ġs ürü",
+      "à¹Ģว à¸Ńรà¹Į",
+      "à¹Ģà¸ĭ à¸Ńรà¹Į",
+      "Ġutilis é",
+      "ĠÑģиÑģÑĤем а",
+      "Ġdw ó",
+      "Ġdwó ch",
+      "Ġpróp rio",
+      "Ġëĵ± ìĿĦ",
+      "arr êt",
+      "ĠЧ а",
+      "×IJ×ŀ ׳×ķת",
+      "عار ض",
+      "à¹Ģà¸ģม สà¹Į",
+      "Ġ׾×Ķ ×ij×Ļף",
+      "Ġ׾ ×ij×Ĺ",
+      "Ġ׾×ij×Ĺ ×ķר",
+      "สา à¸Ĥา",
+      "ĠÐľÐ¾Ñģк ве",
+      "ب عد",
+      "ĠاÙĦÙĤر ار",
+      "ĠÄIJ á»ĭa",
+      "Ġ×Ĺ ×Ĵ",
+      "Ùģ تر",
+      "ÙĪÙĨ Ø©",
+      "Ġ×Ķ×ĸ ×IJת",
+      "å¸Ĥ ãģ®",
+      "ãģ» ãģĹãģĦ",
+      "Ġ×ij×¢ ×Ļר",
+      "ĠÑĤеп еÑĢÑĮ",
+      "ìĬµ ëĭĪê¹Į",
+      "à¹Ħม à¹Īว",
+      "à¹Ħมà¹Īว à¹Īา",
+      "à¹Ħมà¹Īวà¹Īา à¸Īะ",
+      "×ŀ ×IJ×Ķ",
+      "æĥħ åł±",
+      "æĥħåł± ãĤĴ",
+      "غ ÙĨ",
+      "Ġпо Ñı",
+      "ĠпоÑı ви",
+      "éģİ ãģĶ",
+      "تش غ",
+      "تشغ ÙĬÙĦ",
+      "в ел",
+      "Ġ×Ĺ ×ŀ",
+      "ãģ¨ãģªãĤĬ ãģ¾ãģĻ",
+      "Ġra ÄŁ",
+      "ĠraÄŁ men",
+      "ãģĭ ãģ©ãģĨ",
+      "ãģĭãģ©ãģĨ ãģĭ",
+      "ен ко",
+      "ì§Ģ ê³ł",
+      "Ġ×IJ׾ ×Ļ×Ķ",
+      "ĠØ£ ÙĦ",
+      "à¸Īำ หà¸Ļ",
+      "à¸Īำหà¸Ļ à¹Īาย",
+      "nız ı",
+      "Ġ׾ק ×Ĺת",
+      "Ø£ ÙĩÙħ",
+      "Ø£ÙĩÙħ ÙĬØ©",
+      "ت غÙĬر",
+      "ש ×Ĺר",
+      "ס×ķפ ר",
+      "×ĵ ×Ļר",
+      "èī¯ ãģĭãģ£ãģŁ",
+      "×ŀ׾×Ĺ ×ŀ×Ķ",
+      "ÑģÑĤв ие",
+      "ÑĤ ÑĢаÑĤ",
+      "ĠاÙĦØ£ Ø®",
+      "ĠاÙĦأخ ÙĬرة",
+      "ĠاÙĦØŃ ØµÙĪÙĦ",
+      "Ġcréd ito",
+      "צ ×Ļ×¢",
+      "ãĥ¬ ãĥĻãĥ«",
+      "بر ÙĬ",
+      "ëIJ IJ",
+      "ãģł ãģ£ãģ¦",
+      "Ġreal tÃł",
+      "س Ùģر",
+      "×ķ׳ ×ķ",
+      "×Ĵ ×ķ×ĵ",
+      "×Ĵ×ķ×ĵ ׾",
+      "ฮ า",
+      "ãģĹãģ¦ ãģĬãĤĬãģ¾ãģĻ",
+      "Ġg Ãł",
+      "Ġ׾×ij צע",
+      "å¼ķ è¶ĬãģĹ",
+      "Ġ×ŀ ×Ļ׾×Ļ",
+      "Ġ×ŀ×Ļ׾×Ļ ×ķף",
+      "Ùħ در",
+      "Ùħدر سة",
+      "פ ×ķ×ĺ",
+      "à¸Ļà¹īำ มัà¸Ļ",
+      "ëģ Ŀ",
+      "ع Ùĥس",
+      "ĠÙĤ ض",
+      "ĠÑĢÑĭ б",
+      "خط ط",
+      "×ŀ×ķס ×ĵ",
+      "Ġ׼׾ ׾×Ļ",
+      "ĠкоÑĤоÑĢ ое",
+      "צ×Ļ ×ķף",
+      "ĠмеÑģÑĤ а",
+      "ãģĭ ãģ¤",
+      "г ÑĢÑĥпп",
+      "׾ ×Ļ׾",
+      "ת ×ķ×IJר",
+      "ë³µ ì§Ģ",
+      "à¹ģà¸ľ à¹Īà¸Ļ",
+      "Ġ×ij×¢ ת",
+      "æĻĤéĸĵ ãĤĴ",
+      "ï¼ £",
+      "ãģ¨ãģĦãģĨãģĵãģ¨ ãģ§",
+      "Ġ׾×Ķ ק",
+      "Ġ׾ ×ĸ×Ķ",
+      "ĠìłĢ ëĬĶ",
+      "ĠاÙĦØ¥ رÙĩاب",
+      "ĠìŀĪëĬĶ ëį°",
+      "ĠÑĤ огда",
+      "Ġ×Ķ צ×Ļ",
+      "×ķ׾ ×ĺ",
+      "Ġר פ×ķ×IJ×Ļ",
+      "ãģĵãģ¨ ãģ§ãģĻ",
+      "ĠÄij ÃŃch",
+      "ØŃ ÙĬا",
+      "Ġ×Ķ×ŀש ×Ĺק",
+      "ãģľ ãģ²",
+      "Ġ×ŀ×IJ פשר",
+      "ãģ¿ ãģ¾ãģĹãģŁ",
+      "ĠاÙĦØ£ÙħÙĬر ÙĥÙĬ",
+      "Ùħج تÙħع",
+      "Ġس اب",
+      "Ġساب ÙĤ",
+      "׼ ×Ļ׾",
+      "Ạ¾",
+      "ãĥª ãĤ¹ãĥĪ",
+      "Ġì ĥ",
+      "Ġìĥ Ī",
+      "ĠìĥĪ ë¡ľ",
+      "ĠìĥĪë¡ľ ìļ´",
+      "ĠD á»ĭch",
+      "à¹Ģหมาะ สม",
+      "ĠاÙĦÙĨ بÙĬ",
+      "׾ ׾",
+      "ÙĨ ع",
+      "Ðĵ лав",
+      "Ðĵлав наÑı",
+      "Ùħر ض",
+      "Ġ×ķ ×ĵ",
+      "ت ÙĤÙĬ",
+      "تÙĤÙĬ ÙĬÙħ",
+      "Ġb ảng",
+      "ĠÙģ ÙĤاÙĦ",
+      "×¢ ×ŀ×Ļ",
+      "д ÑĢа",
+      "Ġsu á»ijt",
+      "سر عة",
+      "Ġc á»Ń",
+      "Ġ×Ķ ×Ļ×Ĺ×Ļ×ĵ",
+      "سع ÙĬد",
+      "à¸Ńา à¸Ĭีà¸ŀ",
+      "Ġس ÙĪاء",
+      "ãĤ½ ãĥķãĥĪ",
+      "Ġл иÑĩно",
+      "ĠÐļ оÑĢ",
+      "اÙĩ تÙħ",
+      "اÙĩتÙħ اÙħ",
+      "à¸Ń à¸Ķี",
+      "à¸Ńà¸Ķี à¸ķ",
+      "ãģIJ ãĤīãģĦ",
+      "Ġiht iya",
+      "Ġihtiya ç",
+      "ãģ¾ãģ§ ãģ®",
+      "ìĭľ ìĬ¤",
+      "ìĭľìĬ¤ íħľ",
+      "ÑĢÑĥ ÑĪ",
+      "ãĤĦ ãģ£ãģ±",
+      "ãĤĦãģ£ãģ± ãĤĬ",
+      "к еÑĢ",
+      "Ġ ży",
+      "Ġży w",
+      "кл он",
+      "Ġl ượt",
+      "Ã ¾",
+      "да Ñĩи",
+      "tür k",
+      "غ ÙĪ",
+      "ĠигÑĢ ок",
+      "Ġph ê",
+      "Ġש ×¢×ľ",
+      "ĠاÙĦÙħ دÙĨÙĬ",
+      "ĠìŬ룬 ë¶Ħ",
+      "ער ×Ļ×Ŀ",
+      "Ñħод ÑıÑĤ",
+      "Ġx ứ",
+      "ÐĹ Ð°",
+      "ĠÙģ رص",
+      "à¸Īะ à¸Ĺำà¹ĥหà¹ī",
+      "íģ ´",
+      "×¢ ×ij×ķר",
+      "à¹Ģหลà¹Īา à¸Ļีà¹ī",
+      "èĢĥãģĪ ãĤĭ",
+      "ÑĢ еÑģÑĤ",
+      "н нÑĭй",
+      "Ġc ầm",
+      "دا Ø®ÙĦ",
+      "ĠÙħÙĦÙĬ ار",
+      "ĠÐIJ л",
+      "ĠвÑĢем ен",
+      "à¸Ĭà¹Īวย à¹ĥหà¹ī",
+      "ר×Ļ ×ķת",
+      "ëĵ ¯",
+      "飲 ãģ¿",
+      "׳ ׾",
+      "שת ף",
+      "ĠاÙĦسعÙĪد ÙĬ",
+      "u ÃŁ",
+      "ìĿ¸ ëį°",
+      "ĠìĿ¼ ë°ĺ",
+      "ÅĤ ÄĻ",
+      "Ġm á»iji",
+      "×ŀ ×Ļ׳",
+      "ĠاÙĦØ£ Ø·ÙģاÙĦ",
+      "Ġçı kan",
+      "é cole",
+      "ק ×Ļש",
+      "ק×Ļש ×ķר",
+      "ĠоÑģ ÑĥÑīеÑģÑĤв",
+      "ĠоÑģÑĥÑīеÑģÑĤв лÑı",
+      "×ij ×IJר",
+      "à¹Ħà¸Ľ à¸Ķà¹īวย",
+      "Ġ×¢ ×ķ׾×Ķ",
+      "à¸ģà¹ĩ à¹Ħมà¹Ī",
+      "ãĥ¢ ãĥĩ",
+      "ãĥ¢ãĥĩ ãĥ«",
+      "تØŃ ÙĪÙĦ",
+      "Ġод ного",
+      "ת×Ĺ×Ļ׾ ת",
+      "Ġت Ø®",
+      "Ġch cia",
+      "Ġchcia ÅĤ",
+      "ãĥIJ ãĥ³",
+      "èĢħ ãģ¯",
+      "ĠÙħ ØŃÙĦ",
+      "Ñģл ож",
+      "Ñģлож н",
+      "Ġt ÄĻ",
+      "Ġçı kt",
+      "Ġçıkt ı",
+      "ĠC Æ¡",
+      "à¹Ħà¸Ķà¹ī à¹Ģลย",
+      "ır ken",
+      "à¹Ģà¸Ĥà¹īา สูà¹Ī",
+      "ÙħØŃ Ùĥ",
+      "ÙħØŃÙĥ ÙħØ©",
+      "à¸Ħุ à¹īม",
+      "à¸Ļà¹Īา à¸Īะ",
+      "лÑİ Ð´",
+      "де ÑģÑı",
+      "деÑģÑı ÑĤ",
+      "ĠлÑİб ой",
+      "تØŃر ÙĬر",
+      "צע ×ĵ",
+      "Ġе Ñij",
+      "ĠاÙĦØŃ ÙĥÙħ",
+      "Ġص باØŃ",
+      "à¹Ģà¸ļ à¸Ńรà¹Į",
+      "Ġróż nych",
+      "ги б",
+      "ĠÑģ оÑĤ",
+      "ĠÑģоÑĤ ÑĢÑĥд",
+      "ĠÑģоÑĤÑĢÑĥд ник",
+      "ĠобÑĬ ем",
+      "פ ×ĺר",
+      "ãģĻãģĶ ãģı",
+      "ãģ«éĸ¢ ãģĹãģ¦",
+      "в ол",
+      "Ø« ÙħاÙĨ",
+      "Ġd ần",
+      "æĬ ľ",
+      "æĬľ ãģij",
+      "Ġ×¢ ש",
+      "Ġעש ×ķ×Ļ",
+      "ס ×ķף",
+      "ãģªãģ® ãģ§ãģĻ",
+      "ãģ¯ ãģ©ãģĨ",
+      "×ŀ×¢ ר×ij",
+      "ï¼ °",
+      "Ùħ صر",
+      "ÙħÙĨ اسب",
+      "ÙħÙĨاسب Ø©",
+      "ä¸Ĭ ãģ®",
+      "×IJ×Ļש ×ķר",
+      "ĠìĦ¤ ì¹ĺ",
+      "×ŀ×ĵ×Ļ׳ ×ķת",
+      "×ŀר ת",
+      "ãĤĭ ãģ®ãģĮ",
+      "د Ùİ",
+      "ĠاÙĦشر Ùĥات",
+      "ìĭľ ê°Ħ",
+      "ĠÑĢеÑĪ ение",
+      "ãģĻãĤĭ ãģ®ãģ¯",
+      "ĠìŀIJìĭł ìĿĺ",
+      "׾ ×ŀ×ķ",
+      "ãģ¨ãģĵãĤį ãģ§",
+      "Ġק צר",
+      "Ġmã i",
+      "Ġkü ltür",
+      "ãĥ©ãĤ¤ ãĥĸ",
+      "à¸ľà¸¹à¹ī หà¸įิà¸ĩ",
+      "æĻĤéĸĵ ãģĮ",
+      "клÑİÑĩ и",
+      "diÄŁ iniz",
+      "มาà¸ģ à¹Ĩ",
+      "تØŃ ÙħÙĦ",
+      "Ġh ạt",
+      "ãĤ¦ ãĤ£",
+      "п ле",
+      "×ŀ ׾×IJ",
+      "ÅĤ ó",
+      "Ġg á»ijc",
+      "Ġ×IJ ×ķ×ĵ×ķת",
+      "หว าà¸Ļ",
+      "ĠاÙĦ ÙĪز",
+      "ĠاÙĦÙĪز راء",
+      "ëĵ¤ ê³¼",
+      "Ġص ØŃ",
+      "ĠصØŃ ÙĬÙģØ©",
+      "Ġм м",
+      "تد Ø®ÙĦ",
+      "Ġpersön lich",
+      "Ġز ÙĬ",
+      "ĠزÙĬ ادة",
+      "ãĤ· ãĤ¢",
+      "Ġng ắn",
+      "à¸Ħล ิà¸ģ",
+      "Ġs ông",
+      "Ġtü ket",
+      "Ñį ÑĦÑĦ",
+      "ÑįÑĦÑĦ екÑĤ",
+      "ש ×Ļ×ij",
+      "Ġا عت",
+      "ت ض",
+      "تض ÙħÙĨ",
+      "ĠاÙĦÙħØ´ رÙĪع",
+      "Ġprodu ção",
+      "ĠпÑĢимен Ñı",
+      "ни ÑĨÑĭ",
+      "주 ëĬĶ",
+      "ر Ùı",
+      "Ġm Æ¡",
+      "Ġhayat ı",
+      "ëŁ ½",
+      "Ġü cret",
+      "Ġyan ında",
+      "Ġpr ática",
+      "×ij×Ļק ×ķר",
+      "Ãľ N",
+      "Ñģ оÑĤ",
+      "ãĤıãģij ãģ§",
+      "Ġдол го",
+      "ת ׼×ķ",
+      "ĠìķĦ ëĭĮ",
+      "ë į°ìĿ´",
+      "Ġç iz",
+      "Ġcho Äĩ",
+      "Ġ×Ķ ×Ļת",
+      "Ġ×Ķ×Ļת ר",
+      "Ġso át",
+      "׼ ×ij×ĵ",
+      "à¹Ģล à¹Īา",
+      "Ġд еÑĢ",
+      "ĠдеÑĢ ев",
+      "ãĤĴ åħ¥ãĤĮ",
+      "×Ĺ ×ķס",
+      "×Ĺ×ķס ר",
+      "ج ÙĬÙĨ",
+      "t ón",
+      "onn é",
+      "Ġпол ноÑģÑĤÑĮÑİ",
+      "人 ãģŁãģ¡",
+      "Ġpr êt",
+      "ëł ¸",
+      "Ġdéc embre",
+      "cı lar",
+      "Ġת ת",
+      "Ġê²½ìļ° ìĹIJëĬĶ",
+      "ÙĪ عد",
+      "è¦ĭ ãĤĭ",
+      "วิ à¸Īัย",
+      "ë ¶Ī",
+      "ز ÙĪا",
+      "زÙĪا ج",
+      "d ì",
+      "ãģ§ãģĻ ãĤĪ",
+      "Ġвод о",
+      "ĠÙĬ ÙĪجد",
+      "Ñģ оÑģÑĤоÑı",
+      "Ðŀ С",
+      "ĠÄIJ ó",
+      "׊פש",
+      "Ġצ ×Ļ×ij×ķר",
+      "ĠاÙĦÙĤ Ø·",
+      "ĠاÙĦÙĤØ· اع",
+      "Ġиме ÑİÑĤ",
+      "Ġph áºŃn",
+      "×Ľ×¡ פ×Ļ",
+      "полн иÑĤелÑĮ",
+      "éĻIJ ãĤĬ",
+      "ĠÑģ ÑĢав",
+      "ĠÑģÑĢав н",
+      "ÙħاÙĦ Ùĥ",
+      "×ĵר ×ķ×Ŀ",
+      "çļĨ ãģķãĤĵ",
+      "ØŃÙĤ ÙĤ",
+      "à¹ģหล à¹Īà¸ĩ",
+      "ĠاÙĦر سÙħÙĬ",
+      "оÑĩ ки",
+      "×ĺ ×ij×Ĺ",
+      "Ġcan lı",
+      "Ġ׾ ׾",
+      "Ġ׾׾ ×ŀ×ķ×ĵ",
+      "×ŀ×ij ×ķ",
+      "ת ׼",
+      "×ª×Ľ ׳×Ļת",
+      "ĠاÙĦÙħ شار",
+      "ĠاÙĦÙħشار ÙĥØ©",
+      "Ä° Åŀ",
+      "ĠسÙĬ اسÙĬ",
+      "в олÑĮ",
+      "ĠÑģ пÑĢав",
+      "æĿ¥ ãģ¦",
+      "פ×ķר ×ķ×Ŀ",
+      "สำ à¹Ģรà¹ĩ",
+      "สำà¹Ģรà¹ĩ à¸Ī",
+      "ĠÅŁ öyle",
+      "Ġzosta ÅĤa",
+      "ĠH ü",
+      "ר ×ķש",
+      "د ÙĦÙĬÙĦ",
+      "ÑĢи д",
+      "ש ף",
+      "×ŀק ×ķר",
+      "ĠÑĥ Ñĩ",
+      "ĠÑĥÑĩ еб",
+      "ĠÑį ÑĤа",
+      "ков а",
+      "à¸ķà¸Ļ à¹Ģà¸Ńà¸ĩ",
+      "ÙĨ ÙIJ",
+      "à¸Ńีà¸ģ à¸Ħรัà¹īà¸ĩ",
+      "ระ à¸ļุ",
+      "Ġd ữ",
+      "ĠاÙĦØŃ Ø§ÙĦÙĬ",
+      "׼ ×ķ׼",
+      "׼×ķ׼ ×ij",
+      "Ġ×ŀ×IJ שר",
+      "Ġtr ụ",
+      "ÑĤел ем",
+      "Ġв ли",
+      "Ġвли Ñı",
+      "Ġש×IJת ×Ŀ",
+      "Ġuw ag",
+      "Ġuwag ÄĻ",
+      "×ĺ ×Ļת",
+      "×IJ ×ĵ×Ŀ",
+      "à¸Ķ ุ",
+      "Ġ×Ķ×IJ ׾×Ķ",
+      "Ġkar Ä±ÅŁ",
+      "ĠÄIJ á»iji",
+      "да ÑİÑĤ",
+      "ãģªãģ® ãģ«",
+      "Äħ cych",
+      "à¹Ģà¸Ļ à¹īà¸Ļ",
+      "ãģĹãģ¦ ãģĹãģ¾ãģĨ",
+      "int érieur",
+      "ĠfÃŃs ica",
+      "ĠÐŁ ол",
+      "ãģĹãģ ķ",
+      "à¸Ĺำ à¹Ħม",
+      "ĠL âm",
+      "ĠاÙĦÙħ سÙĦÙħ",
+      "ĠاÙĦÙħسÙĦÙħ ÙĬÙĨ",
+      "ص ØŃØ©",
+      "ìĹ Ħ",
+      "à¹Ģà¸Ķà¹ĩ à¸Ķ",
+      "ĠÑĥ ÑĩеÑĤ",
+      "â Ìģ",
+      "Ġب ÙĦا",
+      "ĠاÙĦاجتÙħاع ÙĬ",
+      "פרס ×Ŀ",
+      "ãĥķ ãĥ©",
+      "ĠÐļ огда",
+      "mie ÅĽci",
+      "ĠبÙĬÙĨ Ùħا",
+      "Ġ×ŀ×IJ ×ŀר×Ļ×Ŀ",
+      "Ġ×ij×IJ ×ĸ×ķר",
+      "×ķש ×Ļ×Ŀ",
+      "ĠÑģдел а",
+      "entr ée",
+      "à¹Ģ à¸Ħà¹īา",
+      "Ñĥг л",
+      "ĠاÙĦÙģ ÙĨÙĬ",
+      "ĠÐĴ оÑĤ",
+      "à¸Ĺีà¹Ī มา",
+      "×ķצ ×Ĵ",
+      "ÙĤد رة",
+      "Ġëª ©",
+      "Ġ목 ìłģ",
+      "íıī ê°Ģ",
+      "ĠاÙĦØ£ ربع",
+      "ĠاÙĦأربع اء",
+      "פס ×Ļק",
+      "ĠÑıвлÑı ÑİÑĤÑģÑı",
+      "ب ÙĪÙĨ",
+      "ì° ¾",
+      "×ŀ×¢ ר׼",
+      "×ŀ×¢×¨×Ľ ×ķת",
+      "ãĤ· ãĤ§",
+      "ĠباÙĦ Ø£",
+      "íĸĪ ëįĺ",
+      "ĠاÙĦبر ÙĨاÙħج",
+      "ĠاÙĦØ£ ØŃد",
+      "Ġm Å©",
+      "ĠmÅ© i",
+      "п аÑĤ",
+      "ب ث",
+      "ĠÑĨ енÑĭ",
+      "Ġ×ijת ׾",
+      "è¨Ģ ãĤıãĤĮ",
+      "ĠاÙĦÙħ جاÙĦ",
+      "ĠìĦ¸ ìĥģ",
+      "Ġ×Ĵ ×ķפ",
+      "ĠнаÑĪ ей",
+      "Ġкомп аниÑı",
+      "б ин",
+      "öl ü",
+      "×Ļ ×Ļ×ĺ",
+      "Ġ×ŀס פ×Ļק",
+      "ยัà¸ĩ à¸Ħà¸ĩ",
+      "ĠЧ и",
+      "Ġан ÑĤи",
+      "ĠÑģÑĢед и",
+      "สà¹Īวà¸Ļ à¹ĥหà¸įà¹Ī",
+      "оÑĩ ка",
+      "íĬ¹ ë³Ħ",
+      "ว à¹Īาà¸ĩ",
+      "гоÑĢ од",
+      "با Ùĥ",
+      "à¹Ģส ีà¹Īย",
+      "à¹Ģสีà¹Īย à¸ĩ",
+      "ãĤĤãĤī ãģĦ",
+      "ק ×ķ×Ŀ",
+      "ãģĽ ãģļ",
+      "ĠاÙĦÙĤ اÙĩرة",
+      "Ġ×ij ׼×ļ",
+      "Ùħشار ÙĬع",
+      "باØŃ Ø«",
+      "Ġпо Ñĩ",
+      "ĠпоÑĩ ÑĤи",
+      "ĠÑĦоÑĢм а",
+      "S Ä°",
+      "Ġ×ŀצ ×Ļ×¢",
+      "ล ื",
+      "ลื ม",
+      "ĠÑĤ еÑĢ",
+      "ĠÑĤеÑĢ ÑĢиÑĤоÑĢ",
+      "ĠÑĤеÑĢÑĢиÑĤоÑĢ ии",
+      "Ġв меÑģÑĤ",
+      "ĠвмеÑģÑĤ е",
+      "dıkl arı",
+      "op ération",
+      "à¹Ĥ ห",
+      "ص دÙĬ",
+      "صدÙĬ ÙĤ",
+      "íĸī ìłķ",
+      "تج ا",
+      "تجا ÙĪز",
+      "Ġsu ç",
+      "Ġar ty",
+      "Ġarty ku",
+      "Ġartyku ÅĤ",
+      "ãĤ·ãĥ§ ãĥĥãĥĹ",
+      "ש פ",
+      "שפ ×Ļ×¢",
+      "Ġ×Ķש ×Ļר×ķת",
+      "à¹ģà¸ĸ ม",
+      "ë¸ Ķ",
+      "Ġuk ÅĤad",
+      "Ġ×ķ ׼×Ļ",
+      "หล าà¸ģ",
+      "หลาà¸ģ หลาย",
+      "æĸ¹ ãĤĤ",
+      "Ġpodr óż",
+      "ĠE ÄŁer",
+      "Ġком наÑĤ",
+      "ĠÑģам ÑĭÑħ",
+      "Ġв кÑĥÑģ",
+      "б еж",
+      "Ġ×ij ק×ķ",
+      "æİĽ ãģij",
+      "ãģ¿ ãĤĭãģ¨",
+      "ĠiliÅŁ kin",
+      "ĠÙĬ عÙħÙĦ",
+      "Ġпод аÑĢ",
+      "Ġyaz ılı",
+      "ãĤĴ å¾Ĺ",
+      "Ġwyst ÄĻp",
+      "à¸Ĺีà¹Ī à¹ĥà¸Ĭà¹ī",
+      "ØŃاد Ø«",
+      "ÙĪ ÙĬد",
+      "кÑĥ лÑĮÑĤ",
+      "кÑĥлÑĮÑĤ ÑĥÑĢ",
+      "à¸ģาร à¹ģà¸Ĥà¹Īà¸ĩ",
+      "à¸ģารà¹ģà¸Ĥà¹Īà¸ĩ à¸Ĥ",
+      "à¸ģารà¹ģà¸Ĥà¹Īà¸ĩà¸Ĥ ัà¸Ļ",
+      "ÙħÙĪ ظ",
+      "ÙħÙĪظ Ùģ",
+      "ÙĬÙħ ÙĬ",
+      "ãĤĵãģ§ãģĻ ãģĮ",
+      "diÄŁ im",
+      "diÄŁim iz",
+      "ĠÐŁ еÑĢ",
+      "ĠÐŁÐµÑĢ в",
+      "Ġm ão",
+      "ĠÑģ ез",
+      "ĠÑģез он",
+      "Ġ×Ķ×ŀ ×¢",
+      "Ùħ جÙħÙĪعة",
+      "ĠинÑĦоÑĢм аÑĨии",
+      "i ếc",
+      "ã ng",
+      "ĠÄij ấy",
+      "ãģĶ ç´",
+      "ãģĶç´ ¹",
+      "ãģĶç´¹ ä»ĭ",
+      "Ġad ım",
+      "à¹Ħ หล",
+      "Ġп ÑĢакÑĤи",
+      "ĠпÑĢакÑĤи Ñĩ",
+      "ĠпÑĢакÑĤиÑĩ еÑģ",
+      "ĠпÑĢакÑĤиÑĩеÑģ ки",
+      "ĠاÙĦÙĨ Ùģس",
+      "ĠÑĢабоÑĤ е",
+      "ÙĦÙĬ Ùģ",
+      "ĠاÙĦجÙĨ ÙĪب",
+      "Ġвод Ñĭ",
+      "ì¹ Ļ",
+      "Ġм иÑĢа",
+      "ĠÄij ừng",
+      "ĠпÑĢоÑĤив о",
+      "ĠÑģÑĤÑĢан Ñĭ",
+      "ล ู",
+      "ìĤ ¶",
+      "kre ÅĽl",
+      "Ġbul und",
+      "Ġbulund uÄŁu",
+      "à¹ģ สà¸Ļ",
+      "ãĤ± ãĤ¢",
+      "ת×Ĺ ×ķ×ŀ×Ļ",
+      "ר׼ ×Ķ",
+      "Ġ׾ק ×ķ×Ĺ",
+      "Ġ׾ק×ķ×Ĺ ×ķת",
+      "Ġ×Ľ×ª ×ķ×ijת",
+      "ĠÙĦ ÙĥÙħ",
+      "ب شر",
+      "Ġr Ãłng",
+      "Ġ×ŀ×Ķ ×ŀ",
+      "Ġ×IJ×Ĺר ×ķת",
+      "Ġб он",
+      "Ġбон ÑĥÑģ",
+      "ï½ Ĺ",
+      "à¹ģ ยà¸ģ",
+      "ãģĤãģªãģŁ ãģ®",
+      "ĠÑĥÑĩаÑģÑĤ ие",
+      "ĠE yl",
+      "ĠEyl ül",
+      "ĠçalÄ±ÅŁmalar ı",
+      "خ طر",
+      "ìĿ ½",
+      "à¸ģาร à¹ĥà¸Ĭà¹īà¸ĩาà¸Ļ",
+      "Ġана лиз",
+      "תק ×ij׾",
+      "ни ем",
+      "ĠÄ° ns",
+      "ĠÄ°ns an",
+      "ĠبÙĪ اس",
+      "ĠبÙĪاس طة",
+      "Ġ׳ ×Ľ×ł×¡",
+      "Ġ×Ķ×ŀ ×Ļ×ĵ×¢",
+      "Ġç o",
+      "Ġço ÄŁu",
+      "á» ĺ",
+      "ĠêµŃ 민",
+      "ãĤĤ ãģĦãģĦ",
+      "Ġ׼ ׾×Ļ",
+      "ĠÑģÑĢед не",
+      "g ÅĤo",
+      "gÅĤo ÅĽ",
+      "Ġneg ó",
+      "Ġnegó cio",
+      "ĠÑĢ егиÑģÑĤ",
+      "ĠÑĢегиÑģÑĤ ÑĢа",
+      "ĠÑĢегиÑģÑĤÑĢа ÑĨии",
+      "Ġtr á»ĵng",
+      "ĠпÑĢ Ñı",
+      "ĠпÑĢÑı мо",
+      "ëłĪ ìĿ´",
+      "Ġk ém",
+      "к ле",
+      "à¸Ļำ มา",
+      "ĠÑĦ ин",
+      "ĠÑĦин анÑģ",
+      "ĠÑĦинанÑģ ов",
+      "Ġki á»ĩm",
+      "ยัà¸ĩ à¹Ħ",
+      "ยัà¸ĩà¹Ħ à¸ĩ",
+      "ย ิà¸ĩ",
+      "à¹Ĥ à¸Ľ",
+      "ĠполÑĥÑĩ ил",
+      "×Ļ×ĸ ×Ŀ",
+      "à¹ģละ à¸Ħวาม",
+      "Ġво обÑīе",
+      "ص ÙĬر",
+      "ãĥı ãĥ³",
+      "ĠاÙĦÙĤ اد",
+      "ĠاÙĦÙĤاد Ùħ",
+      "Ġب دÙĪÙĨ",
+      "ع ظÙħ",
+      "ת ׳×ķ×¢",
+      "×ª×ł×ķ×¢ ×Ķ",
+      "Ø£ ÙħÙĦ",
+      "ãģķ ãģĪ",
+      "ÑĤ ем",
+      "ÑĤем пеÑĢ",
+      "ÑĤемпеÑĢ аÑĤÑĥÑĢ",
+      "Ġ׾ ×Ļצ×ķר",
+      "Ġr ÄĻk",
+      "ر سÙĦ",
+      "ìŀIJ 를",
+      "Ġ×Ļצ ×Ļרת",
+      "ÙĨ بÙĬ",
+      "Ñĩ наÑı",
+      "تØŃ ÙĦÙĬÙĦ",
+      "Ġм ик",
+      "Ġмик ÑĢо",
+      "ĠS öz",
+      "Ġfor ça",
+      "Ñģ он",
+      "ĠاÙĦع را",
+      "ĠاÙĦعرا ÙĤÙĬ",
+      "ĠH á»ĵng",
+      "ãģĻãĤĭ ãģŁãĤģãģ«",
+      "à¸Ĺีà¹Ī à¸Ńยูà¹Ī",
+      "Ġ×ķ×IJ ×£",
+      "ص ÙĬد",
+      "ĠìķĬ ê³ł",
+      "ร ัà¸ĩ",
+      "ĠاÙĦت ÙĪاصÙĦ",
+      "à¹Ģม à¸ķร",
+      "Ñĥ ÑģÑĤÑĢой",
+      "ÑĥÑģÑĤÑĢой ÑģÑĤв",
+      "m ıyor",
+      "Ġبا سÙħ",
+      "Ġ×ķ ׼×ķ",
+      "ĠG ül",
+      "á» IJ",
+      "Ãī tat",
+      "غ اÙĦ",
+      "Ø¥ ÙĨØ´",
+      "Ø¥ÙĨØ´ اء",
+      "T Ä°",
+      "à¸Ĥà¹īา ม",
+      "Ġtro ch",
+      "Ġtroch ÄĻ",
+      "إ ص",
+      "إص ابة",
+      "ĠØ« اÙĨÙĬ",
+      "ĠاÙĦص ØŃØ©",
+      "Ġ×ĸ×Ķ ×ķ",
+      "jÄħ cej",
+      "ãĥĢ ãĥ³",
+      "ìĿ¸ ìĿ´",
+      "Ġв олоÑģ",
+      "ëIJĺ ë©´",
+      "Ġzak ÅĤad",
+      "ãģĻ ãģĵãģ¨",
+      "以ä¸Ĭ ãģ®",
+      "Ġ×Ķ×ŀק ×ķ×Ŀ",
+      "ÙħØ´ اÙĩ",
+      "ÙħشاÙĩ دة",
+      "Ñĩ ив",
+      "ب ش",
+      "ย à¹īาย",
+      "Ġsür dür",
+      "ĠN ẵ",
+      "ĠNẵ ng",
+      "ĠигÑĢ аÑĤÑĮ",
+      "Ġê·¸ëŁ¬ ë©´",
+      "ãĥķ ãĥ«",
+      "ล à¹Īะ",
+      "Ġtend rá",
+      "Ġb Ãły",
+      "à¹Ģà¸Ľà¹ĩà¸Ļ à¸ľà¸¹à¹ī",
+      "Ġok o",
+      "Ġoko ÅĤo",
+      "w ÅĤa",
+      "wÅĤa ÅĽci",
+      "wÅĤaÅĽci w",
+      "æĢĿ ãĤı",
+      "ĠYa ÅŁ",
+      "ĠB á»ĩnh",
+      "íı Ń",
+      "بÙĬ د",
+      "קר ף",
+      "à¹Ģศ ร",
+      "à¹Ģศร ษ",
+      "à¹Ģศรษ à¸IJ",
+      "à¹Ģศรษà¸IJ à¸ģิà¸Ī",
+      "ĠاÙĦØ£ ÙĪرÙĪ",
+      "ĠاÙĦØ£ÙĪرÙĪ بÙĬ",
+      "fl äche",
+      "ä¹Ĺ ãĤĬ",
+      "Ġb á»ģn",
+      "Ùĩ ب",
+      "æľĢ ãĤĤ",
+      "Ġsa ç",
+      "à¸Ńำ à¹Ģà¸ł",
+      "à¸Ńำà¹Ģà¸ł à¸Ń",
+      "ĠØ£ ج",
+      "ĠاÙĦد اخÙĦ",
+      "ĠاÙĦداخÙĦ ÙĬØ©",
+      "×ĺ ×ķ×ij",
+      "ãĤĤ ãģªãģı",
+      "Ġли ÑĨа",
+      "à¹ģลà¹īว à¸ģà¹ĩ",
+      "×ĸ׼ ×Ļר",
+      "Ġqu Ãł",
+      "ĠÙĥ Ø°ÙĦÙĥ",
+      "صØŃ Ùģ",
+      "ĠÃĤ u",
+      "ÙĪب ا",
+      "à¹Ģà¸Ľà¸¥à¸µà¹Īยà¸Ļ à¹ģà¸Ľà¸¥",
+      "à¹Ģà¸Ľà¸¥à¸µà¹Īยà¸Ļà¹ģà¸Ľà¸¥ à¸ĩ",
+      "à¸ķัว à¸Ńยà¹Īาà¸ĩ",
+      "Ġráp ida",
+      "Ġtas ar",
+      "Ġtasar ım",
+      "ĠعÙĦÙĬ ÙĩÙħ",
+      "ס ×ķ׾",
+      "c ılı",
+      "cılı k",
+      "Ġر غÙħ",
+      "ìĭľ íĤ¤",
+      "Ġ×IJ׾ ק",
+      "Ġ×IJ׾ק ×ĺר",
+      "Ġ×IJ׾ק×ĺר ×ķ׳×Ļ",
+      "à¹ģà¸ļ à¹Īà¸ĩ",
+      "Ġh ạng",
+      "ãģ£ãģ¦ ãģıãĤĮ",
+      "ĠÙĨ تÙĬ",
+      "ĠÙĨتÙĬ جة",
+      "ıkl ı",
+      "غ اÙĨ",
+      "à¸Ĥà¹īà¸Ń à¸Ħวาม",
+      "à¸Ľà¸¥ าย",
+      "ĠØ£ Ùħس",
+      "à¸Ĺีà¹Ī à¹Ģà¸ģีà¹Īยว",
+      "à¸Ĺีà¹Īà¹Ģà¸ģีà¹Īยว à¸Ĥ",
+      "à¸Ĺีà¹Īà¹Ģà¸ģีà¹Īยวà¸Ĥ à¹īà¸Ńà¸ĩ",
+      "Ġdé fin",
+      "Ġdéfin i",
+      "ÙģÙĨ اد",
+      "ÙģÙĨاد ÙĤ",
+      "à¹Ħà¸Ķà¹ī วà¹Īา",
+      "ãģªãģĦ ãĤĪãģĨãģ«",
+      "Ġpróp ria",
+      "ĠPh át",
+      "ãĤĦãģĻ ãģı",
+      "สวย à¸ĩาม",
+      "ê³ł ìļĶ",
+      "Ñı еÑĤ",
+      "ãģĭãĤĤãģĹãĤĮãģ¾ãģĽãĤĵ ãģĮ",
+      "تر جÙħ",
+      "ĠкÑĢаÑģ ив",
+      "Ġ×ŀ ר×IJש",
+      "д еж",
+      "ĠÙĬ ÙĪÙĨ",
+      "ĠÙĬÙĪÙĨ ÙĬÙĪ",
+      "Ñģк оÑĢ",
+      "ĠKas ım",
+      "ê³Ħ ìķ½",
+      "к оÑģ",
+      "Ġна ÑĢÑĥ",
+      "ĠнаÑĢÑĥ ÑĪен",
+      "Ġdu że",
+      "acc ès",
+      "Ġh á»ĵng",
+      "Ġv Å©",
+      "ãģĦãģŁ ãģĹãģ¾ãģĻ",
+      "Ġ×ĺ ×Ļ",
+      "Ġ×ĺ×Ļ ×ķ׾",
+      "lıkl arı",
+      "Ġqu ê",
+      "ëħ¸ ëıĻ",
+      "ìķ Ķ",
+      "CI ÃĵN",
+      "Ġt ắc",
+      "press ão",
+      "ĠìŀĪ ìľ¼",
+      "สิà¸Ĺà¸ĺิ à¹Į",
+      "íĥ Ħ",
+      "Ġ×Ķ×ŀ ×ŀש׾×Ķ",
+      "å¬ī ãģĹãģĦ",
+      "ĠÄIJ ặc",
+      "ÙĨ زÙĦ",
+      "ĠдÑĢÑĥг ой",
+      "д ÑĥÑĤ",
+      "ìĪ Ļ",
+      "Ġth ụ",
+      "à¹Ģส ร",
+      "à¹Ģสร à¹ĩ",
+      "à¹Ģสรà¹ĩ à¸Ī",
+      "Ġto plant",
+      "Ġtoplant ı",
+      "×IJ×ŀ ף",
+      "×ķ׾ ת",
+      "п омн",
+      "Ġyo ÄŁun",
+      "ÅĦsk iego",
+      "ì° ©",
+      "ĠØ« ÙĦاث",
+      "ĠØ«ÙĦاث Ø©",
+      "Ġl ắng",
+      "ë¦ ´",
+      "ราà¸Ĭ à¸ģาร",
+      "ĠÑģлов а",
+      "á» Ĩ",
+      "à¸Ķี à¸ģวà¹Īา",
+      "ãģĶãģĸ ãģĦãģ¾ãģĻ",
+      "Ġд из",
+      "Ġдиз айн",
+      "fé rence",
+      "lıkl ar",
+      "ãģªãĤĵ ãģ§ãģĻ",
+      "ajÄħ cy",
+      "Ġëĭ¤ ìĸij",
+      "Ġëĭ¤ìĸij íķľ",
+      "ק ×Ļר",
+      "ØŃ Ø§Ø±",
+      "ส ูà¹ī",
+      "Ġz ro",
+      "Ġzro bi",
+      "Ġzrobi Äĩ",
+      "×ŀ ×Ļ׼×Ķ",
+      "à¸Ĭà¹Īวย à¹Ģหลืà¸Ń",
+      "ĠÑįÑĤ Ñĥ",
+      "ë´ ī",
+      "楽 ãģĹãģĦ",
+      "س ÙĪر",
+      "íķĺ ê±°ëĤĺ",
+      "Ùħؤ تÙħر",
+      "Ġpoc zÄħ",
+      "ĠpoczÄħ tk",
+      "ĠpoczÄħtk u",
+      "Ġع ربÙĬ",
+      "اÙĦØ£ ر",
+      "اÙĦأر دÙĨ",
+      "à¸Ķ ร",
+      "Åĵ uvre",
+      "ĠÙĪÙĥ اÙĨت",
+      "ĠÅĽ redni",
+      "خ ضر",
+      "Ġch uyến",
+      "н ÑĤ",
+      "ĠìķĮ ê³ł",
+      "Ġv á»Ŀi",
+      "Ġ×ij ×Ļ×ĵ×Ļ",
+      "×ŀ×ĵ ×ķ×ijר",
+      "ÙĪ Ùģر",
+      "ÙĬ Ø¡",
+      "׳ ×Ľ×¡",
+      "ĠÐĽ а",
+      "л он",
+      "Ġx ấu",
+      "Ùģ ÙĬÙĨ",
+      "Ġfé vrier",
+      "ĠÐŀ на",
+      "ĠV á»ģ",
+      "ĠÅŁey ler",
+      "ĠполÑĥÑĩ ен",
+      "з ад",
+      "Ġn ét",
+      "à¹Ħà¸Ľ ยัà¸ĩ",
+      "×Ĺש×ij ×ķ",
+      "à¸ļัà¸Ļ à¸Ĺ",
+      "à¸ļัà¸Ļà¸Ĺ ึà¸ģ",
+      "Ġgerçek leÅŁ",
+      "иÑĩеÑģк ое",
+      "ìĪĺ ê°Ģ",
+      "ث بت",
+      "ãģ¤ ãģ¾ãĤĬ",
+      "ĠÑĥÑģловиÑı Ñħ",
+      "ëĭ¤ ê°Ģ",
+      "ราย à¹Ħà¸Ķà¹ī",
+      "׼×IJ ×ij",
+      "à¹Ĥà¸Ľà¸£ à¹Ĥม",
+      "à¹Ĥà¸Ľà¸£à¹Ĥม à¸Ĭัà¹Īà¸Ļ",
+      "j ähr",
+      "jähr ige",
+      "ק ׳×Ļ×Ŀ",
+      "×ŀ ×ķק",
+      "×ŀ×ķק ×ĵ",
+      "ãģ«è¡Į ãģ£ãģ¦",
+      "Ø¢ ÙĦ",
+      "вед ение",
+      "Ġ׾ ×Ľ×ª×ķ×ij",
+      "جÙħ Ùĩ",
+      "جÙħÙĩ ÙĪرÙĬØ©",
+      "à¸ī à¸ļ",
+      "à¸īà¸ļ ัà¸ļ",
+      "ĠC òn",
+      "à¸ľ สม",
+      "ãģªãģ© ãģĮ",
+      "×IJ×Ķ ×ij",
+      "ĠдейÑģÑĤв иÑı",
+      "y ız",
+      "à¹Ħมà¹Ī à¹Ģà¸Ħย",
+      "ج ÙĪز",
+      "×Ķ×Ĺ׾×ĺ ×Ķ",
+      "f ällt",
+      "ãĥĵ ãĤ¸",
+      "ãĥĵãĤ¸ ãĥį",
+      "ãĥĵãĤ¸ãĥį ãĤ¹",
+      "Ġ×IJ ×Ļ׳×Ŀ",
+      "ĠнаÑħод иÑĤÑģÑı",
+      "Ġdzi ÅĽ",
+      "ست Ø·ÙĬع",
+      "׾ ×Ļף",
+      "Ø® ÙĦاÙģ",
+      "Ùĩ ÙIJ",
+      "Ġatr ás",
+      "íĺ ģ",
+      "ãĤĴ ãģĶ",
+      "Ġ×Ķ×ŀ ×ķצר",
+      "ĠBakan lıģı",
+      "ÑİÑī ее",
+      "ÙħÙĨ اط",
+      "ÙħÙĨاط ÙĤ",
+      "Ùģ د",
+      "à¸Ļำ à¹Ħà¸Ľ",
+      "Ġв аж",
+      "Ġваж но",
+      "Ġm ạch",
+      "׼ ׳×ķ",
+      "بع ث",
+      "lan ması",
+      "Ġa yr",
+      "Ġayr ıl",
+      "ìĤ¬ íļĮ",
+      "d ÃŃa",
+      "p ÅĤyw",
+      "اÙħ ÙĬØ©",
+      "íĺ ľ",
+      "×IJ׳ ×Ĵ׾",
+      "×IJ׳×Ĵ׾ ×Ļת",
+      "ĠìŀĪëĭ¤ ëĬĶ",
+      "Ġس اعة",
+      "ĠëĤĺ íĥĢ",
+      "b ö",
+      "à¸Ħ ัà¸Ļ",
+      "ĠdziaÅĤ ania",
+      "Ø© Ùĭ",
+      "Ġng Å©",
+      "׳צ ×Ĺ",
+      "ãģ¯ ãģĤãĤĭ",
+      "ĠyaÅŁ ında",
+      "st ück",
+      "car acter",
+      "caracter ÃŃsticas",
+      "Ġr á»Ńa",
+      "ĠÙħختÙĦÙģ Ø©",
+      "ãģ«ãģĬ ãģijãĤĭ",
+      "à¹ģà¸ŀ à¸ĩ",
+      "วิ à¹Īà¸ĩ",
+      "ת פ×ķ",
+      "سا ÙĩÙħ",
+      "使 ãģĨ",
+      "Ùĥ رÙĬ",
+      "×IJ פ×Ļ",
+      "........ .......",
+      "ĠÑĤак им",
+      "×Ļ׼ ×ķ×Ļ",
+      "Ø´ بÙĩ",
+      "ج ÙĬر",
+      "ãģĿãģ® ãģ¾ãģ¾",
+      "ac jÄĻ",
+      "ĠاÙĦت رÙĥ",
+      "ĠاÙĦترÙĥ ÙĬ",
+      "ĠпÑĢав илÑĮно",
+      "Ġت عÙħÙĦ",
+      "à¸ģล à¹īา",
+      "Ġbi ên",
+      "Ġ×ij׳×Ļ ×Ļת",
+      "Ġкл Ñĥб",
+      "Ġ×ŀ ש×Ķ",
+      "в ÑĪий",
+      "ãģĵãģ¨ãģĮãģ§ãģį ãĤĭ",
+      "à¸ŀัà¸Ļà¸ĺ ุ",
+      "à¸ŀัà¸Ļà¸ĺุ à¹Į",
+      "ר ×ķ×Ŀ",
+      "ĠاÙĦÙģ رÙĨ",
+      "ĠاÙĦÙģرÙĨ سÙĬ",
+      "à¹Ģà¸Ľà¹ĩà¸Ļ à¸Ħà¸Ļ",
+      "ãģĹãģ¦ ãģĬãĤĬ",
+      "Ġth ầy",
+      "ãĤĵ ãģłãģijãģ©",
+      "ìĶ ¨",
+      "Ùħ دÙĨ",
+      "ت ÙĪÙĨ",
+      "ĠмеÑĤ ал",
+      "ĠмеÑĤал л",
+      "Ġin ÃŃcio",
+      "à¸Ńà¸Ńà¸ģ à¸Īาà¸ģ",
+      "ëĴ ¤",
+      "Ġcu á»ijn",
+      "Ġbu á»Ļc",
+      "ÙĨ سÙĬ",
+      "ä cht",
+      "×ŀ ×Ļ׳×Ļ×Ŀ",
+      "ãģķ ãģ¦",
+      "ãģĮ ãģ§ãģį",
+      "ÑĬ ем",
+      "Ġtá i",
+      "ĠЧ ÑĤ",
+      "ĠЧÑĤ обÑĭ",
+      "à¸Ľà¸¥ ูà¸ģ",
+      "à¸Ĭุม à¸Ĭà¸Ļ",
+      "н Ñģкий",
+      "Ġv ững",
+      "Ġ×Ķ ׾×ij",
+      "ë le",
+      "Ġש ×¢×ijר",
+      "в аÑĤÑĮÑģÑı",
+      "б ой",
+      "ع ÙĪÙĨ",
+      "à¹ģà¸Ķ à¸Ļ",
+      "Ġספר ×Ļ×Ŀ",
+      "Ġt uyên",
+      "Ġnhi êu",
+      "ĠQu ý",
+      "Ġh uyết",
+      "ãĤı ãģĭãĤīãģªãģĦ",
+      "Ġ×ŀ ׼ף",
+      "Ġ×Ķ ק׾",
+      "Ġ׾×IJ ×ķר",
+      "ĠÄIJi á»ĩn",
+      "ش ؤ",
+      "شؤ ÙĪÙĨ",
+      "Ġ×ŀ׊פש",
+      "ĠпоÑģÑĤоÑıн но",
+      "×ŀ ×Ļר",
+      "ìħ Ķ",
+      "Ðŀ Ñģ",
+      "ÐŀÑģ нов",
+      "×ĸ ×Ļת",
+      "ĠH á",
+      "ĠÑĩаÑģ ов",
+      "×IJ ×ķ׾×Ļ",
+      "Ġm át",
+      "Ø® رÙĪ",
+      "خرÙĪ ج",
+      "ÙĤ ضا",
+      "ÙĤضا ÙĬا",
+      "à¹Ģà¸Ľ à¸Ńรà¹Į",
+      "ĠÙĬ ÙĪÙĦ",
+      "ĠÙĬÙĪÙĦ ÙĬÙĪ",
+      "à¹Ĥà¸Ĺ ษ",
+      "׳ פ׾",
+      "ת ×ķש",
+      "ת×ķש ×ij×Ļ",
+      "Ġv ários",
+      "×ŀ ר×IJ×Ķ",
+      "ëĿ¼ ìĿ´",
+      "ÙĨ غ",
+      "×ij צע",
+      "г он",
+      "ĠÄIJ ược",
+      "ع Ùı",
+      "пÑĥÑģ к",
+      "ĠÙĪاÙĦ Ùģ",
+      "üc ü",
+      "×Ļק ×Ļ×Ŀ",
+      "Ġس بÙĬÙĦ",
+      "׾×ij ף",
+      "ĠاÙĦÙĤ رÙĨ",
+      "ס ×ķת",
+      "ĠQu áºŃn",
+      "ãģĵãĤĮ ãģĮ",
+      "ãĥĸ ãĥ©ãĥ³ãĥī",
+      "×Ĵ ×ŀר",
+      "Ġwarto ÅĽci",
+      "ĠÙĪب ÙĬÙĨ",
+      "Ġd ạ",
+      "ÐIJ в",
+      "ÐIJв ÑĤо",
+      "Ġol acaktır",
+      "à¸Ļ à¸Ĺà¹Į",
+      "Ùħ طار",
+      "Ġ×¢ ק×ij",
+      "Ġת פ",
+      "ãģĹãģ¦ ãģĦãģ¦",
+      "צ ×ŀ×Ĺ",
+      "à¸Ī à¸Ńà¸ĩ",
+      "Ġö de",
+      "ìį ¨",
+      "ÙĨ اس",
+      "調 ãģ¹",
+      "ĠогÑĢ омн",
+      "ë³´ íĹĺ",
+      "×ĺ ק",
+      "×ĺק ס×ĺ",
+      "ĠbaÅŁ v",
+      "ĠbaÅŁv uru",
+      "Ġpom ys",
+      "Ġpomys ÅĤ",
+      "ãģ« ä¹Ĺ",
+      "Ġש ׼ף",
+      "ĠاÙĦÙħس ؤÙĪÙĦ",
+      "Ġз ан",
+      "Ġзан ÑıÑĤ",
+      "Ġd Æ°Æ¡ng",
+      "ãĥĹãĥ¬ ãĤ¤",
+      "ล à¸ļ",
+      "ÑĤи ка",
+      "ĠAr alık",
+      "Ġнед о",
+      "Ġm á»Ļ",
+      "Ġor an",
+      "Ġoran ı",
+      "Ġktó r",
+      "Ġktór Äħ",
+      "Ġ×Ķ×IJ×Ĺר ×ķ׳×ķת",
+      "ائ ÙĨ",
+      "ÅĦ s",
+      "ÅĦs ka",
+      "åĽ½ ãģ®",
+      "×ŀ ×ĺ×Ļ",
+      "ĠвопÑĢоÑģ Ñĭ",
+      "à¸Ńà¸ĩà¸Ħà¹Į à¸ģร",
+      "×ŀ ×ķצ×IJ",
+      "Ġpó ź",
+      "Ġpóź niej",
+      "ש×ŀ ×IJ׾",
+      "Ġk aps",
+      "Ġkaps am",
+      "Ġkapsam ında",
+      "Ġmá quina",
+      "ĠÅĽwie cie",
+      "Ġho Ãłng",
+      "Ġöz gü",
+      "×Ĵ×ķר ×Ŀ",
+      "ãģĤ ãģŁãĤĬ",
+      "à¸ķัà¸Ķ สิà¸Ļ",
+      "à¸ķัà¸Ķสิà¸Ļ à¹ĥà¸Ī",
+      "б ÑĢи",
+      "ãģ«ãģªãĤĭ ãģ¨",
+      "ت ÙĥÙĪÙĨ",
+      "Ġ×ķ×Ķ ×Ļ×IJ",
+      "Ġchi ếu",
+      "ÑģÑĤан ав",
+      "ÑģÑĤанав ли",
+      "ÑģÑĤанавли ва",
+      "×ŀ ×ķ×Ĵ",
+      "c ité",
+      "ĠK örper",
+      "Ġש ×Ĵ×Ŀ",
+      "ع ظ",
+      "عظ ÙĬÙħ",
+      "Ġ×Ķ×IJ ×Ļש×Ļ",
+      "Ġmat ière",
+      "ĠÙģ ÙĪÙĤ",
+      "Ġk to",
+      "Ġkto ÅĽ",
+      "à¸Ļ à¹Ĥย",
+      "à¸Ļà¹Ĥย à¸ļาย",
+      "å¾ħ ãģ¡",
+      "à¹Ģม à¸Ļ",
+      "à¹Ģมà¸Ļ ู",
+      "A ÃĩÃĥO",
+      "Ġt ù",
+      "Ġtù y",
+      "ãĥĪ ãĥ³",
+      "ĠоÑĤ каз",
+      "Ġ×ŀ ×ķצר",
+      "ül ü",
+      "ãģķãĤĵ ãģ«",
+      "Ġ×Ĺ ×ķ×ij",
+      "קר ×Ļ×IJ×Ķ",
+      "ĠاÙĦØ® دÙħات",
+      "ĠÙĦÙħ دة",
+      "ر ؤ",
+      "رؤ ÙĬØ©",
+      "ãĤĴè¦ĭ ãģ¤ãģij",
+      "à¸Ł า",
+      "Ġréuss i",
+      "à¸Ļัà¸ģ à¹Ģรียà¸Ļ",
+      "ĠÑĩиÑģ л",
+      "à¸ģาร à¹Ģลà¹Īà¸Ļ",
+      "Ġhaz ırl",
+      "Ġhazırl an",
+      "ĠпеÑĢв Ñĭй",
+      "ли м",
+      "ĠоÑĤзÑĭв Ñĭ",
+      "Ġwy jÄħ",
+      "ĠwyjÄħ tk",
+      "ĠØ£ ÙĤÙĦ",
+      "ס ×ļ",
+      "Ġê²° ìłķ",
+      "Ġ׾×ŀ×¢ ש×Ķ",
+      "Ġl ắp",
+      "à¹ģà¸ļ ร",
+      "à¹ģà¸ļร à¸Ļà¸Ķà¹Į",
+      "วà¹Īา à¹Ģà¸Ľà¹ĩà¸Ļ",
+      "Ġب دا",
+      "Ġبدا ÙĬØ©",
+      "ãģ¨ãģĦãģĨ ãģ®ãģĮ",
+      "иÑĩеÑģк им",
+      "à¸ģาร à¸ŀัà¸Ĵà¸Ļา",
+      "Ġb Ãło",
+      "Ġmia ÅĤa",
+      "y waÄĩ",
+      "ĠMär z",
+      "ĠÙĨ سبة",
+      "Ġéconom ique",
+      "×ĸ ×ŀ",
+      "×ĸ×ŀ ׳×Ļ×Ŀ",
+      "æŃ¢ ãĤģ",
+      "Ġt ủ",
+      "íķĺ ìĭł",
+      "Ġkażde go",
+      "stra ÃŁe",
+      "à¸Ĭ ีà¹ī",
+      "à¹Ģ à¸ļา",
+      "ÑĢеÑģ ÑĥÑĢÑģ",
+      "ев ой",
+      "ش باب",
+      "à¸ķà¹Īาà¸ĩ à¸Ľà¸£à¸°à¹Ģà¸Ĺศ",
+      "Ġ×IJ ×Ļש",
+      "Ġ×IJ×Ļש ×Ļת",
+      "×Ļ ×ķפ",
+      "×Ļ×ķפ ×Ļ",
+      "ĠìļĶ 구",
+      "ì¡° ìĤ¬",
+      "ãģ£ãģŁ ãĤī",
+      "׾ ×Ļק",
+      "миниÑģÑĤ ÑĢ",
+      "ãĤĤãģ® ãģ¯",
+      "Ġl Æ°Æ¡ng",
+      "Ġна и",
+      "Ġнаи бол",
+      "Ġнаибол ее",
+      "íİ ĺ",
+      "à¹ģà¸ŀ à¹ī",
+      "ãĤŃ ãĥ¥",
+      "ĠкоÑĤоÑĢ Ñĭм",
+      "à¹ģà¸Ĺ à¸ĩ",
+      "à¹ģà¸Ĺà¸ĩ à¸ļà¸Ńล",
+      "Ġ׳ ×Ļ×Ķ",
+      "Ġ׳×Ļ×Ķ ×ķ׾",
+      "âĤ ª",
+      "ĠGi ải",
+      "ĠиÑģполÑĮзов а",
+      "ëł¥ ìĿĦ",
+      "ãģĹãģĭ ãĤĤ",
+      "à¸ģà¹ĩ à¸ķà¹īà¸Ńà¸ĩ",
+      "ĠÑĢ еб",
+      "ĠÑĢеб ен",
+      "ĠÑĢебен ка",
+      "ت ÙĪاصÙĦ",
+      "ãĤ°ãĥ« ãĥ¼ãĥĹ",
+      "ãĤĦ ãĤī",
+      "à¹Ģà¸Ľà¸´à¸Ķ à¸ķัว",
+      "б ÑĢо",
+      "ë°ĸ ìĹIJ",
+      "ÙĨ Ùİا",
+      "×Ķ ×Ĵ",
+      "×Ķ×Ĵ ׳×Ķ",
+      "à¸Ĺ รั",
+      "à¸Ĺรั à¸ŀ",
+      "à¸Ĺรัà¸ŀ ยà¹Į",
+      "Ġkh á»iji",
+      "עצ ×ŀ×ķ",
+      "бол езн",
+      "Ġë°Ľ ìķĦ",
+      "ม à¸Ļ",
+      "มà¸Ļ ุ",
+      "มà¸Ļุ ษ",
+      "มà¸Ļุษ ยà¹Į",
+      "âĹ Ĩ",
+      "×ŀ צ׾×Ļ×Ĺ",
+      "Ñıв ление",
+      "Ùħ Ø·ÙĦ",
+      "ÙħØ·ÙĦ ÙĪب",
+      "Ø® اÙĦÙģ",
+      "ت ÙĪÙĤÙģ",
+      "ãģ§ãģį ãģ¾ãģĽãĤĵ",
+      "оÑģÑĤ ей",
+      "м еÑĩа",
+      "기 ëĬĶ",
+      "תש ע",
+      "ص ÙĬب",
+      "Ġ×ij×¢ ×ķ×ĵ",
+      "à¸Ĥà¸Ńà¸ĩ à¹Ģà¸Ĥา",
+      "ÑĤÑı ж",
+      "ĠÑĥ пÑĢав",
+      "ĠÑĥпÑĢав лениÑı",
+      "Ġgén ér",
+      "Ġth ÃŃ",
+      "פ ×ļ",
+      "Ġر Ùħض",
+      "ĠرÙħض اÙĨ",
+      "Ġtr uyá»ĩn",
+      "إ عداد",
+      "ãĤµ ãĥĿãĥ¼ãĥĪ",
+      "Ġпол но",
+      "Ø® اÙħ",
+      "ÐŁ еÑĤ",
+      "ÐŁÐµÑĤ еÑĢ",
+      "ÐŁÐµÑĤеÑĢ бÑĥÑĢ",
+      "ÐŁÐµÑĤеÑĢбÑĥÑĢ г",
+      "ÙħÙĨت دÙī",
+      "ãģķãĤĮ ãģ¾ãģĹãģŁ",
+      "ĠëĮĢ íķĺìŬ",
+      "à¸ľà¸¹à¹ī à¸Ĺีà¹Ī",
+      "Ġ×ŀ×IJ ×ķ",
+      "׾ ׳×ĵ",
+      "оÑĩ нÑĭе",
+      "ĠнаÑĩ ала",
+      "Ġ׾ ×Ļ׾×ĵ×Ļ×Ŀ",
+      "ов ое",
+      "ãģĻãĤĭãģĵãģ¨ ãģ§",
+      "ĠاÙĦÙĨ Ùģ",
+      "ĠاÙĦÙĨÙģ Ø·",
+      "ìŀĪ ëĬĶ",
+      "غ ÙĨÙĬ",
+      "פ ×ĵ",
+      "ãĤ ¾",
+      "ĠCr é",
+      "ãģ© ãģ¡ãĤī",
+      "Ø« اÙĨ",
+      "ÑĢаб аÑĤ",
+      "ÑĢабаÑĤ Ñĭва",
+      "Ġê°Ļ ëĭ¤",
+      "à¸Ī ั",
+      "à¸Īั à¸ģร",
+      "Ġch ụ",
+      "Ġchụ p",
+      "Ġм аÑģÑĤ",
+      "ĠмаÑģÑĤ еÑĢ",
+      "Ġn ắm",
+      "ĠÑģÑĤ али",
+      "Ġ×Ķ×IJ ×Ļר×ķ×¢",
+      "ãĤ½ ãĥ³",
+      "åĪĨ ãģĭãĤĬ",
+      "ط بع",
+      "بد ا",
+      "gr áfico",
+      "г еÑĢ",
+      "à¸Ķำà¹Ģà¸Ļิà¸Ļ à¸ģาร",
+      "Ġsal dır",
+      "Ġsaldır ı",
+      "в ÑĪиÑħ",
+      "ãģĭãģ£ãģŁ ãģ§ãģĻ",
+      "Ġyapı yor",
+      "ĠاÙĦÙģ ت",
+      "צר פת",
+      "з доÑĢов",
+      "×ij×¢ ׾",
+      "Ġ×IJ ×ŀ×Ļת×Ļ",
+      "Ġоб Ñĭ",
+      "ĠобÑĭ Ñĩ",
+      "ĠобÑĭÑĩ но",
+      "Ġ׾ ×ķ×ŀר",
+      "ت ÙĥÙĨ",
+      "تÙĥÙĨ ÙĪÙĦÙĪج",
+      "تÙĥÙĨÙĪÙĦÙĪج ÙĬا",
+      "Ġhakk ı",
+      "ĠÑĢаР²",
+      "ĠÑĢав но",
+      "رÙĬ Ùĥ",
+      "Ġ×ij ×ŀ×Ļ×ĵ",
+      "Ġ×ij×ŀ×Ļ×ĵ ×Ķ",
+      "à¹ģà¸ģ à¹īว",
+      "Ġìĸ ĺ",
+      "Ġìĸĺ 기",
+      "ãģĹãģ¦ ãģĦãģ¾ãģĹãģŁ",
+      "Ġkı sm",
+      "Ġkısm ı",
+      "ê± ¸",
+      "åĨħ ãģ®",
+      "ì§ ķ",
+      "à¹Ģหมืà¸Ńà¸Ļ à¸ģัà¸Ļ",
+      "ĠÙģ ÙIJ",
+      "ĠÙģÙIJ ÙĬ",
+      "ÙĤ اعدة",
+      "Ġmoż esz",
+      "Ùħ صاÙĦ",
+      "ÙħصاÙĦ ØŃ",
+      "ãģ¾ãģŁ ãģ¯",
+      "б ег",
+      "Ġs ıc",
+      "Ġsıc ak",
+      "Ñĩ иÑģ",
+      "ÑĩиÑģ лен",
+      "Ġн ог",
+      "ãĥģãĥ£ ãĥ³",
+      "ãĥ« ãĥī",
+      "Ġgi ó",
+      "Ġs ını",
+      "Ġsını f",
+      "ив аÑĤÑĮ",
+      "Ġqu ên",
+      "Ġì łģ",
+      "Ġìłģ ìļ©",
+      "ĠJo ão",
+      "Ùģ اد",
+      "ĠGl ück",
+      "à¸Ĺ à¸Ńà¸Ķ",
+      "Ġg ói",
+      "ï¼ Ĭ",
+      "Ġdé tail",
+      "ĠدÙĬ سÙħ",
+      "ĠدÙĬسÙħ بر",
+      "ë¡ľ ìĦľ",
+      "×ŀ ×ķ×Ĺ",
+      "à¹Ħ ฮ",
+      "ĠоÑĤ д",
+      "ĠоÑĤд ÑĭÑħ",
+      "Ġkh uyến",
+      "à¸Ħ à¸Ńย",
+      "Ġج ÙĨÙĬ",
+      "ĠجÙĨÙĬ Ùĩ",
+      "ĠاÙĦد Ùģاع",
+      "à¸Ļà¹īำ หà¸Ļัà¸ģ",
+      "ĠìĤ¬ëŀĮ ëĵ¤ìĿ´",
+      "Ġth ừa",
+      "ĠÃ¶ÄŁrenc i",
+      "ĠпомоÑī и",
+      "ĠczÄĻ ÅĽÄĩ",
+      "ש ×ĺר",
+      "ĠN hi",
+      "ĠNhi á»ģu",
+      "׳ צ×Ļ",
+      "ĠнаÑĪ ем",
+      "ĠkarÅŁÄ± laÅŁ",
+      "Ġ×Ķש ׳×Ļ×Ŀ",
+      "ĠÄIJ Æ°á»Ŀng",
+      "Ġtr ú",
+      "ĠÑĢазлиÑĩ нÑĭÑħ",
+      "ĠاÙĦØ´ Ùĩر",
+      "Ġ×ľ×¢ ×ķ׾×Ŀ",
+      "ØŃ Ø¬Ø±",
+      "ĠÄij á»ķ",
+      "ĠìĿĺ íķ´",
+      "à¸ļ à¹Īà¸Ńย",
+      "Ġ×Ķ ×Ļ׾×ĵ",
+      "ãģ¨ãģª ãģ£ãģŁ",
+      "Ġ×Ĺ×ķ ×ķת",
+      "Ġש×Ļר×ķת ×Ļ",
+      "Äħ cy",
+      "س رÙĬ",
+      "K Ä°",
+      "פ ׳×ķ",
+      "ÑģÑĤÑĢÑĥк ÑĤÑĥÑĢ",
+      "ÑĤ ÑĢÑĥд",
+      "Ġ×Ķ קר",
+      "Ġ×Ķקר ×ķ×ij",
+      "Ġth áºŃm",
+      "èģŀ ãģį",
+      "ÙĤÙĪ ÙĬ",
+      "клÑİÑĩ ен",
+      "ÑĤе Ñħ",
+      "ÑĤеÑħ нолог",
+      "è¡Į ãģ£ãģŁ",
+      "Ġ×ķ×IJ ×Ļף",
+      "ĠÅŁek lin",
+      "ĠÅŁeklin de",
+      "r ô",
+      "ÑĢ ог",
+      "Ġнов Ñĭе",
+      "Ġס ×ij×Ļ×ij",
+      "Ġtecn ologÃŃa",
+      "ס ׼",
+      "×¡×Ľ ×ķ×Ŀ",
+      "ĠÅŀ ub",
+      "ĠÅŀub at",
+      "Ġ×Ķ×ŀ ׾×IJ",
+      "Ġwy pos",
+      "Ġwypos aż",
+      "ãģ¯ ä½ķ",
+      "ãĤ¬ ãĥ³",
+      "ê° ĸ",
+      "Ġкак ие",
+      "Ġçocuk lar",
+      "Ġ׾צ ×ĵ",
+      "Ġkay ıt",
+      "ĠмеÑģÑĤ е",
+      "Ùħ دÙĬÙĨØ©",
+      "Ġ׼ ×Ĵ",
+      "Ġ׼×Ĵ ×ķף",
+      "ãģĹãģ¦ ãĤĭ",
+      "ĠÙħا ÙĬÙĪ",
+      "ãģ£ãģ¦ãģĹãģ¾ ãģ£ãģŁ",
+      "ĠпÑĢогÑĢамм Ñĭ",
+      "à¹ģล à¸Ļà¸Ķà¹Į",
+      "ãĥ¯ ãĤ¤",
+      "ער ×ķ×¥",
+      "Ñģ ид",
+      "ĠB öyle",
+      "Ġì²ĺ ìĿĮ",
+      "Ġת פק×Ļ×ĵ",
+      "ĠTr ên",
+      "íĥ Ī",
+      "ĠÐłÐ¾ÑģÑģ ий",
+      "ĠÐłÐ¾ÑģÑģий Ñģкой",
+      "Ġs Ãłn",
+      "Ġrè gle",
+      "ĠyaklaÅŁ ık",
+      "à¹Ģล ิà¸ģ",
+      "Ġد ائÙħ",
+      "Ġ×ķ ×Ĵ",
+      "اب ر",
+      "Ġb è",
+      "ĠاÙĦ ÙĤدÙħ",
+      "ĠÑĢеÑĪ ениÑı",
+      "hi ên",
+      "ÑĤи к",
+      "Ä Ħ",
+      "à¸ļรร ยาà¸ģ",
+      "à¸ļรรยาà¸ģ าศ",
+      "רצ ×ķף",
+      "åĭķ ãģį",
+      "ĠGä ste",
+      "Ġ기 본",
+      "ĠÙĬ عرÙģ",
+      "ĠS á»Ń",
+      "gÅĤ ÄĻb",
+      "à¹Ģà¸Ń ส",
+      "×IJ×ŀ ×Ļף",
+      "Ġп Ñĥнк",
+      "ĠпÑĥнк ÑĤ",
+      "Ġ×Ļ×ķ×ĵ ×¢×Ļ×Ŀ",
+      "ãĤ« ãĥ©ãĥ¼",
+      "Ġ×ijס ×ĵר",
+      "Ġbu á»ĵn",
+      "й ÑĤ",
+      "йÑĤ еÑģÑĮ",
+      "ãĤĴ æ±ĤãĤģ",
+      "Ġ×IJת ׼×Ŀ",
+      "Ġ모 르",
+      "ظ رÙĪÙģ",
+      "Ñĩ еÑģÑĤво",
+      "ìĸ´ ìĦľ",
+      "Ġод на",
+      "Ġkap ı",
+      "Ġëħ¸ ëł¥",
+      "ĠKü che",
+      "ĠاÙĦت Ø´",
+      "Ø· ÙĬب",
+      "ĠíĬ¹ íŀĪ",
+      "ĠвÑĭп ÑĥÑģ",
+      "ĠвÑĭпÑĥÑģ к",
+      "×ĵ ת×Ļ",
+      "Ġu ÄŁ",
+      "ĠuÄŁ ra",
+      "ائ Ùĩا",
+      "Ġtho át",
+      "ãģª ãĤĤãģ®",
+      "Ñij ÑĢ",
+      "기 ê°Ģ",
+      "ĠgeliÅŁ me",
+      "تØŃ ÙĤ",
+      "تØŃÙĤ ÙĤ",
+      "Ġоп аÑģ",
+      "б ÑĢоÑģ",
+      "ห ุ",
+      "หุ à¹īà¸Ļ",
+      "ì¼ Ģ",
+      "ãĤ¹ ãĥŀ",
+      "ãĤ¹ãĥŀ ãĥĽ",
+      "Ø£ Ùģر",
+      "Ø£Ùģر اد",
+      "ĠTh á»±c",
+      "Ġth ắ",
+      "ãĥªãĥ³ ãĤ¯",
+      "Ġni á»ģm",
+      "ĠHö he",
+      "عÙħ ار",
+      "ÙĥÙĪر ÙĪÙĨ",
+      "ÙĥÙĪرÙĪÙĨ ا",
+      "ĠÄIJ ến",
+      "ĠÑģам ом",
+      "ĠÑĤ еле",
+      "ĠÄijo án",
+      "à¸Ħวามà¸Ħิà¸Ķ à¹Ģหà¹ĩà¸Ļ",
+      "Ġд иÑģк",
+      "Ø£ Ø·ÙģاÙĦ",
+      "ม ารà¹Į",
+      "à¸Ĺ หาร",
+      "à¸Ĺ à¸Ļ",
+      "Ġب عÙĬد",
+      "ĠاÙĦÙĩ ÙĨد",
+      "åĩº ãģĹãģ¦",
+      "Ġkar de",
+      "Ġkarde ÅŁ",
+      "×Ķ×Ļס×ĺ ×ķר",
+      "×Ķ×Ļס×ĺ×ķר ×Ļ×Ķ",
+      "éģ¸ ãģ³",
+      "ع اÙħÙĦ",
+      "à¸Ĥ ยาย",
+      "Ġtü rl",
+      "Ġtürl ü",
+      "ĠìĿ¼ ìĿ´",
+      "Ġmaté ria",
+      "Ġ׼׾ ×ķ×ŀר",
+      "ãĥģãĥ£ ãĥ¼",
+      "جÙħ اعة",
+      "ĠÑģво им",
+      "Ø¥ÙĤ اÙħØ©",
+      "ä¾ĭ ãģĪãģ°",
+      "س اب",
+      "آ خر",
+      "ÙĤ دÙĬر",
+      "×IJ×ŀ ×Ļ",
+      "ìĸ »",
+      "Ġ׳×ķס פת",
+      "ĠÐĴ лад",
+      "ĠÐĴлад им",
+      "ĠÐĴладим иÑĢ",
+      "Ġest ará",
+      "ãģĵãģĨ ãģĦãģĨ",
+      "ãĤĴ 使çĶ¨",
+      "มา à¸ķร",
+      "มาà¸ķร à¸IJาà¸Ļ",
+      "ãģ£ãģ ½",
+      "Ġn ú",
+      "Ġnú i",
+      "ย าà¸ĩ",
+      "ĠاÙĦج ÙĨس",
+      "Ġüst ün",
+      "ëľ »",
+      "ãĤ» ãĥ«",
+      "ãģ¦ãģĦ ãģįãģ¾ãģĻ",
+      "Ġ×Ĺ ×ķ×ĸ",
+      "Ġ×Ĺ×ķ×ĸ ר",
+      "ĠÐĵ лав",
+      "à¹Ĥà¸Ĭ à¸Ħ",
+      "íı IJ",
+      "ÙĨت ظر",
+      "Ġ×Ĵ ×ij×Ļ",
+      "ع ÙĤب",
+      "int ér",
+      "intér êt",
+      "×ŀ פ×Ĵ",
+      "×ŀפ×Ĵ ש",
+      "Ġth ù",
+      "اÙģ ت",
+      "Ġ×ŀש פ",
+      "Ġ×ŀשפ ×ĺ×Ļ",
+      "ĠÙħ ÙĪاÙĤع",
+      "è¦ ļ",
+      "è¦ļ ãģĪ",
+      "×ĵ ×Ļף",
+      "à¹Ģรืà¹Īà¸Ńà¸ĩ ราว",
+      "ãģ¾ ãģĤ",
+      "Ġgh ế",
+      "иÑĢÑĥ ÑİÑĤ",
+      "à¸ģ ว",
+      "à¸ģว à¹īาà¸ĩ",
+      "Ġпов еÑĢ",
+      "ĠповеÑĢ Ñħ",
+      "ĠповеÑĢÑħ ноÑģÑĤ",
+      "׳ ×ĵר",
+      "Ġкон ÑĨе",
+      "Ġдолж на",
+      "Ġ×Ļש ×Ļר",
+      "acaģı z",
+      "ìĹ Ķ",
+      "Ġn ÃŃvel",
+      "Ġö r",
+      "Ġör nek",
+      "Ùĥ Ùģ",
+      "ĠФедеÑĢ аÑĨии",
+      "Ġ구 ìĦ±",
+      "หัว à¹ĥà¸Ī",
+      "ĠV áºŃy",
+      "м ед",
+      "мед и",
+      "меди ÑĨин",
+      "медиÑĨин Ñģк",
+      "از ÙĬ",
+      "×Ĵ×ij ×ķ׾",
+      "ÑĦ ÑĢ",
+      "Ġzus ätzlich",
+      "à¸ģ à¸ģ",
+      "ĠاÙĦاÙĤتصاد ÙĬØ©",
+      "Ġh è",
+      "lu ÄŁun",
+      "ج Ùİ",
+      "à¹Ħà¸Ł ลà¹Į",
+      "ÄIJ T",
+      "ãģĿãģ® ä»ĸ",
+      "à¸Ĺิ à¹īà¸ĩ",
+      "ĠاÙĦØ£ ÙĪ",
+      "ر سÙħ",
+      "æ°Ĺ ãģ¥",
+      "ìĿ´ ë©°",
+      "ÑĮ ев",
+      "ص ط",
+      "ĠاÙĦاست Ø«",
+      "ĠاÙĦاستث Ùħار",
+      "à¸Ńา à¸Ħาร",
+      "ĠÑĤоÑĩ но",
+      "ĠV ân",
+      "à¸Ń ร",
+      "à¸Ńร à¹Īà¸Ńย",
+      "ĠاÙĦس ÙĨØ©",
+      "Ġc Æ°á»Ľi",
+      "×Ļ×Ķ ף",
+      "íį ¼",
+      "話 ãģĹ",
+      "âĹ ĭ",
+      "ĠìķĬ ìĿĢ",
+      "ãĥ¡ ãĥ¼ãĤ",
+      "ãĥ¡ãĥ¼ãĤ «",
+      "ãĥ¡ãĥ¼ãĤ« ãĥ¼",
+      "ĠÑĤеп ло",
+      "å½¼ ãĤī",
+      "ĠÄ° z",
+      "ĠÄ°z mir",
+      "íĻ į",
+      "Ġr ượ",
+      "Ġrượ u",
+      "æĢĿãģĦ åĩº",
+      "ĠPh ạm",
+      "Ġchá u",
+      "צ×Ļ ×ķת",
+      "ĠìĿ¼ 본",
+      "ìĤ¬ ëĬĶ",
+      "ĠÑģозд ан",
+      "Ġar acı",
+      "Ġ×¢ ר",
+      "Ġער ×Ļ׼×Ķ",
+      "ĠíķĺëĤĺëĭĺ ìĿĺ",
+      "dzi ÅĤ",
+      "à¸Ľà¸£à¸° à¸ĺาà¸Ļ",
+      "Ġser ÃŃa",
+      "ĠìŀĪ ëıĦë¡Ŀ",
+      "در ج",
+      "íķľëĭ¤ ëĬĶ",
+      "à¸Ńา à¸Ĺ",
+      "à¸Ńาà¸Ĺ ิà¸ķ",
+      "à¸Ńาà¸Ĺิà¸ķ ยà¹Į",
+      "ÑĤелÑĮ нÑĭй",
+      "ĠØ® دÙħات",
+      "×ŀ׳ ×ĺ",
+      "Ġl ược",
+      "ĠS Ãłi",
+      "ĠÙĪ اض",
+      "ĠÙĪاض ØŃ",
+      "غ از",
+      "ĠdoÄŁ al",
+      "Ġ×ijש ×Ŀ",
+      "Ġд лин",
+      "ĠØ¥ طار",
+      "Ġ×ijס פר",
+      "ãĤĴ ä¸İ",
+      "ãĤĴä¸İ ãģĪ",
+      "Ġë²ķ ë¥ł",
+      "ĠÑĥ вели",
+      "ĠÑĥвели Ñĩи",
+      "ส à¹Ħà¸ķ",
+      "สà¹Ħà¸ķ ลà¹Į",
+      "à¹Ħ à¸ģล",
+      "×ij׊ף",
+      "ĠìĿ´ íĽĦ",
+      "Ġm unic",
+      "Ġmunic ÃŃpio",
+      "تÙħ Ø«ÙĦ",
+      "ĠÄij áo",
+      "H ôtel",
+      "Ġl á»Ńa",
+      "ĠÄij ẳng",
+      "Ñĩ ки",
+      "Ø´ رÙĪ",
+      "شرÙĪ Ø·",
+      "ĠìĿ´ 를",
+      "ÙĬ Ùĭا",
+      "×ŀ׾ ×ļ",
+      "×ŀ×Ķ ×Ļר×ķת",
+      "ĠобÑıз аÑĤелÑĮ",
+      "ĠобÑıзаÑĤелÑĮ но",
+      "é nergie",
+      "Ġmud ança",
+      "Ġm ụ",
+      "Ġmụ n",
+      "Ġn º",
+      "ĠاÙĦت عا",
+      "ĠاÙĦتعا ÙĪÙĨ",
+      "ĠاÙĦاجتÙħاع ÙĬØ©",
+      "Ġп лаÑģÑĤ",
+      "Ġëĵ± ìĿĺ",
+      "ãĥIJãĤ¤ ãĤ¯",
+      "Ùĩج ÙĪÙħ",
+      "ĠSa úde",
+      "Ġì¤ijìļĶ íķľ",
+      "Ġ×Ķצ ×Ļ×ij×ķר",
+      "תק ף",
+      "ĠاÙĦعاÙĦÙħ ÙĬ",
+      "ĠболÑĮÑĪ ой",
+      "ĠÙĥ ÙĦÙħ",
+      "ĠÙĥÙĦÙħ Ø©",
+      "ãģ®ãģ§ãģ¯ãģªãģĦ ãģ§ãģĹãĤĩãģĨãģĭ",
+      "ĠÙħ باراة",
+      "Ġש×IJ ׳",
+      "Ġש×IJ׳ ×Ĺ׳×ķ",
+      "ãĤ¹ãĤ¿ ãĤ¤ãĥ«",
+      "ĠSa ÄŁ",
+      "ĠSaÄŁ lık",
+      "Ġh Æ°",
+      "׳ ×Ĺ×Ķ",
+      "Ġ×ij קר×ij",
+      "Ø· عÙħ",
+      "ห ิà¸Ļ",
+      "à¸Ĺุà¸ģ วัà¸Ļ",
+      "à¸Ħรัà¹īà¸ĩ à¸Ĺีà¹Ī",
+      "ĠlÃł nh",
+      "Ġdonn é",
+      "ãģĽ ãģĦ",
+      "جز ÙĬرة",
+      "доÑĢ ож",
+      "ì¼ ľ",
+      "تÙĨظ ÙĬÙģ",
+      "ãĥģ ãĥ§",
+      "Ġald ıģı",
+      "ج اج",
+      "ĠÑĤ омÑĥ",
+      "à¸Ľ ิ",
+      "Ġ×ijר שת",
+      "ãģıãģªãĤĬ ãģ¾ãģĻ",
+      "ĠпÑĢин ÑĨип",
+      "Ġ׊׾×ķ",
+      "ëı ¼",
+      "×ķ×Ĵ ש",
+      "س س",
+      "à¸Ľ ู",
+      "Ġh ầu",
+      "æĦŁãģĺ ãĤĭ",
+      "ï¼ ´",
+      "د ÙĪا",
+      "ĠÑģм ог",
+      "scri ção",
+      "Ġth áºŃn",
+      "Ġר ×ķ×IJ×Ķ",
+      "обÑĢаж ен",
+      "ĠاÙĦتج ارÙĬØ©",
+      "Ø· بÙĬع",
+      "jÄħc Äħ",
+      "íĸī ìľĦ",
+      "Ġнов Ñĭй",
+      "Ġ×ŀ ×Ĺ×ĵש",
+      "æĮ¯ ãĤĬ",
+      "gu é",
+      "Ġ×IJ ×Ļר×ķ×¢",
+      "Ġ×IJ×Ļר×ķ×¢ ×Ļ×Ŀ",
+      "ĠاÙĦ Ø°Ùĩب",
+      "×ĵ ×IJ",
+      "ت اÙĨ",
+      "ãģł ãģĹ",
+      "à¸Ńั à¸ķรา",
+      "à¹Ĥ à¸Ī",
+      "بÙĦ اد",
+      "×Ķ×Ļ ×Ļ׳×ķ",
+      "ĠÑģп е",
+      "ĠÑģпе ÑĨиалÑĮно",
+      "ĠÅĽwi ata",
+      "ãĤĵãģ§ãģĻ ãĤĪ",
+      "شر ÙĥØ©",
+      "ĠpÅĤ yt",
+      "Ġsitu é",
+      "Ġ׼×IJ ׾×Ķ",
+      "ס ×ijר",
+      "Ġkaż d",
+      "Ġkażd ym",
+      "ãĤĴæĮģ ãģ¤",
+      "׾×Ķ ׾",
+      "׾×Ķ׾ ף",
+      "ĠwÅĤ as",
+      "ĠwÅĤas ne",
+      "ĠsaÄŁ lan",
+      "×ŀ×¢ ׾×Ķ",
+      "ĠاÙĦا ÙĪÙĦ",
+      "ìĹIJìĦľ ëıĦ",
+      "×IJ×Ļר ×ķפ×Ķ",
+      "تÙĤ ÙĨÙĬØ©",
+      "Ùħ ائ",
+      "Ùħائ Ø©",
+      "Ġcompañ ÃŃa",
+      "Ġsü rek",
+      "Ġsürek li",
+      "ĠиÑģ кÑĥÑģ",
+      "ĠиÑģкÑĥÑģ ÑģÑĤв",
+      "ĠB ürger",
+      "ת ×Ĺר",
+      "ת×Ĺר ×ķת",
+      "à¸ŀรà¹īà¸Ńม à¸ģัà¸ļ",
+      "Ø´ Ùħ",
+      "à¸ĸืà¸Ń วà¹Īา",
+      "è¾¼ ãĤĢ",
+      "ä¼ij ãģ¿",
+      "ĠاÙĦØ£ ب",
+      "ĠÑģÑĤоим оÑģÑĤÑĮ",
+      "ĠпÑĢав а",
+      "may ın",
+      "ห วย",
+      "ĠاÙĦØ· بÙĬعÙĬ",
+      "à¸Ĺีà¹Ī à¸ŀัà¸ģ",
+      "ĠEst á",
+      "Ñĭва ÑİÑĤ",
+      "ب سÙĬ",
+      "بسÙĬ Ø·",
+      "Ġ×ij×¢ ×ijר",
+      "åı¯èĥ½ ãģ§ãģĻ",
+      "Ġ×ĵ ×ķ׾",
+      "Ġ×ĵ×ķ׾ ר",
+      "Ùĩ Ùİا",
+      "воÑĢ оÑĤ",
+      "ãģ¦ ãģĦãģ¾ãģĹãģŁ",
+      "à¹Ĥà¸Ĺร ศ",
+      "à¹Ĥà¸Ĺรศ ั",
+      "à¹Ĥà¸Ĺรศั à¸ŀ",
+      "à¹Ĥà¸Ĺรศัà¸ŀ à¸Ĺà¹Į",
+      "Ġק ׳",
+      "ĠاÙĦØ« ÙĨ",
+      "ĠاÙĦØ«ÙĨ ائÙĬØ©",
+      "Ġco ût",
+      "à¸ķิà¸Ķ à¸ķัà¹īà¸ĩ",
+      "Ġö rg",
+      "Ġörg üt",
+      "ĠاÙĦØ® ÙĦÙĬ",
+      "ĠاÙĦØ®ÙĦÙĬ ج",
+      "Ġb á»įn",
+      "×ķ׾×ķ×Ĵ ×Ļ",
+      "ëŀ ľ",
+      "ĠÐij олÑĮ",
+      "ĠÐijолÑĮ ÑĪ",
+      "×Ĵ ×ijר×Ļ×Ŀ",
+      "ÙĤ ÙĬد",
+      "×ij×Ļ×ĺ ×ķ×Ļ",
+      "æīĵ ãģ¡",
+      "Ġol muÅŁ",
+      "f äh",
+      "fäh ig",
+      "ล าà¸Ļ",
+      "ĠÙĤ طر",
+      "ש פ×Ķ",
+      "èªŃ ãĤĵãģ§",
+      "à¸Ĥ วา",
+      "Ġchi ếm",
+      "ãĤ¤ãĥ³ ãĤ¿",
+      "ãĤ¤ãĥ³ãĤ¿ ãĥ¼ãĥ",
+      "ãĤ¤ãĥ³ãĤ¿ãĥ¼ãĥ į",
+      "ãĤ¤ãĥ³ãĤ¿ãĥ¼ãĥį ãĥĥãĥĪ",
+      "Ġ׾ש×ŀ ×ķר",
+      "Ġت رÙĥ",
+      "ĠترÙĥ ÙĬا",
+      "ר ×ķ×ĺ",
+      "ãģ¨æĢĿ ãģĦãģ¾ãģĹãģŁ",
+      "ĠاÙĦت ÙĤ",
+      "Ġd Æ°",
+      "ãģ¦ãģıãĤĮ ãĤĭ",
+      "ãģĹãģŁ ãģĵãģ¨",
+      "Ġróż ne",
+      "ĠاÙĦØ· ÙģÙĦ",
+      "ĠPost é",
+      "Ġ×ŀש ×ķ×Ŀ",
+      "Ñį ÑĢ",
+      "ĠÑĢабоÑĤ аеÑĤ",
+      "ãĤ· ãĥª",
+      "ãĤ·ãĥª ãĥ¼ãĤº",
+      "Ġ×ij×Ķ ×Ĺ׾×ĺ",
+      "ק×Ķ ×Ļ׾×Ķ",
+      "ãĤ« ãĥ¡",
+      "ãĤ«ãĥ¡ ãĥ©",
+      "ï¼ ¯",
+      "ĠìĤ¬ ìĿ´",
+      "Ġk ì",
+      "Ġth Æ°á»Ľc",
+      "ض بط",
+      "ÙĤب ÙĪÙĦ",
+      "åĪ¥ ãģ®",
+      "Ġparticul ière",
+      "ĠÑģво ем",
+      "Ġ×¢ סק",
+      "Ġעסק ×Ļ×Ŀ",
+      "×ij×Ĺ ×Ļר×ķת",
+      "×ij ×Ļ׳×ķ",
+      "à¸ĭ à¸Ń",
+      "Ġ×¢ ×ķ×ijר",
+      "ãģłãģ£ãģŁ ãģ®ãģ§",
+      "ıld ıģı",
+      "Ùħ دار",
+      "Ùħدار س",
+      "주 ìĭľ",
+      "à¸Ńา ศ",
+      "à¸Ńาศ ัย",
+      "Ġt ấm",
+      "à¸ŀิ à¸Ī",
+      "à¸ŀิà¸Ī าร",
+      "à¸ŀิà¸Īาร à¸ĵา",
+      "ÑĤелÑĮ нÑĭе",
+      "Ñģк ÑĥÑİ",
+      "Ðľ Ðĺ",
+      "à¹Ģà¸ģ า",
+      "à¹Ģà¸ģา หล",
+      "à¹Ģà¸ģาหล ี",
+      "×ĵ ×Ĺ",
+      "à¹Ģà¸Ĭ ิà¸ĩ",
+      "Ġد ÙĤÙĬÙĤØ©",
+      "íķĻ ìĥĿ",
+      "Ġש×IJ ׾×Ķ",
+      "Ġcontr ôle",
+      "Ġsit uação",
+      "à¸Ĥà¸Ńà¸ĩ à¸ľà¸¹à¹ī",
+      "ÙĨ Ø·ÙĤ",
+      "ê³¼ íķĻ",
+      "หลาย à¸Ħà¸Ļ",
+      "Ġn ắng",
+      "ÙĤ Ùı",
+      "ì¡° ê±´",
+      "Ñ ķ",
+      "ãĥĥ ãģ¨",
+      "×ŀ ×Ļ׾×Ķ",
+      "Gr ün",
+      "×Ļ ×Ļ×¢",
+      "×Ļ×Ļ×¢ ×ķ×¥",
+      "×ŀ׳ ׼",
+      "ë ŃIJ",
+      "×ŀ×¢ ×ŀ×ĵ",
+      "สำ à¸Ļัà¸ģ",
+      "ج دد",
+      "à¸Ħ ัà¸Ķ",
+      "Ġ×Ķ×ŀש פ",
+      "Ġ×Ķ×ŀשפ ×Ĺ×Ķ",
+      "×ŀש ק׾",
+      "ÙĦ Ùı",
+      "Ġty tu",
+      "Ġtytu ÅĤ",
+      "ÑĪ ей",
+      "ĠìĿ¼ ë¶Ģ",
+      "ÑĪ ение",
+      "Ġph óng",
+      "ĠìĹŃ ìĤ¬",
+      "ãĤ« ãĥ³",
+      "Ġtú i",
+      "ĠÙĨ ÙĪÙģ",
+      "ĠÙĨÙĪÙģ Ùħبر",
+      "gr ün",
+      "ĠاÙĦØ´ ÙħاÙĦ",
+      "ÅĽwi adc",
+      "ÅĽwiadc zenie",
+      "ער ×Ķ",
+      "Ġ×¢ ×ķ×ij",
+      "Ġ×¢×ķ×ij ×ĵ×Ļ×Ŀ",
+      "×ĵ×ķ×Ĵ ×ŀ×IJ",
+      "ä»Ĭ ãģ¯",
+      "Ġv ão",
+      "ĠТ ем",
+      "Ñģ илÑĮ",
+      "Ġch ợ",
+      "Ùħ را",
+      "Ùħرا ÙĤب",
+      "à¹Ħมà¹Ī รูà¹ī",
+      "Ġر ائع",
+      "×IJ׳ ×Ĺ׳×ķ",
+      "สà¹Īà¸ĩ à¹Ģสริม",
+      "צ ×Ĺ",
+      "ĠìŀĪìĸ´ ìĦľ",
+      "Ġkur ulu",
+      "Ġkurulu ÅŁ",
+      "ĠÃĸ zellik",
+      "ĠÃĸzellik le",
+      "Ġת ×Ļק",
+      "Ġgh é",
+      "Ġspr zÄĻ",
+      "ĠsprzÄĻ t",
+      "ער ×ķת",
+      "را ØŃØ©",
+      "ãģ£ ãģį",
+      "ãģ£ãģį ãĤĬ",
+      "ĠìķĦ ëŀĺ",
+      "stit uição",
+      "Ġдолж но",
+      "×Ķ רש",
+      "×Ķרש ×ŀ×Ķ",
+      "×Ķ׾ ×ļ",
+      "ãģ¡ ãģª",
+      "ãģ¡ãģª ãģ¿",
+      "ãģ¡ãģªãģ¿ ãģ«",
+      "פ ×Ĺ×ĵ",
+      "ĠاÙĦج ÙħÙĬع",
+      "×ij×¢ ׾×Ļ",
+      "Ġtr ùng",
+      "Ġפ ת×Ĺ",
+      "×ŀ׾×Ĺ ×ŀת",
+      "ãĥĨ ãĥ¼ãĥ",
+      "ãĥĨãĥ¼ãĥ ŀ",
+      "Ùħ تاب",
+      "Ùħتاب عة",
+      "Ġ모 ìĬµ",
+      "ÙĬ ص",
+      "åIJĪ ãģĨ",
+      "ĠY ap",
+      "ĠYap ı",
+      "ĠÑģ казаÑĤÑĮ",
+      "ëª °",
+      "à¸Ĺีà¹Ī สำà¸Ħัà¸į",
+      "ĠìĹĨ ìĬµëĭĪëĭ¤",
+      "Ġnh ắc",
+      "Ġülk eler",
+      "Ġмног ие",
+      "íķĺ ìħ¨",
+      "มาà¸ģ à¸Ĺีà¹Īสุà¸Ķ",
+      "à¸ģ à¹īา",
+      "à¸ģà¹īา ว",
+      "ĠÄ° yi",
+      "л еж",
+      "леж а",
+      "ãĤ¸ ãĥ§",
+      "à¸Ĺั à¸ŀ",
+      "ا ÙĪر",
+      "Ġ×Ĺ×ijר ×Ļ",
+      "Ġ׾ ש×Ŀ",
+      "ì² «",
+      "ĠT á»Ń",
+      "×ŀ ×ķ׳×Ļ",
+      "ÙĤ ÙĪد",
+      "à¸ģระ à¹Ģà¸Ľ",
+      "à¸ģระà¹Ģà¸Ľ à¹ĭ",
+      "à¸ģระà¹Ģà¸Ľà¹ĭ า",
+      "ĠпÑĢоблем Ñĭ",
+      "Ġaç ıs",
+      "Ġaçıs ından",
+      "Ġ×Ķ×ŀ ׼",
+      "ĠÙħع ظÙħ",
+      "ÙĤÙĬ اس",
+      "ĠпÑĢод олж",
+      "ĠпÑĢодолж а",
+      "Ġver diÄŁi",
+      "ĠпÑĢед меÑĤ",
+      "ãģĦãģ¾ãģĻ ãģĮ",
+      "ĠëĶ° 른",
+      "ĠاÙĦ ÙĤÙĬاÙħ",
+      "ĠØ¥ÙĦÙĬ Ùĩا",
+      "Т ÐIJ",
+      "п оз",
+      "ãĤ· ãĥ¥",
+      "ä¸ĬãģĮ ãĤĬ",
+      "à¹Ģà¸Ķิม à¸ŀัà¸Ļ",
+      "à¸ģุ ล",
+      "ØŃر ÙĬØ©",
+      "ק×ij×ķצ ×ķת",
+      "ë¯ ¿",
+      "ĠاÙĦÙħ ÙĨا",
+      "ĠاÙĦÙħÙĨا Ø·ÙĤ",
+      "ĠвÑĭп ол",
+      "ĠвÑĭпол нÑı",
+      "ãĥĭ ãĤ¢",
+      "Ġê²° êµŃ",
+      "×Ĺ ×ķ×ŀ",
+      "×Ĺ×ķ×ŀ ר×Ļ×Ŀ",
+      "ĠУкÑĢа инÑĭ",
+      "ห à¸Ńม",
+      "ר ×Ļס",
+      "ĠÑħоÑĤ ел",
+      "ĠобÑĢаз ованиÑı",
+      "Ġkh ẳng",
+      "Ġm Æ°a",
+      "Ġgör me",
+      "Ġgüç lü",
+      "سع Ùī",
+      "มัà¹Īà¸Ļ à¹ĥà¸Ī",
+      "íķĺ ê²łìĬµëĭĪëĭ¤",
+      "Ġпол Ñĥ",
+      "Ġfün f",
+      "ãģ¨æĢĿ ãģ£ãģ¦ãģĦãģ¾ãģĻ",
+      "Ġê·¸ê²ĥ ìĿĢ",
+      "ĠdÃ¼ÅŁÃ¼n ce",
+      "ìŀ ł",
+      "ĠH Æ°á»Ľng",
+      "ĠTi á»ĥu",
+      "Ġç ift",
+      "ãģij ãģ°",
+      "à¸Īà¸Ļ à¸ĸึà¸ĩ",
+      "à¸Ĺำ à¹Ħà¸Ķà¹ī",
+      "ĠìŀIJ ì²´",
+      "Ġd õ",
+      "Ġdõ i",
+      "à¸Ī ัà¸Ļ",
+      "à¸Īัà¸Ļ à¸Ĺ",
+      "à¸Īัà¸Ļà¸Ĺ รà¹Į",
+      "ece ÄŁini",
+      "׳×ķ×¢ ר",
+      "غ ار",
+      "ĠاÙĦØ£ÙħرÙĬ ÙĥÙĬ",
+      "داع ش",
+      "ĠбезопаÑģ ноÑģÑĤи",
+      "Ġб Ñİ",
+      "ĠбÑİ Ð´Ð¶",
+      "ĠбÑİдж еÑĤ",
+      "ãĥĬ ãĤ¤",
+      "à¸ŀà¸ļ วà¹Īา",
+      "da ÄŁ",
+      "×IJ ×ķפף",
+      "íĹ Į",
+      "ãĥĢãĤ¤ ãĤ¨",
+      "ãĥĢãĤ¤ãĤ¨ ãĥĥãĥĪ",
+      "ĠëĮĢ íĨµ",
+      "ĠëĮĢíĨµ ëł¹",
+      "D Ä°",
+      "Ø£ ØŃداث",
+      "ĠA ÄŁ",
+      "ĠAÄŁ ust",
+      "ĠAÄŁust os",
+      "ØŃÙĦ ÙĪÙĦ",
+      "Ġw ÅĽ",
+      "ĠwÅĽ ród",
+      "ĠÑģо оÑĤвеÑĤ",
+      "ĠÑģооÑĤвеÑĤ ÑģÑĤв",
+      "ĠÑģооÑĤвеÑĤÑģÑĤв ии",
+      "ĠLu áºŃt",
+      "Ġ׼׾ פ×Ļ",
+      "Ġв еÑī",
+      "ĠвеÑī еÑģÑĤв",
+      "ק ×Ļ×¥",
+      "ĠبÙĩ ذا",
+      "عا ش",
+      "à¹Ģà¸Ľà¹ĩà¸Ļ à¹Ģรืà¹Īà¸Ńà¸ĩ",
+      "Т Ðķ",
+      "Ġ×ij×IJ ×Ļ׳×ĺר׳×ĺ",
+      "س عد",
+      "Ġ×Ķ×ĺ ×Ļפ×ķ׾",
+      "פ ×Ļס",
+      "à¸ĩà¹Īาย à¹Ĩ",
+      "ĠGer ät",
+      "׾ ×Ļ×ĵ×Ķ",
+      "ĠÑĢ иÑģк",
+      "׾ק ×Ĺ",
+      "н наÑı",
+      "ר ×Ļ×ĵ",
+      "п ÑĢакÑĤи",
+      "пÑĢакÑĤи к",
+      "à¸Ĥัà¹īà¸Ļ à¸ķà¸Ńà¸Ļ",
+      "à¸Ļà¹Īา รัà¸ģ",
+      "larınız ı",
+      "à¸Ńà¸Ļุ à¸įา",
+      "à¸Ńà¸Ļุà¸įา à¸ķ",
+      "ĠzdjÄĻ cia",
+      "Ġb ây",
+      "Ñģ ÑĢ",
+      "ÑģÑĢ оÑĩ",
+      "ãĥĭ ãĥ³ãĤ°",
+      "Ġö ner",
+      "Ġöner i",
+      "Ġнов ÑĭÑħ",
+      "دع ÙĪØ©",
+      "Ġg ắn",
+      "ĠاÙĦÙĦ بÙĨ",
+      "ĠاÙĦÙĦبÙĨ اÙĨÙĬ",
+      "ãĥĨãĤ£ ãĥ¼",
+      "Ġص ØŃÙĬØŃ",
+      "ем ÑĭÑħ",
+      "çĸ² ãĤĮ",
+      "ĠпÑĢо иÑģ",
+      "ĠпÑĢоиÑģ ÑħодиÑĤ",
+      "ส à¸ķิ",
+      "ĠT ết",
+      "Ġ×Ķ׾ ׾×ķ",
+      "à¹Ģรืà¹Īà¸Ńà¸ĩ à¸Ļีà¹ī",
+      "×ŀ×ij ׳×Ķ",
+      "Ġconte údo",
+      "Ġا خت",
+      "Ġاخت ÙĬار",
+      "Ùħ سÙĦ",
+      "ÙħسÙĦ سÙĦ",
+      "ëı Ī",
+      "Ġ׾ ×Ļ×ĵ",
+      "à¸ŀิ à¸ĺี",
+      "ĠÑģов Ñģ",
+      "ĠÑģовÑģ ем",
+      "ãģĮãģĤãĤĬ ãģ¾ãģĹãģŁ",
+      "Ġsó ng",
+      "Ø¥ صÙĦاØŃ",
+      "ë§ ģ",
+      "Ùģ ÙĬر",
+      "ĠJe żeli",
+      "ìłľ ëıĦ",
+      "d ÅĤug",
+      "ìĥģ ìĿĦ",
+      "Ġc áºŃn",
+      "Ġhá»į p",
+      "أ ست",
+      "أست اذ",
+      "Ġ×ŀ ×Ļש×Ķ",
+      "Ġ×ŀ×Ļש×Ķ ×ķ",
+      "Ġd Ãły",
+      "Ġch Ãłng",
+      "ãģ¡ãĤĥãĤĵ ãģ¨",
+      "ĠÄij ám",
+      "Ġsw ój",
+      "Ġpoder á",
+      "ĠоÑĤлиÑĩ а",
+      "Ġpéri ode",
+      "ünd ig",
+      "×ĺ×¢ ף",
+      "ÑģÑĤÑĢо иÑĤелÑĮ",
+      "ר ת×Ļ",
+      "Ġ×Ļ×Ķ ×Ļ×ķ",
+      "׾ ס",
+      "ĠاÙĦÙħÙĨ زÙĦ",
+      "à¸Ļิ à¹īว",
+      "иÑĦ ика",
+      "иÑĦика ÑĨи",
+      "ðŁĺ ī",
+      "Ġad ına",
+      "ãĢĤãĢĤ ãĢĤ",
+      "×IJ ×Ļף",
+      "ס ×Ļר",
+      "ĠÙĬ عد",
+      "çŃĶ ãģĪ",
+      "اÙĦ جز",
+      "اÙĦجز ائر",
+      "енÑĮ к",
+      "ร ห",
+      "รห ัส",
+      "ĠTürk çe",
+      "ê¾ ¸",
+      "Ġ×Ļ ×ķ׼׾",
+      "Ġש ×ķ׳×Ķ",
+      "Ġ×ij×ŀ צ×ij",
+      "ĠдейÑģÑĤв иÑĤелÑĮно",
+      "ĠبأÙĨ Ùĩ",
+      "×ŀק ×ĵ",
+      "Ġ×Ķש ק",
+      "Ø®ÙĬ ارات",
+      "Ġf ı",
+      "Ġfı rs",
+      "Ġfırs at",
+      "ëij ĺ",
+      "ĠìĦľ ìļ¸",
+      "Ġ×Ķ×Ĵ ×ķ×£",
+      "ر عا",
+      "رعا ÙĬØ©",
+      "ĠK ết",
+      "к Ñģи",
+      "ĠÑĥÑģлÑĥг и",
+      "ноÑģÑĤ ей",
+      "ìļ´ ëıĻ",
+      "ĠобÑĬ Ñı",
+      "ĠобÑĬÑı вл",
+      "н еж",
+      "×Ķפ ×ļ",
+      "Ġ×ij×¢ ×Ļ׳×Ļ",
+      "ëĨ Ĵ",
+      "ĠпÑĢоÑĨ ед",
+      "ĠпÑĢоÑĨед ÑĥÑĢ",
+      "Ġiht iy",
+      "Ġihtiy acı",
+      "Ġë°Ķ ëŀį",
+      "Ġë°Ķëŀį ëĭĪëĭ¤",
+      "à¸ģล ัว",
+      "ĠÑģл ожно",
+      "ק×Ļ ×Ļ×ŀת",
+      "ĠÄIJ ình",
+      "ĠÙħ ÙĦÙģ",
+      "Ġà¹Ĥà¸Ķย มี",
+      "Ġkat kı",
+      "تØŃ ÙĪÙĬÙĦ",
+      "à¹Ħ à¸ŀ",
+      "ĠH á»į",
+      "ñ e",
+      "Ġдо Ñħод",
+      "Ġtho ải",
+      "íķĺìŬ ìķ¼",
+      "ãĤ¹ãĥĿ ãĥ¼ãĥ",
+      "ãĤ¹ãĥĿãĥ¼ãĥ Ħ",
+      "ĠG òn",
+      "Ġk è",
+      "Ġkè m",
+      "éĢ² ãĤģ",
+      "ãĤ¹ ãĥ¼ãĥ",
+      "ãĤ¹ãĥ¼ãĥ ij",
+      "ãĤ¹ãĥ¼ãĥij ãĥ¼",
+      "ĠgiÃł u",
+      "ĠØ¥ عادة",
+      "Ġ׾ ×ķק",
+      "Ġ׾×ķק ×Ĺ",
+      "ĠÑħоÑĩ еÑĤ",
+      "×ĺ ׾×ķ×ķ",
+      "×ĺ׾×ķ×ķ ×Ļ×ĸ",
+      "×ĺ׾×ķ×ķ×Ļ×ĸ ×Ļ×Ķ",
+      "Ġth uyết",
+      "ãģĿãĤĮ ãģ§",
+      "Ġvard ı",
+      "à¹Ħร à¹ī",
+      "ع بد",
+      "ĠRep ública",
+      "ãĥ¼ãĤ¿ ãĥ¼",
+      "Ġ×ŀ×IJ ×ķת",
+      "à¹Ħà¸Ľ à¹ģลà¹īว",
+      "Ġyapıl acak",
+      "ãĤ¹ãĤ¿ ãĥ¼ãĥĪ",
+      "ãģ» ãģ¼",
+      "Ġko ÅŁ",
+      "ĠмаÑĤ еÑĢи",
+      "Ġsiè cle",
+      "ĠاÙĦÙħ ختÙĦÙģ",
+      "ĠاÙĦÙħختÙĦÙģ Ø©",
+      "Ġ׾ק ר×IJ",
+      "Ġ׾קר×IJ ת",
+      "Ġ×Ķפ ×ķ×¢×ľ",
+      "Ġt òa",
+      "Ġr Æ¡i",
+      "åij¨ ãĤĬ",
+      "à¸Ŀ à¸Ļ",
+      "j ÅĽÄĩ",
+      "ĠìķĬ ìĿĦ",
+      "اÙĨت ÙĤاÙĦ",
+      "ëĸ ł",
+      "ив аеÑĤ",
+      "ãĥĪ ãĥ«",
+      "ĠاÙĦÙģÙĦسطÙĬÙĨ ÙĬØ©",
+      "à¸ģลà¹Īาว วà¹Īา",
+      "ا Ùĥت",
+      "ĠÃĸ l",
+      "ĠÑĢе ÑĪи",
+      "ĠÑĢеÑĪи л",
+      "Ġ׳×ķס פ×ķת",
+      "Ġìłķ ì¹ĺ",
+      "вл еÑĩен",
+      "Ùħر ØŃÙĦØ©",
+      "Ġcome ça",
+      "Ġy ık",
+      "ìĤ ´",
+      "à¸ĺ à¸Ļา",
+      "à¸ĺà¸Ļา à¸Ħาร",
+      "à¸Ńà¸Ļ า",
+      "à¸Ńà¸Ļา à¸Ħ",
+      "à¸Ńà¸Ļาà¸Ħ à¸ķ",
+      "Ġpeque ña",
+      "ä»ķ äºĭãĤĴ",
+      "Ġب Ø°ÙĦÙĥ",
+      "Ġнов ого",
+      "ãģĹãģ¦ ãģĦãģªãģĦ",
+      "ĠاÙĦÙħ ÙĬاÙĩ",
+      "à¸ģà¹ĩ à¹Ģà¸Ľà¹ĩà¸Ļ",
+      "Ġж ÑĥÑĢ",
+      "ĠжÑĥÑĢ нал",
+      "в еÑģ",
+      "خت ار",
+      "Ġ매 ìļ°",
+      "ĠM ã",
+      "ĠавÑĤомаÑĤ Ñĭ",
+      "ضع Ùģ",
+      "ĠاÙĦÙģ Ùĥر",
+      "ãģ§ãģĻ ãģ®ãģ§",
+      "ãĥ¡ãĥ³ ãĥIJãĥ¼",
+      "Ġк ÑĢÑĥг",
+      "ĠاÙĦسÙĦ طة",
+      "à¸Ħรัà¹īà¸ĩ à¹ģรà¸ģ",
+      "à¸ģระà¸Ĺ รว",
+      "à¸ģระà¸Ĺรว à¸ĩ",
+      "ÑĨ ов",
+      "éķ· ãģĦ",
+      "大ãģį ãģĦ",
+      "Ġgeç miÅŁ",
+      "ìĦ± ìĿ´",
+      "Ġצר ×Ļ׼×Ķ",
+      "Ġм оÑī",
+      "ĠмоÑī н",
+      "Ġק ×Ļש",
+      "Ġק×Ļש ×ķר×Ļ×Ŀ",
+      "ĠNas ıl",
+      "г ÑĢан",
+      "Ġ×ŀ ×ķצר×Ļ×Ŀ",
+      "Ġ×ŀס ×ķ×Ĵ",
+      "Ġy ür",
+      "Ġyür üt",
+      "Ġ׾׊צ×ķ",
+      "×ķÖ ¼",
+      "ĠìŀĪ ìĹĪëĭ¤",
+      "Ġter ör",
+      "ĠTh Æ°Æ¡ng",
+      "ĠÙĪ ÙĬÙħ",
+      "ĠÙĪÙĬÙħ ÙĥÙĨ",
+      "ج ÙĪÙĨ",
+      "ĠÙĪغÙĬر Ùĩا",
+      "×ŀ פ×ķ",
+      "×Ĵ×ķר ×ŀ×Ļ×Ŀ",
+      "׼×ij ×Ļש",
+      "ĠاÙĦÙĦ غ",
+      "ĠاÙĦÙĦغ Ø©",
+      "شر Ùĥ",
+      "ĠاÙĦر اب",
+      "ĠاÙĦراب ع",
+      "ĠпÑĢ ек",
+      "ĠпÑĢек ÑĢаÑģ",
+      "ĠпÑĢекÑĢаÑģ н",
+      "Ġenerg ÃŃa",
+      "ק×ĵ ×ŀ×Ļ",
+      "ãģıãģª ãģ£ãģŁ",
+      "ĠÄij ứ",
+      "ĠÄijứ a",
+      "Serv i",
+      "Servi ço",
+      "Ġkald ır",
+      "åĥį ãģį",
+      "Ġод еж",
+      "Ġодеж д",
+      "물 ìĿĦ",
+      "ãģĿãģĨ ãģ§",
+      "ãģĮãģĤ ãĤĮãģ°",
+      "ìĻ ķ",
+      "צ×ĵ ק",
+      "Ġart ır",
+      "Ġile ti",
+      "Ġileti ÅŁim",
+      "ãĤĪãģĨ ãģ§",
+      "ãĥĪ ãĥ¼",
+      "ãĤ¢ ãĥĭ",
+      "ãĤ¢ãĥĭ ãĥ¡",
+      "×ĺ×Ļ ×Ļ׾",
+      "ãĥķ ãĥªãĥ¼",
+      "ãĥĿ ãĥ³",
+      "ÐŁÑĢ о",
+      "Ġع اÙĦÙĬØ©",
+      "ĠÃ¶ÄŁ ret",
+      "ĠÃ¶ÄŁret men",
+      "ĠкаÑĩеÑģÑĤв а",
+      "Ġ×Ķ×ĺ ×ij×¢",
+      "Ġзна Ñİ",
+      "ãģ¦ ãģıãĤĭ",
+      "Ġm ừng",
+      "ÙħÙĪ ت",
+      "ש ×ķ×ŀר",
+      "×Ĺ׾ ×ij",
+      "Ġwzgl ÄĻ",
+      "ĠwzglÄĻ du",
+      "ë²Ī 째",
+      "Ġtá» ĵ",
+      "Ġtá»ĵ n",
+      "ãĥ¯ãĥ¼ ãĤ¯",
+      "Ġpo życz",
+      "Ġpożycz k",
+      "×Ļ ×ķצר×Ļ×Ŀ",
+      "Ùĥر Ùħ",
+      "Ġг аÑĢ",
+      "ĠгаÑĢ ан",
+      "ĠгаÑĢан ÑĤи",
+      "ล à¹īาà¸ĩ",
+      "Ġìĺģ íĻĶ",
+      "×ĺ ×Ļס",
+      "Ġth ẻ",
+      "ĠìŀĪëĭ¤ ê³ł",
+      "اÙĦت ز",
+      "اÙĦتز اÙħ",
+      "Ġна ÑĪи",
+      "is ée",
+      "ãģĵãĤĮ ãĤĴ",
+      "Ġm ẽ",
+      "ض ÙĦ",
+      "بÙĪ ت",
+      "Ġ׼ ׼×Ķ",
+      "h ợ",
+      "ĠاÙĦس ÙĪرÙĬØ©",
+      "Ġ×ľ×¢ ×ķ×ŀ",
+      "Ġ×ľ×¢×ķ×ŀ ת",
+      "ĠbaÅŁ ar",
+      "ĠbaÅŁar ılı",
+      "е ÑģÑĤÑĮ",
+      "à¸Ħร ี",
+      "à¸Ħรี ม",
+      "ĠìłĦ ì²´",
+      "ĠسÙĬ ÙĥÙĪÙĨ",
+      "Ġ×ŀ×ĵ ×ķ×¢",
+      "ĠëķĮ문 ìĿ´ëĭ¤",
+      "Ġc ứng",
+      "ger ät",
+      "Ġм иÑĢ",
+      "ĠмиÑĢ е",
+      "ĠÙĥÙĬÙģ ÙĬØ©",
+      "Ġפר ×ĺ×Ļ×Ŀ",
+      "Ġgo ÅĽci",
+      "иÑĤ еÑģÑĮ",
+      "ÑĥÑĪ ки",
+      "ؤ ÙħÙĨ",
+      "Ġ×IJ ׼ף",
+      "ĠاÙĦر جÙĦ",
+      "Ġl á»įc",
+      "à¹Ģรีย à¸ģวà¹Īา",
+      "ãģĵãģ® ãĤĪãģĨãģª",
+      "ë§Į íģ¼",
+      "Ġп еÑĩ",
+      "ÙĪÙĦ ات",
+      "ĠÃľ ye",
+      "liÄŁ inde",
+      "à¸Ħะ à¹ģà¸Ļ",
+      "à¸Ħะà¹ģà¸Ļ à¸Ļ",
+      "ãĤĭãģĵãģ¨ ãģ¯",
+      "วิ à¹Ģà¸Ħร",
+      "วิà¹Ģà¸Ħร าะ",
+      "วิà¹Ģà¸Ħราะ หà¹Į",
+      "Ġвозмож ноÑģÑĤи",
+      "ĠاÙĦÙĨ ساء",
+      "ãĥīãĥ© ãĥŀ",
+      "Ġgü c",
+      "Ġgüc ü",
+      "Ġt Æ°á»Ŀng",
+      "Ġacomp aña",
+      "ãĤ¤ ãĥ©",
+      "ק צ×ij",
+      "ĠY ö",
+      "ĠYö net",
+      "ĠYönet im",
+      "สัม à¸ľ",
+      "à¸ªà¸±à¸¡à¸ľ ัส",
+      "à¸Ļ าม",
+      "ĠÄij ợi",
+      "à¹ģหà¹Īà¸ĩ à¸Ĭาà¸ķิ",
+      "ãģĿãĤĮ ãģ§ãĤĤ",
+      "ät ig",
+      "ת ×ķ×Ŀ",
+      "ĠbaÅŁ lat",
+      "ĠвÑģ ей",
+      "ת ×Ļק",
+      "ת×Ļק ×ķף",
+      "ĠNg ô",
+      "ĠGesch ä",
+      "ĠGeschä fts",
+      "Ø£ Ùħ",
+      "Ø£Ùħ راض",
+      "à¹Ģà¸Ĺ à¸Ħà¸Ļ",
+      "à¹Ģà¸Ĺà¸Ħà¸Ļ ิ",
+      "à¹Ģà¸Ĺà¸Ħà¸Ļิ à¸Ħ",
+      "Ġм енÑĮ",
+      "ĠменÑĮ ÑĪе",
+      "Ġöl ç",
+      "Ġölç ü",
+      "ĠÙĬ جعÙĦ",
+      "ĠÄij ỡ",
+      "ש ×Ļ׾",
+      "ש×Ļ׾ ×ķ×ij",
+      "ĠGr Ã¶ÃŁe",
+      "ĠÙĩ اتÙģ",
+      "รà¹īาà¸Ļ à¸Ńาหาร",
+      "×Ķ׾ ×Ļ׼",
+      "×Ķ׾×Ļ׼ ×Ļ",
+      "иÑĢÑĥ ÑİÑī",
+      "èĭ¥ ãģĦ",
+      "ĠÃĸ zel",
+      "ãģĦãģŁ ãĤī",
+      "à¸Ħำ à¸ĸาม",
+      "Ġzosta ÅĤy",
+      "Ġ×Ķס ×Ļפ×ķר",
+      "×Ķ ×ķ׾",
+      "×Ķ×ķ׾ ×ļ",
+      "à¹Ģà¸Ĭà¹Īà¸Ļ à¸ģัà¸Ļ",
+      "à¹Ĥ à¸Ĩ",
+      "à¹Ĥà¸Ĩ ษ",
+      "à¹Ĥà¸Ĩษ à¸ĵา",
+      "×IJר צ×ķת",
+      "×Ĵר פ×Ļ",
+      "Ġao ût",
+      "ĠÙĬ رÙĬد",
+      "ت ÙĪج",
+      "تÙĪج ÙĬÙĩ",
+      "ĠÑįÑĤ ап",
+      "ãĤ¹ãĤ¿ ãĥ³",
+      "Ġkr ó",
+      "Ġkró tk",
+      "ãĤĴ使 ãģĨ",
+      "ì ·¨",
+      "éĸ¢ ãĤı",
+      "à¸Ķà¹īวย à¸Ħวาม",
+      "à¸Ļำ à¹Ģสà¸Ļà¸Ń",
+      "Ġa yrıca",
+      "à¸Ī à¹īาà¸ĩ",
+      "ĠÑĦоÑĤ огÑĢаÑĦ",
+      "Ġв еÑĩ",
+      "ĠвеÑĩ еÑĢ",
+      "åĩº ãģĹãģŁ",
+      "ĠÐ¥ о",
+      "Ġ×ŀ ר×Ĵ×Ļש",
+      "à¹ĥหà¹ī à¹Ģà¸Ľà¹ĩà¸Ļ",
+      "ãĤĴ 缮",
+      "ãĤĴ缮 æĮĩ",
+      "׾ ×ŀ×Ļ×Ŀ",
+      "nÄħ ÅĤ",
+      "ĠÑģÑĤ анд",
+      "ĠÑģÑĤанд аÑĢÑĤ",
+      "ĠSü d",
+      "ĠT âm",
+      "اخت بار",
+      "à¹Ģà¸ģ à¸Ńรà¹Į",
+      "Ùħس رØŃ",
+      "Ġbi á»ĩn",
+      "ب Ùı",
+      "Ġص اÙĦ",
+      "ĠصاÙĦ ØŃ",
+      "ĠPh ụ",
+      "íľ ´",
+      "ãĥ¬ãĥĵ ãĥ¥ãĥ¼",
+      "Ġbụ ng",
+      "Ġrég ime",
+      "ĠØ£ Ø´Ùĩر",
+      "ĠÑĢабоÑĤ ник",
+      "à¸Ŀ ัà¸Ļ",
+      "اع تÙħ",
+      "اعتÙħ اد",
+      "Ġзам еÑĤ",
+      "ãģ¾ ãģ£ãģ¦",
+      "Ġch ặt",
+      "æĿ¥ ãĤĭ",
+      "ĠاÙĦÙĤ ÙĪات",
+      "ãģ«åħ¥ ãģ£ãģ¦",
+      "تØŃ Ø§ÙĦÙģ",
+      "Ùħ زÙĬد",
+      "ĠÙĬ صÙĦ",
+      "ìĹ ¼",
+      "à¹Ģà¸Ĭ à¹ĩ",
+      "à¹Ģà¸Ĭà¹ĩ à¸Ħ",
+      "Ġk á»ĭ",
+      "Ġká»ĭ p",
+      "ĠìķĦ ì§ģ",
+      "×IJ׳ ×Ĵ",
+      "Ġобла ÑģÑĤÑĮ",
+      "Ġpomoc Äħ",
+      "Ġ×ķ ש׾",
+      "ëĵł ì§Ģ",
+      "ĠGi ám",
+      "ĠSt ück",
+      "Ġchá y",
+      "ĠëĤĺ ìĺ¤",
+      "ש ×Ļ×ĺת",
+      "×ŀ×ĵ ר",
+      "×ŀ×ĵר ×Ļ×ļ",
+      "Ġsüre ç",
+      "к ва",
+      "×ij׾ ×Ļ×Ŀ",
+      "×Ķ ת×Ļ",
+      "×Ķת×Ļ ×Ļ×Ĺס",
+      "ÙĤب اÙĦ",
+      "Ġס ×ķ×Ĵ",
+      "Ġס×ķ×Ĵ ×Ļ",
+      "ÑģÑĤ олÑĮ",
+      "ä½ķ ãĤĤ",
+      "×ĸ׼ ×ķר",
+      "è²· ãģĨ",
+      "å®ī ãģı",
+      "à¸Ħรัà¹īà¸ĩ à¸Ļีà¹ī",
+      "kö p",
+      "ĠÑģеÑĢ виÑģ",
+      "оÑĩ нÑĭÑħ",
+      "ê±° ëŀĺ",
+      "تأ Ùĥ",
+      "تأÙĥ ÙĬد",
+      "×ĵ ׾ק",
+      "Ġпо Ñĩем",
+      "ĠпоÑĩем Ñĥ",
+      "пиÑģ аÑĤÑĮ",
+      "×ij שר",
+      "ĠH Ãłng",
+      "ĠT ìm",
+      "Ġtr ừ",
+      "ãĤ» ãĥĥãĤ¯ãĤ¹",
+      "×ķ׳ ×Ĵ",
+      "mız da",
+      "п Ñģи",
+      "ĠìŀĪ 기",
+      "Ġr út",
+      "ز اÙĨ",
+      "تÙĨ ÙĪع",
+      "ÙħÙĤ ا",
+      "ÙħÙĤا ÙĪÙħØ©",
+      "Ġ׾צ ×ķר×ļ",
+      "Ġ×ij ×Ļר×ķש׾×Ļ×Ŀ",
+      "ãĥ´ ãĤ£",
+      "eb ile",
+      "ebile ceÄŁi",
+      "ãĥ¦ ãĥ¼ãĤ",
+      "ãĥ¦ãĥ¼ãĤ ¶",
+      "ãĥ¦ãĥ¼ãĤ¶ ãĥ¼",
+      "ãĤĴä½ľ ãĤĭ",
+      "Ñģ меÑĢ",
+      "ÑģмеÑĢ ÑĤ",
+      "Ġì§ ģ",
+      "Ġì§ģ ìłij",
+      "ĠÐŁ аÑĢ",
+      "ØŃ Ø§Ø¶",
+      "ØŃاض ر",
+      "Ùħ ÙĥاÙģ",
+      "ÙħÙĥاÙģ ØŃØ©",
+      "ล ิà¸Ļ",
+      "ãģ¦ ãģįãģ¦",
+      "ÑĢоÑģ л",
+      "ĠÄ°ÅŁ te",
+      "ÙĤص ÙĬر",
+      "Ġ×ij×Ĵ ×Ļ׾",
+      "Ġ×ŀת ×IJ×Ļ×Ŀ",
+      "Ġ×Ķ ×Ĺ×ĵ",
+      "Ġ×Ķ×Ĺ×ĵ ש×Ķ",
+      "ר ×ķ×¢",
+      "Ġprodukt ów",
+      "ĠÙħ صدر",
+      "не ÑĨ",
+      "ĠاÙĦعÙħÙĦ ات",
+      "Ġçık ma",
+      "Ġد بÙĬ",
+      "ק ×Ļף",
+      "ת ×IJר",
+      "ת×IJר ×Ļ×ļ",
+      "׳×Ļ ×Ļ×ĵ",
+      "صر اع",
+      "l ève",
+      "צ ×Ļר",
+      "à¸Ķ ัà¸Ļ",
+      "à¹ĥหà¹ī à¹Ħà¸Ķà¹ī",
+      "ãĤ¿ãĤ¤ ãĥł",
+      "Ġgi ảng",
+      "С ÐŁ",
+      "ĠاÙĦÙħ ØŃÙĦ",
+      "ĠاÙĦÙħØŃÙĦ ÙĬØ©",
+      "ĠT ất",
+      "׾ ×ķ×ĺ",
+      "h á»ķ",
+      "Ġam éric",
+      "Ġaméric ain",
+      "Ġ×ijש׾ ×ij",
+      "Ġ׾×IJ ×ķ×ŀ×Ļ",
+      "Ġpe ça",
+      "ĠÑĢаз нÑĭÑħ",
+      "ãģĦãĤĭ ãģ¨",
+      "ãĥĩ ãĥ³",
+      "ס קר",
+      "Ġ×Ķ×ŀ×Ĺ ×Ļר",
+      "ãģ¨ãģĦãģĨ ãĤĤãģ®",
+      "رت بط",
+      "ĠиÑģÑĤ оÑĩ",
+      "ĠиÑģÑĤоÑĩ ник",
+      "สมัà¸Ħร สมาà¸Ĭิà¸ģ",
+      "Ġ à¸Ĺัà¹īà¸ĩ",
+      "Ġà¸Ĺัà¹īà¸ĩ à¸Ļีà¹ī",
+      "ĠT áºŃp",
+      "ãģ£ãģ¦ ãģĦãģĨ",
+      "ĠاÙĦÙĪ صÙĪÙĦ",
+      "Ġdéc ada",
+      "Ġо ÑĦоÑĢм",
+      "ĠоÑĦоÑĢм лен",
+      "สำหรัà¸ļ à¸ģาร",
+      "Ġog óln",
+      "ãģĨãģ¡ ãģ«",
+      "Ġvá rias",
+      "ãģĻãģİ ãĤĭ",
+      "ÙĪ Ùĩا",
+      "à¹Ĥà¸Ľà¸£ à¸Ķ",
+      "ĠÐłÐ¾ÑģÑģ иÑı",
+      "人 ãĢħ",
+      "ãģĹãģ¦ ãģįãģŁ",
+      "Ġsı rasında",
+      "Ġng ôn",
+      "س ÙĨØ©",
+      "تÙħ تع",
+      "×ŀ׼ ×ij×Ļ",
+      "Ġnh ấn",
+      "×¢ ×ŀ×Ļ×ĵ",
+      "á» ¨",
+      "ж иÑĤÑĮ",
+      "ãĤī ãģĽ",
+      "gr áf",
+      "gráf ica",
+      "ĠÙĤ ÙĪÙĦ",
+      "ĠÙĤÙĪÙĦ Ùĩ",
+      "ëĭ¨ ì²´",
+      "ห à¹īา",
+      "หà¹īา ม",
+      "使 ãģ£ãģ¦",
+      "ת ×Ļ×ij",
+      "ת×Ļ×ij ת",
+      "i á»ĥu",
+      "à¹ģ à¸Ĭม",
+      "à¹ģà¸Ĭม à¸Ľ",
+      "à¹ģà¸Ĭà¸¡à¸Ľ à¹Į",
+      "Ạ¬",
+      "ĠëĤĺ ëĿ¼",
+      "ĠÙħباشر Ø©",
+      "Ġtr Äĥm",
+      "سÙĥ ÙĪ",
+      "ĠاÙĦØ° Ùī",
+      "Ġbi ç",
+      "Ġbiç im",
+      "ت راجع",
+      "Ġоб еÑģп",
+      "ĠобеÑģп еÑĩ",
+      "ĠобеÑģпеÑĩ ива",
+      "Ġвозд ÑĥÑħ",
+      "Ñĭв аÑĤÑĮ",
+      "ÙĦ ØŃÙĤ",
+      "ĠMü dü",
+      "ĠMüdü rl",
+      "ĠMüdürl Ã¼ÄŁÃ¼",
+      "Ġyapt ır",
+      "Ġפר ס",
+      "Ġפרס ×ķ×Ŀ",
+      "Ø· ÙĪر",
+      "ÑģÑĤв оваÑĤÑĮ",
+      "ìŀ¥ ìĿĦ",
+      "à¸Ĺีà¹Īà¸Ķี à¸Ĺีà¹Īสุà¸Ķ",
+      "à¸Ńั ล",
+      "ÑĢ Ñİ",
+      "Ùħست ÙĤبÙĦ",
+      "Ñģл ÑĥÑĪ",
+      "ÑģлÑĥÑĪ а",
+      "èªį ãĤģ",
+      "Ġ׾ ×Ļ×ŀ",
+      "Ġ׾×Ļ×ŀ ×ķ×ĵ×Ļ",
+      "ת ש×ķ×ij",
+      "תש×ķ×ij ×ķת",
+      "ĠgerçekleÅŁtir il",
+      "ĠاÙĦ اتÙģاÙĤ",
+      "ĠÑĥÑĢов не",
+      "ĠÑĤ ÑĢав",
+      "Ġ×Ķ×ŀ ×ķף",
+      "ØŃÙģ اظ",
+      "ĠÙħ ÙIJ",
+      "ĠÙħÙIJ ÙĨ",
+      "ĠÙħÙIJÙĨ ÙĴ",
+      "Ġdem ás",
+      "×ŀ×ķ×ĸ ×Ļק×Ķ",
+      "ש ×Ļ×Ĺ×Ķ",
+      "Ġb ú",
+      "алÑĮ нÑĭм",
+      "ãĤı ãģŁ",
+      "ãĤıãģŁ ãģĹ",
+      "ĠاÙĦÙħÙĪ اد",
+      "ת ׼׳",
+      "×ª×Ľ×ł ×ķף",
+      "ãĥŃ ãĥĥãĤ¯",
+      "hi ếu",
+      "ĠÑĥ ме",
+      "ÙħØŃا ÙĪÙĦØ©",
+      "×IJ ×ķשר",
+      "Ġкон кÑĥÑĢ",
+      "ĠконкÑĥÑĢ Ñģ",
+      "Ġ×ŀ ×ij×Ĺ",
+      "Ġ×ŀ×ij×Ĺ ×Ļ×ł×ª",
+      "Ġan lam",
+      "Ġanlam ı",
+      "Ġli á»ĩt",
+      "Ġв Ñħод",
+      "ĠH ình",
+      "ĠÙĨ ÙĬ",
+      "ĠÙĨÙĬ ÙĪز",
+      "ãĤ¸ãĥ£ ãĥ¼",
+      "×ij ×Ļ×¥",
+      "ÑĤелÑĮ нÑĭÑħ",
+      "à¸Ĺุà¸ģ à¸Ńยà¹Īาà¸ĩ",
+      "ĠkiÅŁ inin",
+      "Ø£ Ùĥثر",
+      "ĠиÑģÑĤоÑĢ ии",
+      "Ġë³Ģ íĻĶ",
+      "פ׾ ס×ĺ",
+      "×¤×ľ×¡×ĺ ×Ļ׳×Ļ",
+      "ĠÑģ еÑĤ",
+      "ĠÑģеÑĤ и",
+      "dıģ ımız",
+      "íķĺ ëıĦë¡Ŀ",
+      "×Ķ ר",
+      "×Ķר ×ij×Ķ",
+      "ãģĻãĤĭãģĵãģ¨ ãģ¯",
+      "Ġphi ếu",
+      "تØŃ Ø³ÙĬÙĨ",
+      "ĠÅĽ rod",
+      "ĠÅĽrod ow",
+      "ĠÅĽrodow isk",
+      "ĠÑĢаÑģ Ñħод",
+      "بر ÙĬد",
+      "Ġر ÙĬ",
+      "ĠرÙĬ اÙĦ",
+      "Ġ×ķ ׼×ļ",
+      "ì§Ģ ìļĶ",
+      "׼ ×ŀ×ķ",
+      "Ġ×¢×ľ ×Ļ×Ķ×Ŀ",
+      "f ÃŃcio",
+      "Ġkar arı",
+      "tıģ ını",
+      "ĠС ов",
+      "ĠСов еÑĤ",
+      "ãģĬéĩij ãĤĴ",
+      "м еждÑĥ",
+      "междÑĥ на",
+      "междÑĥна ÑĢод",
+      "междÑĥнаÑĢод н",
+      "Ġm á»Ŀi",
+      "ĠاÙĦØ¥ ÙĬر",
+      "ĠاÙĦØ¥ÙĬر اÙĨÙĬ",
+      "ĠاÙĦرÙĪ سÙĬ",
+      "ص ÙĨد",
+      "صÙĨد ÙĪÙĤ",
+      "ĠاÙĦØ¥ÙĨ ترÙĨت",
+      "Ġt ắm",
+      "ĠÑĤак ого",
+      "Ġ×ij ׾×ķ×Ĵ",
+      "Ġü crets",
+      "Ġücrets iz",
+      "×Ĺ×ĸ ×Ļר",
+      "ìĸ´ ìķ¼",
+      "ĠPh ần",
+      "ï¼ ľ",
+      "Ġ×ĺ ×ij×¢",
+      "Ġ×ĺ×ij×¢ ×Ļ",
+      "×IJ×ŀ ×IJ",
+      "اÙĤ ÙĦ",
+      "Ġcondi ções",
+      "ÙĤات ÙĦ",
+      "ĠÑĢезÑĥлÑĮÑĤаÑĤ е",
+      "ĠÑģво ими",
+      "צ×ij ×Ļ×¢",
+      "gé ni",
+      "Ġz es",
+      "Ġzes po",
+      "Ġzespo ÅĤ",
+      "ÑĪ ив",
+      "Ġפר×ĺ×Ļ ×ķת",
+      "Ùħست Ø´Ùģ",
+      "ÙħستشÙģ Ùī",
+      "شر ع",
+      "Ġko ÅĽci",
+      "Ġ×Ķ×IJ ×Ļ׳×ĺר׳×ĺ",
+      "ĠЧ еÑĢ",
+      "поÑĩ ÑĤ",
+      "Ġactiv ités",
+      "çŁ¥ ãģ£ãģ¦",
+      "Ġ×ij ×ĸ×Ķ",
+      "Ġyüz den",
+      "ãģªãĤĬ ãģ¾ãģĽãĤĵ",
+      "Ġíĺ ¹",
+      "Ġíĺ¹ ìĿĢ",
+      "Ġ×ŀש ׳×Ķ",
+      "ĠÐĴ еÑĢ",
+      "Ġ×ij×IJ×ķת ×ķ",
+      "éĿ¢ çĻ½",
+      "éĿ¢çĻ½ ãģĦ",
+      "شر ØŃ",
+      "gr ünde",
+      "Ùģ Ø´",
+      "ÙģØ´ ÙĦ",
+      "Ġsé jour",
+      "ë´ IJ",
+      "Ġr ôle",
+      "ش عار",
+      "ем Ñĭе",
+      "ĠاÙĦج سÙħ",
+      "алÑĮ ное",
+      "Ġìĥģ íĥľ",
+      "ï¼ ¤",
+      "ë¯Ģ ë¡ľ",
+      "ĠÙĨ ÙĤØ·",
+      "ĠÙĨÙĤØ· Ø©",
+      "ãģĿãģĨ ãģł",
+      "ãģĻãĤĭ ãģ®ãģĮ",
+      "ห ู",
+      "Ġnh á»ĭ",
+      "Ġeconóm ica",
+      "ס×ĺ ×ķ×ĵ",
+      "ס×ĺ×ķ×ĵ ׳×ĺ",
+      "มี à¹Ĥà¸Ńà¸ģาส",
+      "Ġgest ão",
+      "รูà¹ī วà¹Īา",
+      "Ġlo ạt",
+      "ĠاÙĦÙħ Ùı",
+      "ĠاÙĦØŃ ÙħÙĦ",
+      "ĠاÙĦعÙħÙĦ ÙĬØ©",
+      "Ġê²ĥ ëıĦ",
+      "ĠÐľÐ¾Ñģк ва",
+      "ק×ĺ ×ķר",
+      "Ġпод ÑĢоб",
+      "ĠподÑĢоб н",
+      "Ġl Æ°ng",
+      "ت Ùģس",
+      "تÙģس ÙĬر",
+      "ĠاÙĦ بع",
+      "ĠاÙĦبع ض",
+      "ئ ت",
+      "Ðķ ÐĿ",
+      "ìĹ° 구",
+      "à¹ĥหà¹ī à¸Ħุà¸ĵ",
+      "ãģĤãĤĬ ãģ¾ãģĹãģŁ",
+      "Ġbir ka",
+      "Ġbirka ç",
+      "ĠÄ° sl",
+      "ĠÄ°sl am",
+      "çĹĽ ãģ¿",
+      "Ġh ảo",
+      "Ġм аÑı",
+      "ĠiÅŁ çi",
+      "ש ×",
+      "×©× ģ",
+      "à¸ģาร à¹Ģมืà¸Ńà¸ĩ",
+      "×ķ×Ķ ר",
+      "Ġch ó",
+      "ëĨ Ģ",
+      "Ġyan lı",
+      "Ġyanlı ÅŁ",
+      "幸 ãģĽ",
+      "×IJר×Ĵ ×ķ׳×Ļ",
+      "à¸Ńาà¸Ī าร",
+      "à¸Ńาà¸Īาร ยà¹Į",
+      "ĠинÑĦоÑĢм аÑĨиÑİ",
+      "Ðĵ Ðŀ",
+      "׳ ×Ĺש",
+      "ĠìķĮ ìķĦ",
+      "ĠÑħаÑĢакÑĤеÑĢ иÑģÑĤ",
+      "ĠÑħаÑĢакÑĤеÑĢиÑģÑĤ ик",
+      "à¸Ħุà¸ĵ สามารà¸ĸ",
+      "è¦ĭ ãģĪãĤĭ",
+      "à¸Ĭัà¸Ķ à¹Ģà¸Ī",
+      "à¸Ĭัà¸Ķà¹Ģà¸Ī à¸Ļ",
+      "ĠdziaÅĤ al",
+      "ĠdziaÅĤal noÅĽci",
+      "à¹Ĥà¸ŀ สà¸ķà¹Į",
+      "ĠÐļ ол",
+      "ĠÙģ ÙĩÙĬ",
+      "Ġ×ŀ פ׳×Ļ",
+      "Ġ×Ķק שר",
+      "Ùħر Ùĥ",
+      "ÙħرÙĥ ز",
+      "Ġho á",
+      "Ġа пп",
+      "Ġапп аÑĢаÑĤ",
+      "Ġp ami",
+      "Ġpami ÄĻ",
+      "ĠpamiÄĻ ta",
+      "Ġç ünkü",
+      "×ĵ ×ķף",
+      "ãģ¯ ãģĵãģ¡ãĤī",
+      "ĠM Ãł",
+      "ĠÙĬ ÙĤدÙħ",
+      "ĠпÑĢ ез",
+      "ĠпÑĢез иденÑĤ",
+      "à¸Ńุ à¸ķ",
+      "à¸Ńุà¸ķ สา",
+      "à¸Ńุà¸ķสา ห",
+      "à¸Ńุà¸ķสาห à¸ģรรม",
+      "ì§Ģ ìĽIJ",
+      "Ġ×IJפשר ×ķת",
+      "sch üt",
+      "schüt z",
+      "ĠTi ên",
+      "Ġsay ılı",
+      "ĠгÑĢÑĥпп Ñĭ",
+      "оÑĩ нÑĭй",
+      "Ġ×ľ×¢ ×ŀ×ķ×ĵ",
+      "Ġwr zeÅĽ",
+      "ĠwrzeÅĽ nia",
+      "ĠÄIJ ầu",
+      "à¹Ģà¸Ĥà¹īา รà¹Īวม",
+      "nız da",
+      "Ø®ÙĬ ص",
+      "Ġgü nc",
+      "Ġgünc el",
+      "ĠÙĦÙĩ Ø°Ùĩ",
+      "ĠÙĬ عتبر",
+      "lé gi",
+      "ãĤı ãģĭãĤĭ",
+      "Ġr ừng",
+      "ظ Ùĩ",
+      "ظÙĩ ÙĪر",
+      "Ġ×ŀ×ij ×Ļף",
+      "Ġ기 íĥĢ",
+      "åĪĩ ãĤĮ",
+      "lan mÄ±ÅŁ",
+      "à¸Ĺีà¹Ī มีà¸Ħวาม",
+      "Ġh á»ģ",
+      "ت ÙĪجÙĩ",
+      "ĠاÙĦØ¥ دارة",
+      "Ġú til",
+      "ס פ×ķ",
+      "à¸Ħวาม รัà¸ģ",
+      "à¹Ĥ ฮ",
+      "Ġпол иÑĤ",
+      "ĠполиÑĤ ик",
+      "Ġsat ın",
+      "ĠÅŀ imdi",
+      "×ŀ ×ķר×Ļ×Ŀ",
+      "ìķĺ ëĭ¤",
+      "×Ĺ ×ķ×ķ",
+      "×Ĺ×ķ×ķ ×Ļ×Ķ",
+      "à¸Ħà¸Ńม à¸ŀิ",
+      "à¸Ħà¸Ńมà¸ŀิ ว",
+      "à¸Ħà¸Ńมà¸ŀิว à¹Ģà¸ķà¸Ńรà¹Į",
+      "Ġا ذا",
+      "تخ اذ",
+      "ãĤ¨ ãĥ«",
+      "Ġpossibilit é",
+      "ยืà¸Ļ ยัà¸Ļ",
+      "Ġü nivers",
+      "Ġünivers ite",
+      "ĠاÙĦد ÙĪرÙĬ",
+      "ĠìķĬëĬĶ ëĭ¤",
+      "ĠìĦľ ë¡ľ",
+      "ØŃ Ø§ÙĦ",
+      "Ġë ¨",
+      "Ġë¨ ¼",
+      "Ġ먼 ìłĢ",
+      "à¸Ĺีà¹Ī à¸ĸูà¸ģ",
+      "ì§ ľ",
+      "Ġsk óry",
+      "лÑĮ ÑĨ",
+      "à¹ĥà¸Ĭà¹ī à¹Ģวลา",
+      "×ijק שת",
+      "ĠØ° ÙĪ",
+      "æĹ¥ ãĢħ",
+      "ĠкоÑĤоÑĢ ÑĥÑİ",
+      "ĠÑĥÑĢов енÑĮ",
+      "ê¹ ¨",
+      "à¹Ħ à¸Ĺ",
+      "ãĤµ ãĥĹãĥª",
+      "ãĤ¸ ãĥ§ãĥ³",
+      "ãģĻ ãģ¹ãģį",
+      "ĠG ór",
+      "ãĥĪ ãĤ¤",
+      "ãĥĪãĤ¤ ãĥ¬",
+      "ĠyaÅŁ ama",
+      "Ġdá»ĭ p",
+      "Ġb ữa",
+      "à¸ĭ ุ",
+      "Ġöl üm",
+      "ãģ£ãģ¦ ãģıãĤĭ",
+      "à¸ģาร à¸Ħà¹īา",
+      "ש ער",
+      "ĠÑĤип а",
+      "Ġг еÑĢ",
+      "ĠгеÑĢ о",
+      "רק ע",
+      "Ġu waż",
+      "Ġuważ a",
+      "ש×ŀ ף",
+      "Ġhast alık",
+      "ãĤıãĤĮ ãĤĭ",
+      "ba ÅŁÄ±",
+      "Ñĩ ÑĤо",
+      "Ġ×ij ×ŀר׼×ĸ",
+      "Ġìļ°ë¦¬ ìĿĺ",
+      "ĠÙĥاÙĨ ÙĪا",
+      "ĠØ£ بر",
+      "Ġأبر ÙĬÙĦ",
+      "ì¸ µ",
+      "à¹Ħà¸Ĥ à¹Ī",
+      "ĠÙĪ ÙĦÙĪ",
+      "à¸Ĺ ัว",
+      "à¸Ĺัว รà¹Į",
+      "ĠÙĪØ£ Ùĥد",
+      "à¸Ĭ วà¸Ļ",
+      "׾ ×ķק",
+      "æį ¨",
+      "æį¨ ãģ¦",
+      "Ġİç in",
+      "p éri",
+      "Ġy al",
+      "Ġyal nız",
+      "ÑĮÑı н",
+      "Ġg ắng",
+      "à¸ģà¹ĩ ยัà¸ĩ",
+      "ĠУкÑĢа ин",
+      "ĠÑģ ами",
+      "ĠпÑĢовед ен",
+      "à¸ķà¸ģ à¹ģà¸ķà¹Īà¸ĩ",
+      "ĠQu ân",
+      "é paration",
+      "ĠbaÅŁ ında",
+      "Ġzn ale",
+      "Ġznale ź",
+      "Ġznaleź Äĩ",
+      "ãĤ± ãĥ¼",
+      "ãĥİ ãĥ¼",
+      "à¸ĸูà¸ģ à¸ķà¹īà¸Ńà¸ĩ",
+      "ëª ¸",
+      "Ġëı Į",
+      "ĠëıĮ ìķĦ",
+      "ĠSch üler",
+      "Ġпод гоÑĤов",
+      "ĠподгоÑĤов к",
+      "ع رÙĪ",
+      "عرÙĪ ض",
+      "la ÅŁtır",
+      "ĠÑģоÑģÑĤав лÑıеÑĤ",
+      "ĠпÑĢоиз вод",
+      "ĠпÑĢоизвод ÑģÑĤва",
+      "ĠоÑģнов е",
+      "ĠØ´ ÙħاÙĦ",
+      "à¸ģร ี",
+      "ĠgörÃ¼ÅŁ me",
+      "оÑĩ ек",
+      "Ġ×Ĺ×ijר ×Ļ×Ŀ",
+      "ÙħØ® اط",
+      "Ùħخاط ر",
+      "ï¼ Ń",
+      "ר פ×IJ",
+      "ĠM ẹ",
+      "ยà¸Ńม รัà¸ļ",
+      "Ġv ết",
+      "Ø® Ø°",
+      "ĠاÙĦت Ø·",
+      "ĠاÙĦتط بÙĬÙĤ",
+      "à¸Ļ ึà¸ģ",
+      "Ġ×Ķ ×Ľ×ł×¡×ª",
+      "ĠогÑĢ ани",
+      "ĠогÑĢани Ñĩен",
+      "ĠÃĩ alÄ±ÅŁ",
+      "ĠاÙĦÙħÙĨت دÙī",
+      "à¸Īำà¸Ļวà¸Ļ มาà¸ģ",
+      "ĠÑĤоÑĢ ÑĢ",
+      "ĠÑĤоÑĢÑĢ енÑĤ",
+      "ĠìĤ´ ìķĦ",
+      "à¸ŀลัà¸ĩ à¸ĩาà¸Ļ",
+      "à¸Ĭ ัà¸Ļ",
+      "ĠÐIJн дÑĢ",
+      "Ġréalis é",
+      "×ŀש ×IJ",
+      "à¹ģ à¸Ĭ",
+      "à¹ģà¸Ĭ รà¹Į",
+      "Ġб ог",
+      "มา à¹ģลà¹īว",
+      "ĠاÙĦÙĨ ار",
+      "Ġolmad ıģı",
+      "×ĵ ×¢×Ķ",
+      "ĠÑĥ веÑĢ",
+      "ĠÑĥвеÑĢ ен",
+      "ãĤĭ ãĤĤãģ®",
+      "أ د",
+      "أد ÙĪات",
+      "Ġ×Ķ×ĸ ×ķ×Ĵ",
+      "Ø¥ عÙĦاÙħ",
+      "h á»ı",
+      "ĠNä he",
+      "ĠÑĤ еÑģÑĤ",
+      "Ġ×ŀ ×ķ׼ר",
+      "Ġë¬¸ìłľ ê°Ģ",
+      "ת ×ķצ×IJ×Ķ",
+      "m ó",
+      "mó vel",
+      "ĠاÙĦتج ارة",
+      "Ġмног иÑħ",
+      "обÑī а",
+      "Ġ×¢ סק×Ļ",
+      "ĠEdu cação",
+      "ק ש×Ļ×Ŀ",
+      "é tabl",
+      "établ issement",
+      "Ġд еле",
+      "иÑĢÑĥ еÑĤÑģÑı",
+      "آ ثار",
+      "Ġ×Ķ×ŀ ר׼×ĸ×Ļ",
+      "ãĥIJ ãĥ«",
+      "ĠвÑģÑĤÑĢ еÑĩ",
+      "ãģĴ ãĤĭ",
+      "Ġci Äħ",
+      "ĠciÄħ gu",
+      "ÙĬ ست",
+      "à¸łà¸² ว",
+      "à¸łà¸²à¸§ ะ",
+      "Ø£ Ùħر",
+      "Ġо жи",
+      "Ġожи да",
+      "Ġ ủy",
+      "ãĥŀ ãĥ«",
+      "ر اس",
+      "оÑĩ ной",
+      "ת ×Ĵ×ķ×ij×ķת",
+      "تع رÙĬÙģ",
+      "ĠÑģо ÑĨиалÑĮно",
+      "ãĤĴ éĸĭ",
+      "ĠиÑģÑģлед ова",
+      "Ġd ú",
+      "Ġdú vida",
+      "Ġsk ÅĤ",
+      "ĠskÅĤ ada",
+      "Ġhä ufig",
+      "ĠвÑĭб ÑĢ",
+      "ĠвÑĭбÑĢ аÑĤÑĮ",
+      "ãģ®ãģ§ãģ¯ãģªãģĦ ãģĭ",
+      "ĠÑģ илÑĮно",
+      "ÑĤвеÑĢж ден",
+      "ר פ",
+      "רפ ×ķ×IJ×Ķ",
+      "æĢĿ ãģĦãģ¾ãģĻ",
+      "ØŃر ص",
+      "ש×ķת ×£",
+      "Ùħس جد",
+      "à¹Ĥà¸Ĭ วà¹Į",
+      "ем ÑģÑı",
+      "в ÑĪие",
+      "Ġм л",
+      "Ġмл н",
+      "Ġ׾×Ķ ×ij×Ļ×IJ",
+      "ĠÙĬ تعÙĦÙĤ",
+      "à¸ķ ูà¹ī",
+      "Ġп ÑĢаз",
+      "ĠпÑĢаз д",
+      "ĠпÑĢазд ник",
+      "Ġн ем",
+      "Ġнем ного",
+      "Ġs Ãłng",
+      "تÙĨ سÙĬ",
+      "تÙĨسÙĬ ÙĤ",
+      "Ġtá» Ŀ",
+      "Ġмед и",
+      "ãģ« æĪ",
+      "ãģ«æĪ »",
+      "à¸Ħว à¹īา",
+      "ãģĭ ãģijãĤĭ",
+      "×ij׾ ×ķת",
+      "ĠÑįк Ñģп",
+      "ĠÑįкÑģп еÑĢÑĤ",
+      "Ġдев ÑĥÑĪ",
+      "ĠдевÑĥÑĪ к",
+      "ĠØŃ Øµ",
+      "ÙĨØ´ Ø£",
+      "ãģĮãģĤãĤĭ ãģ®ãģ§",
+      "Ġت راÙħ",
+      "ĠتراÙħ ب",
+      "أس ÙĪاÙĤ",
+      "Ġ׾פ ׳×ķת",
+      "Ġا ï»·",
+      "ãģ« ãģı",
+      "ãģ«ãģı ãģĦ",
+      "ĠØ£ عÙĦÙī",
+      "Ġ׾×Ķ ×ŀש×Ļ×ļ",
+      "rä u",
+      "ש×ŀ ×Ļ×Ŀ",
+      "åĪĨ ãģij",
+      "ãģĻ ãģ§",
+      "ãģĻãģ§ ãģ«",
+      "×Ķ׾ ׼×Ķ",
+      "×Ĺ׾ ×Ļ×£",
+      "Ġì ±ħ",
+      "Ġì±ħ ìŀĦ",
+      "à¹Ģà¸Ī ริ",
+      "à¹Ģà¸Īริ à¸į",
+      "éģĬ ãģ³",
+      "ج سد",
+      "สา à¸ĺ",
+      "สาà¸ĺ าร",
+      "สาà¸ĺาร à¸ĵ",
+      "Ġbas ın",
+      "ÑĢаР³",
+      "г ад",
+      "Ġho ÅŁ",
+      "íķ µ",
+      "×ij×Ĺ ×Ļר×Ķ",
+      "×ŀס ×ļ",
+      "Ġìłľ íĴĪ",
+      "تÙħ ÙĪÙĬÙĦ",
+      "ĠL Æ°u",
+      "ë¡ľ ë¶ĢíĦ°",
+      "Ġп об",
+      "Ġпоб ед",
+      "ÙħÙĨ Ø°",
+      "常 ãģ«",
+      "ÙĤ س",
+      "ĠاÙĦÙħ صدر",
+      "ĠÙĪاÙĦ است",
+      "Ġkh ắp",
+      "ĠاÙĦج اÙĨب",
+      "Ġng uyá»ĩn",
+      "éĸĵ éģķãģĦ",
+      "ĠÑģÑĤ ÑĢа",
+      "ĠÑģÑĤÑĢа Ñħ",
+      "ĠÑģÑĤÑĢаÑħ ов",
+      "รี à¸ļ",
+      "Ġx Æ°Æ¡ng",
+      "Ġì° ¾",
+      "Ġì°¾ ìķĦ",
+      "Ġng ại",
+      "г ал",
+      "à¸ĭ ีà¹Ī",
+      "Ġ×ij פ×Ļ×Ļס×ij×ķק",
+      "Ц енÑĤÑĢ",
+      "Ġaval iação",
+      "Ġeconóm ico",
+      "×ĸ ף",
+      "ĠÐľ ак",
+      "Ġinter és",
+      "à¸ģล ิà¹Īà¸Ļ",
+      "ÑģÑĤÑĮ Ñİ",
+      "ĠÄij Æ°Æ¡ng",
+      "å¼· ãģı",
+      "ĠKh ách",
+      "à¹Ģà¸Ļืà¹īà¸Ń หา",
+      "ĠYaz ı",
+      "è²· ãģ£ãģ¦",
+      "Ðł Ðķ",
+      "à¹Ģà¸ŀิà¹Īม à¸Ĥึà¹īà¸Ļ",
+      "สม à¸ļู",
+      "สมà¸ļู รà¸ĵà¹Į",
+      "Ġм иÑĢов",
+      "×Ĵ ׳×Ļ×Ŀ",
+      "ĠÄij ức",
+      "à¸Ń ารà¹Į",
+      "ص اص",
+      "ãģĬ ãĤĪ",
+      "ãģĬãĤĪ ãģ³",
+      "ÃªÌ ī",
+      "ĠاÙĦÙħؤ تÙħر",
+      "ĠاÙĦÙħر ØŃÙĦØ©",
+      "สà¸Ńà¸ļ à¸ĸาม",
+      "Ġà¸Īาà¸ģ à¸Ļัà¹īà¸Ļ",
+      "Ġت عد",
+      "ãģĿãģ® ãģŁãĤģ",
+      "Ġkh áng",
+      "à¸Ļ ิà¸Ķ",
+      "ãĥĬ ãĥ³",
+      "ëĦ¤ ìļĶ",
+      "ĠاÙĦ اØŃت",
+      "ĠاÙĦاØŃت ÙĦاÙĦ",
+      "ìļ ķ",
+      "Ġмод ели",
+      "ĠпÑĢоÑĨ енÑĤ",
+      "à¸ŀวà¸ģ à¹Ģรา",
+      "Ġ×Ķצ ×ĵ",
+      "Ġ×Ķצ×ĵ ×ĵ×Ļ×Ŀ",
+      "ständ e",
+      "׳ ×Ĵר",
+      "Ġdot yc",
+      "Ġdotyc zÄħ",
+      "ĠdotyczÄħ ce",
+      "ĠÅĽ wiÄĻt",
+      "×ŀר ×Ķ",
+      "ãģĻãģĶ ãģĦ",
+      "ãĥĩãĤ£ ãĥ³ãĤ°",
+      "à¸ģาร สรà¹īาà¸ĩ",
+      "ë Ĥ¬",
+      "Ġì°¸ ìŬ",
+      "Ñģ Ñħ",
+      "ÑģÑħ ем",
+      "ÙħÙĪ س",
+      "Ġn ấu",
+      "Ġ׾×ŀ×¢ ׾×Ķ",
+      "à¹Ģà¸Ľ à¹īา",
+      "à¹Ģà¸Ľà¹īา หมาย",
+      "Ġmù i",
+      "ائ ز",
+      "íĽ Ī",
+      "×Ĺ×ij ×ķר×Ķ",
+      "à¸ľà¸¹à¹ī à¹ĥà¸Ĭà¹ī",
+      "Ġpa ź",
+      "Ġpaź dzi",
+      "Ġpaździ ern",
+      "Ġpaździern ika",
+      "ลà¸ĩ à¹Ħà¸Ľ",
+      "ÙĤ اع",
+      "Ġch áºŃm",
+      "Ġözellik leri",
+      "ĠÄIJ o",
+      "ĠÄIJo Ãłn",
+      "ж ение",
+      "Ġh ẳ",
+      "Ġhẳ n",
+      "ĠaÅŁ k",
+      "ï½ į",
+      "ãĥij ãĤ¹",
+      "×Ķ×ķר ×IJ×ķת",
+      "ĠÅ »",
+      "ĠÅ» y",
+      "×ŀ×ĸ ׾",
+      "ĠÑĥ кÑĢа",
+      "ĠÑĥкÑĢа ин",
+      "à¹Ģà¸Ĭ ิ",
+      "à¹Ģà¸Ĭิ à¸į",
+      "Ðł Ðĺ",
+      "ĠzwiÄħz ku",
+      "×Ķ×Ĺ׾×ĺ ת",
+      "ãĤĵãģ§ãģĻ ãĤĪãģŃ",
+      "ãģ¦ ãģĬãĤĬ",
+      "лож иÑĤÑĮ",
+      "×ŀ ×ķ׳×Ļ×Ŀ",
+      "ฮ ิ",
+      "ì° ¬",
+      "ĠاÙĦÙħØ´ ترÙĥ",
+      "ĠdÃ¼ÅŁ ük",
+      "аг енÑĤ",
+      "ĠاÙĦØ£ سبÙĪع",
+      "ĠÙĤ رÙĬب",
+      "ин д",
+      "инд ив",
+      "индив ид",
+      "индивид Ñĥ",
+      "индивидÑĥ алÑĮн",
+      "för der",
+      "Ġseç en",
+      "Ġseçen ek",
+      "Ġét ant",
+      "ĠлÑİб им",
+      "каз ÑĭваеÑĤ",
+      "ว ิà¸Ļ",
+      "Ġ×Ķ×ij ×IJ×Ļ×Ŀ",
+      "Ġд ов",
+      "Ġдов олÑĮ",
+      "ĠдоволÑĮ но",
+      "×¢×ĵ ×Ļ×£",
+      "Ġok re",
+      "Ġokre ÅĽ",
+      "ĠokreÅĽ lon",
+      "Ġت رÙĬد",
+      "à¹Ģมืà¹Īà¸Ń วัà¸Ļà¸Ĺีà¹Ī",
+      "ãĤĪ ãģĭãģ£ãģŁ",
+      "Cum h",
+      "Cumh ur",
+      "Cumhur ba",
+      "Cumhurba ÅŁ",
+      "CumhurbaÅŁ kan",
+      "CumhurbaÅŁkan ı",
+      "Ġn ợ",
+      "à¸ľà¸¹à¹ī à¹Ģลà¹Īà¸Ļ",
+      "Ġcompl ète",
+      "à¹Ģà¸ŀ ศ",
+      "د ÙIJ",
+      "Ġdü z",
+      "Ġdüz ey",
+      "ãģ§ãģĤãĤĭ ãģĵãģ¨",
+      "ext érieur",
+      "× ³",
+      "Ġinform ação",
+      "ãĤ¯ãĥª ãĥĭãĥĥãĤ¯",
+      "ĠPub li",
+      "ĠPubli é",
+      "ר ×ķ×ĵ",
+      "à¸Ħวาม à¸Ľà¸¥à¸Ńà¸Ķà¸łà¸±à¸¢",
+      "ĠØ£ÙĬ ض",
+      "ĠØ£ÙĬض Ùĭا",
+      "ت سبب",
+      "ãģ¤ ãĤĤãĤĬ",
+      "из ма",
+      "à¸Ĥึà¹īà¸Ļ à¹Ħà¸Ľ",
+      "Ùĥ ÙIJ",
+      "ÙĦ ÙĪÙħ",
+      "Ġש צר",
+      "Ġשצר ×Ļ×ļ",
+      "ãģ¯ ãĤĤãģ¡ãĤįãĤĵ",
+      "Ġк ан",
+      "Ġкан ал",
+      "ãģ«ãģª ãģ£ãģ¦ãģĦãģ¾ãģĻ",
+      "ĠاÙĦØ£ Ùĥثر",
+      "ت اØŃ",
+      "ÙĨت Ùĩ",
+      "ÙĨتÙĩ اء",
+      "ا ÙĪÙĬØ©",
+      "ĠBug ün",
+      "н Ñģкого",
+      "à¸Ķ à¹Īวà¸Ļ",
+      "é volution",
+      "ãģ£ãģ¦ ãģĦãģ¾ãģĹãģŁ",
+      "ãĤ ħ",
+      "ĠV Æ°Æ¡ng",
+      "à¸łà¸²à¸ŀ ย",
+      "à¸łà¸²à¸ŀย à¸Ļ",
+      "à¸łà¸²à¸ŀยà¸Ļ à¸ķรà¹Į",
+      "Ġ×Ķ צ׾×Ļ×Ĺ",
+      "ĠاÙĦإسÙĦاÙħ ÙĬ",
+      "ÙĦÙĬ ب",
+      "Ġed ição",
+      "ÑģÑĤÑĢ ел",
+      "Ġkh úc",
+      "ÙĨÙħÙĪ Ø°",
+      "ÙĨÙħÙĪØ° ج",
+      "׾ צ×Ķ",
+      "ÑģÑĤав ил",
+      "à¸ĸ า",
+      "สรà¹īาà¸ĩ à¸Ħวาม",
+      "ãģĦ ãģ£ãģ±",
+      "ãģĦãģ£ãģ± ãģĦ",
+      "ÑģÑĤав лен",
+      "ĠاÙĦ ÙĤدس",
+      "Ġng ược",
+      "ب خ",
+      "ส หร",
+      "สหร ั",
+      "สหรั à¸IJ",
+      "ĠØ£ غ",
+      "Ġأغ سط",
+      "Ġأغسط س",
+      "ãģĨ ãģ¾",
+      "ãģĨãģ¾ ãģı",
+      "ĠêµŃ ìłľ",
+      "ØŃض ار",
+      "Ġd ừng",
+      "æĬ¼ ãģĹ",
+      "ت ÙĪا",
+      "تÙĪا جد",
+      "ש×ŀ ×Ĺ×Ķ",
+      "ãģı ãĤĵ",
+      "Ġ×ij×¢ צ",
+      "Ġ×ijעצ ×Ŀ",
+      "×ŀ ׳×Ļ×ķת",
+      "×ķ ×Ļ×ĵ",
+      "×ķ×Ļ×ĵ ×IJ×ķ",
+      "à¸Ĭ ิà¸ĩ",
+      "Ġprac ÄĻ",
+      "Ġз аÑĤ",
+      "ĠзаÑĤ ем",
+      "ĠìŀIJ ìľł",
+      "Ġì¤ Ģ",
+      "Ġì¤Ģ ë¹Ħ",
+      "Ġb áºŃ",
+      "ĠbáºŃ c",
+      "Ġ×Ķ×ŀ צ×ij",
+      "ĠÙĤ ÙĬÙħØ©",
+      "à¹Ģà¸Ń à¹Ģà¸Ĭ",
+      "à¹Ģà¸Ńà¹Ģà¸Ĭ ีย",
+      "Ġperch è",
+      "ĠاÙĦع سÙĥر",
+      "ĠاÙĦعسÙĥر ÙĬØ©",
+      "ج ÙĬب",
+      "ëŀ µ",
+      "Ùħ Ùĩر",
+      "ÙħÙĩر جاÙĨ",
+      "Ùħ راÙĥ",
+      "ÙħراÙĥ ز",
+      "Ġод нако",
+      "à¸Ķี à¹Ĩ",
+      "Ġצ פ×ķ",
+      "Ġkullan ılan",
+      "Ġк ино",
+      "ãĥĨãĤ£ ãĥ³ãĤ°",
+      "ĠGi Ỽi",
+      "ت ÙĪز",
+      "تÙĪز ÙĬع",
+      "ย ิà¸Ļ",
+      "ยิà¸Ļ à¸Ķี",
+      "Ġc Åĵur",
+      "ĠiÅŁ aret",
+      "Ġ×ij×¢ ×ĸר",
+      "Ġ×ij×¢×ĸר ת",
+      "Ġп аÑĨи",
+      "ĠпаÑĨи енÑĤ",
+      "ãģ¿ãģŁãģĦ ãģ§ãģĻ",
+      "в ез",
+      "ли на",
+      "од е",
+      "Ġ×IJ×ķת ף",
+      "dıģ ınız",
+      "ĠÐIJ в",
+      "ĠÐIJв ÑĤоÑĢ",
+      "ï¼ ®",
+      "ĠC ần",
+      "ĠاÙĦا Ø®",
+      "ĠاÙĦاخ بار",
+      "Ġê±° ìĿĺ",
+      "Ġat enção",
+      "Ġgeld iÄŁi",
+      "ãĤª ãĤ¹",
+      "ãĤªãĤ¹ ãĤ¹",
+      "ãĤªãĤ¹ãĤ¹ ãĥ¡",
+      "ев Ñĭе",
+      "кÑĢÑĭ л",
+      "à¹Ģà¸Ĭ ียà¸ĩ",
+      "à¹Ģà¸Ĭียà¸ĩ à¹ĥหมà¹Ī",
+      "Ġmar ço",
+      "ĠاÙĦÙħ ادة",
+      "Ġг ол",
+      "Ġsprzeda ży",
+      "Ġíķ´ ê²°",
+      "ĠÐķ го",
+      "ê¹ Ģ",
+      "Ġ׾ק×ij׾ ת",
+      "ĠاÙĦÙģ ÙĨاÙĨ",
+      "Ġcomunic ación",
+      "à¹Ģสà¹īà¸Ļ à¸Ĺาà¸ĩ",
+      "íĺ ¹",
+      "à¸Ĭ ำ",
+      "à¸Ĭำ ระ",
+      "Ġ׼ ×IJ×ŀ",
+      "Ġ׼×IJ×ŀ ×ķר",
+      "à¸Ĭ à¹Īาà¸ĩ",
+      "ز Ùĩر",
+      "Ġklient ów",
+      "ива ÑİÑĤ",
+      "ан г",
+      "׳ ×ļ",
+      "Ġg á»įn",
+      "Ãľ R",
+      "ìĺģ ìĥģ",
+      "Ġغ زة",
+      "ìĿĮ ìĿĦ",
+      "Ġbez po",
+      "Ġbezpo ÅĽ",
+      "ĠbezpoÅĽ redni",
+      "ĠاÙĦÙħ ÙĪا",
+      "ĠاÙĦÙħÙĪا Ø·ÙĨ",
+      "ĠاÙĦÙħÙĪاطÙĨ ÙĬÙĨ",
+      "ãĤĮ ãģ¾ãģĻ",
+      "ĠмаÑĤ Ñĩ",
+      "×IJ ×ķף",
+      "Ġر سÙħÙĬ",
+      "ĠÑįк он",
+      "ĠÑįкон ом",
+      "ĠÑįконом иÑĩеÑģк",
+      "ãĥľ ãĥ¼",
+      "Ġд иÑĢ",
+      "ĠдиÑĢ екÑĤоÑĢ",
+      "ĠÑģк оÑĢо",
+      "à¸ļ ำ",
+      "à¸ļำ ร",
+      "à¸ļำร ุà¸ĩ",
+      "ĠÑĦ ÑĥÑĤ",
+      "ĠÑĦÑĥÑĤ бол",
+      "Ġ×IJ ×Ļ׾",
+      "Ġì¤ij êµŃ",
+      "ìľ ¤",
+      "eÄŁ e",
+      "à¹Ħ à¸ģà¹Ī",
+      "tra î",
+      "traî n",
+      "ĠÑĤ ÑĢÑĥб",
+      "à¹Ģà¸ļ ื",
+      "à¹Ģà¸ļื à¹īà¸Ńà¸ĩ",
+      "à¹ģม à¸Ļ",
+      "ĠتØŃ Ø¯ÙĬØ«",
+      "Ġ׼ עת",
+      "ØŃ Ø§Ø³Ø¨",
+      "lı ģa",
+      "ק×Ļ ×Ļ×ŀ×Ļ×Ŀ",
+      "оÑģÑĤ ÑĮÑİ",
+      "à¸Ŀ ั",
+      "à¸Ŀั à¹Īà¸ĩ",
+      "Ø´ غÙĦ",
+      "ìĽ ¹",
+      "Ġкажд ого",
+      "Ġbölüm ü",
+      "หà¸Ļ ี",
+      "Ġistedi ÄŁi",
+      "Ġtr Æ°ng",
+      "ãĥ Į",
+      "ฮ à¸Ń",
+      "Ø£ÙĨ Ø´",
+      "Ø£ÙĨØ´ طة",
+      "ĠاÙĦÙħ سÙĬ",
+      "ĠاÙĦÙħسÙĬ ØŃ",
+      "ลัà¸ģษ à¸ĵà¹Į",
+      "Ġn á»Ńa",
+      "à¸Ĺีà¹Ī à¸ķà¹īà¸Ńà¸ĩà¸ģาร",
+      "ÑĪ ек",
+      "л Ñij",
+      "Ġש ×Ļ×Ķ",
+      "Ġש×Ļ×Ķ ×Ļ×Ķ",
+      "Ġkhu ôn",
+      "ĠÑĤÑĢеб ованиÑı",
+      "Ġ×ľ×¢ ×ĸ×ķר",
+      "ĠاÙĦع Ùħر",
+      "ราà¸Ħา à¸ĸูà¸ģ",
+      "ÙĩÙı ÙħÙĴ",
+      "ü st",
+      "üst ü",
+      "Ġден ег",
+      "Ġn ạ",
+      "à¸Ĥà¸Ļ ม",
+      "Ġбл аг",
+      "Ġблаг од",
+      "Ġблагод аÑĢ",
+      "ĠблагодаÑĢ Ñı",
+      "Ø¥ سÙĦاÙħ",
+      "à¸Ļิ ว",
+      "çŁ¥ ãĤīãģªãģĦ",
+      "Ø« ÙĤØ©",
+      "Ġг олоÑģ",
+      "×IJ×ķר ×Ĺ",
+      "Ġtr ứng",
+      "Ġод ном",
+      "ĠkoÅĦ cu",
+      "Ġ×ķ רק",
+      "Wi ÄĻ",
+      "WiÄĻ cej",
+      "Ġ×IJ ×Ļ׼×ķת",
+      "Ġ×IJ×Ļ׼×ķת ×Ļ",
+      "Ñģ оÑģ",
+      "Ġje żeli",
+      "以ä¸ĭ ãģ®",
+      "å°ı ãģķ",
+      "å°ıãģķ ãģª",
+      "олог ии",
+      "Ġоб ÑģлÑĥж",
+      "ĠобÑģлÑĥж ива",
+      "Ùĥت ابة",
+      "Ġê´Ģ ìĭ¬",
+      "×¢ ש×Ļר",
+      "Ġaras ındaki",
+      "ĠÑĢай она",
+      "ÙĪا جب",
+      "Ġ×ij×Ĺ×Ļ ×Ļ",
+      "íķ´ 주",
+      "Ġg óc",
+      "ай л",
+      "ĠT ình",
+      "æļ® ãĤī",
+      "æļ®ãĤī ãģĹ",
+      "æĻĤ ãģ«ãģ¯",
+      "ĠгоÑĢод е",
+      "Ġ׼×IJ ×Ļ׾",
+      "Ġ׼×IJ×Ļ׾ ×ķ",
+      "ĠC á»Ļng",
+      "ãģ©ãģĨ ãģĹãģ¦ãĤĤ",
+      "×Ĺ ×ķ×£",
+      "تØŃ Ø±Ùĥ",
+      "ĠÑģлов ам",
+      "à¸Īะ à¸Ĭà¹Īวย",
+      "ĠاÙĦÙħست ÙĤبÙĦ",
+      "ÙĤ ض",
+      "ÙĤض ÙĬ",
+      "×ijס ×ķפ",
+      "×ijס×ķפ ×ķ",
+      "iÄĻ Äĩ",
+      "ĠY ıl",
+      "Ø´ ÙĬØ®",
+      "à¸Ħุà¸ĵ à¸Īะ",
+      "ש×ŀ ×ķת",
+      "Ġت عرض",
+      "Ġanál ise",
+      "ĠÑģоб иÑĢа",
+      "à¹Ģà¸ŀ à¸Ĭ",
+      "à¹Ģà¸ŀà¸Ĭ ร",
+      "Ġв ели",
+      "Ġвели к",
+      "สั à¹īà¸Ļ",
+      "Ġpop ulação",
+      "รà¹Īวม à¸ģัà¸Ļ",
+      "×Ĺ ×ŀ",
+      "×Ĺ×ŀ ×Ļש×Ļ",
+      "ס ×Ļס",
+      "åĨħ ãģ§",
+      "Ġsob Äħ",
+      "ĠY ay",
+      "ĠYay ın",
+      "ãĥ¡ ãĥĭãĥ¥ãĥ¼",
+      "ĠпÑĢедоÑģÑĤав лÑı",
+      "ãģł ãģ¨æĢĿãģĨ",
+      "Ġê³ł ê°Ŀ",
+      "Ġод ним",
+      "à¹ĥà¸Ļ à¹Ģรืà¹Īà¸Ńà¸ĩ",
+      "Ġs á»ķ",
+      "ĠÐĹ Ð´ÐµÑģÑĮ",
+      "Ġизмен ениÑı",
+      "ĠìĿ¼ ìĿĦ",
+      "ãģªãģ® ãģł",
+      "клад Ñĭва",
+      "ÑĢ ма",
+      "Ġ×ķ×ij ׼׾",
+      "تأ ÙħÙĬÙĨ",
+      "ĠпÑĢи ÑıÑĤ",
+      "ĠпÑĢиÑıÑĤ н",
+      "Ùħ Ùħار",
+      "ÙħÙħار سة",
+      "ãģ¨ãģª ãģ£ãģ¦",
+      "Ġج ÙħÙĬÙĦ",
+      "Ġì§ Ī",
+      "Ġì§Ī 문",
+      "Ġquest ão",
+      "i é",
+      "ié ndo",
+      "หà¹īà¸Ńà¸ĩ à¸ŀัà¸ģ",
+      "ãĥij ãĥ¼ãĥĪ",
+      "ÑĤвеÑĢж да",
+      "н Ñģкой",
+      "з ал",
+      "มุ à¹Īà¸ĩ",
+      "á» Ĭ",
+      "Ġ×Ķ×IJ×Ĺר ×ķ׳×Ķ",
+      "ĠTh Æ°",
+      "주 민",
+      "ĠاÙĦع ب",
+      "év én",
+      "évén ement",
+      "ÙĤÙĪ اعد",
+      "د Ùı",
+      "ĠìķĬ ìĬµëĭĪëĭ¤",
+      "Ġë³´ 기",
+      "Ġyapıl ması",
+      "à¹Ģร าà¸ģ",
+      "à¹Ģราà¸ģ à¹ĩ",
+      "ØŃ Ø°Ø±",
+      "ÙĤ صر",
+      "ãģ¦ãģĹãģ¾ ãģĦãģ¾ãģĹãģŁ",
+      "Ġà¹Ģà¸Ľà¹ĩà¸Ļ à¸ķà¹īà¸Ļ",
+      "ãģ¨ ãģ«",
+      "ãģ¨ãģ« ãģĭ",
+      "ãģ¨ãģ«ãģĭ ãģı",
+      "н ÑĨе",
+      "зв Ñĥк",
+      "ãģĹãĤĪãģĨ ãģ¨",
+      "ĠاÙĦصØŃ ÙĬØ©",
+      "Ġש×Ķ ×Ļ×ķ",
+      "ĠDi ÄŁer",
+      "ÙĤÙĦ ÙĤ",
+      "ãĤ¸ãĥ£ ãĥ³",
+      "Ġr á»Ŀi",
+      "Ġл еÑĩ",
+      "ĠлеÑĩ ениÑı",
+      "تب اد",
+      "تباد ÙĦ",
+      "צ פ×Ķ",
+      "à¸Ħวาม à¹Ģหà¹ĩà¸Ļ",
+      "ĠØ´ ب",
+      "Ġشب ÙĥØ©",
+      "ר ×Ļק",
+      "Ùħ عد",
+      "Ùħعد ات",
+      "dıģ ında",
+      "Ġ×ijש ׳×Ļ×Ŀ",
+      "Ġ×Ķ ×Ļשר×IJ׾",
+      "Ġ×Ķ×Ļשר×IJ׾ ×Ļת",
+      "Ġsı nav",
+      "׳צ ×Ļ×Ĵ",
+      "วัà¸ķ à¸ĸุ",
+      "ĠاÙĦبر ÙĦÙħ",
+      "ĠاÙĦبرÙĦÙħ اÙĨ",
+      "t ivitÃł",
+      "ãĤĵãģł ãĤįãģĨ",
+      "ק×Ļ ×Ļ×ŀ",
+      "ÙĦÙĬ Ùĥ",
+      "ĠÄij ò",
+      "ĠÄijò i",
+      "ĠÐĺн ÑĤеÑĢ",
+      "ĠÐĺнÑĤеÑĢ неÑĤ",
+      "ãģ«ãģ¨ãģ£ãģ¦ ãģ¯",
+      "ãģ£ ãģĵ",
+      "ק ×ķס",
+      "ست ØŃÙĤ",
+      "æķĻ ãģĪãģ¦",
+      "ãĥĢ ãĥ¡",
+      "ĠÙħÙĨ زÙĦ",
+      "à¹Ģà¸ĭ à¹ĩà¸Ļ",
+      "使 ãģĪãĤĭ",
+      "è¦ĭ ç©į",
+      "è¦ĭç©į ãĤĤãĤĬ",
+      "Ø£ Ùģ",
+      "Ø£Ùģ Ùĥار",
+      "Ġиг ÑĢов",
+      "ĠигÑĢов Ñĭе",
+      "Ġm ÄĻż",
+      "ĠmÄĻż czy",
+      "ĠmÄĻżczy zn",
+      "ĠاÙĦØŃ ÙĤÙĬÙĤÙĬ",
+      "ع بر",
+      "׼×ķ׾ ׳×ķ",
+      "íĿ ¥",
+      "×ŀ×IJ ×ķ×Ĺר",
+      "خت ص",
+      "ãĥŀ ãĥŀ",
+      "Ġ×IJ×Ĺ ×ķ×ĸ",
+      "í ĮĢ",
+      "Ġr á»iji",
+      "Ġв ÑĤоÑĢ",
+      "ĠвÑĤоÑĢ ой",
+      "Ġl ẫn",
+      "пÑĢ ом",
+      "пÑĢом ÑĭÑĪ",
+      "пÑĢомÑĭÑĪ лен",
+      "пÑĢомÑĭÑĪлен н",
+      "ĠоÑĤноÑĪ ениÑı",
+      "Ġs ứ",
+      "Ġм обилÑĮ",
+      "ĠмобилÑĮ н",
+      "ĠÑįÑĤ омÑĥ",
+      "Ġt ạp",
+      "ĠìĤ¬ ê±´",
+      "ĠìķĮ 볤",
+      "Ùĥ Ùı",
+      "ÙĥÙı ÙħÙĴ",
+      "Ġק ×ķר×Ķ",
+      "ĠÑĦ иÑĢ",
+      "ĠÑĦиÑĢ м",
+      "Ġsık ıntı",
+      "׳ ׼",
+      "׳׼ ×ķף",
+      "ÙĪÙĦÙĪج ÙĬ",
+      "ØŃ Ø§ÙĨ",
+      "Ġlo ạn",
+      "Ġ×IJ׾ ×£",
+      "Ġm ắn",
+      "abh äng",
+      "abhäng ig",
+      "ĠÑĥÑĢов нÑı",
+      "Ġ׾×ij×ĵ ×ķק",
+      "ÙĬ ÙħÙĨ",
+      "lay ın",
+      "Ġh ải",
+      "Ġзав од",
+      "ĠìķĦ 주",
+      "สà¸ĸ า",
+      "สà¸ĸา à¸ļัà¸Ļ",
+      "Ġgüven lik",
+      "à¹Ģà¸Ķ à¹Īà¸Ļ",
+      "×ij×ĵ ק",
+      "Ġë Ī",
+      "ĠëĪ Ħ",
+      "ĠëĪĦ 구",
+      "éĩįè¦ģ ãģª",
+      "รà¸Ńà¸ĩ รัà¸ļ",
+      "sch lie",
+      "schlie ÃŁen",
+      "Ġìĸ ¼",
+      "Ġìĸ¼ ë§Ī",
+      "Ġìĸ¼ë§Ī ëĤĺ",
+      "ÑĤи ки",
+      "íķľëĭ¤ ê³ł",
+      "ãģłãģ£ãģŁ ãĤī",
+      "Ġ×Ķ ×Ļ×ĺ×ij",
+      "ãģªãģijãĤĮãģ° ãģªãĤīãģªãģĦ",
+      "â Ì",
+      "Ã¢Ì £",
+      "Ġph ạt",
+      "ak Ä±ÅŁ",
+      "ãģ¦ãģĹãģ¾ ãģĦãģ¾ãģĻ",
+      "à¹Ģà¸ĭ à¹ĩ",
+      "ĠС егоднÑı",
+      "Ġinsan ların",
+      "Ġdévelop pe",
+      "ת פר",
+      "תפר ×Ļ×ĺ",
+      "اÙĨت شار",
+      "ê° ij",
+      "Fran çois",
+      "Ø£ÙĦ ع",
+      "Ø£ÙĦع اب",
+      "ãĤĴ è¶ħ",
+      "ãĤĴè¶ħ ãģĪ",
+      "Ġê°Ļ ìĬµëĭĪëĭ¤",
+      "ãĤ³ ãĥ¬",
+      "ĠмеÑģÑı ÑĨев",
+      "íĮ ħ",
+      "ĠاÙĦج اÙħعة",
+      "ìĿ¸ íĦ°",
+      "ìĿ¸íĦ° ëĦ·",
+      "×ĵר ×ķש",
+      "ĠÙĪØ£ شار",
+      "ĠпÑĢав ила",
+      "ãģĿãģĵ ãģ«",
+      "×Ĺ ×ŀ×ĵ",
+      "à¹Ģหà¸ķุ à¸ģารà¸ĵà¹Į",
+      "Ġê²½ íĹĺ",
+      "ãģ¶ ãĤĬ",
+      "׾ ש",
+      "׾ש ×ķף",
+      "à¹Ģ à¸ĸ",
+      "ĠDo ÄŁu",
+      "ĠиÑģполÑĮзов ание",
+      "Ġçoc uÄŁu",
+      "магазин е",
+      "ĠÄiji á»ĥn",
+      "Ġas lı",
+      "Ġaslı nda",
+      "Ġdoen ça",
+      "Ġس اع",
+      "Ġساع ات",
+      "ĠиÑģполÑĮзов аниÑı",
+      "ר ×ķצ×Ļ×Ŀ",
+      "ĠзнаÑĩ иÑĤ",
+      "ĠÑĢаР¼",
+      "ĠÑĢам каÑħ",
+      "거 리",
+      "Ġп ÑĭÑĤа",
+      "ãĥģ ãĥ³",
+      "Ġпо Ñģк",
+      "ĠпоÑģк олÑĮ",
+      "ĠпоÑģколÑĮ кÑĥ",
+      "إ بر",
+      "إبر اÙĩ",
+      "إبراÙĩ ÙĬÙħ",
+      "ĠÑĤÑĢ еÑħ",
+      "ĠGen ç",
+      "س ÙĪÙģ",
+      "Ġve ÃŃculo",
+      "ĠNg ân",
+      "ĠоÑĩеÑĢ едÑĮ",
+      "à¸Ħร ึà¹Īà¸ĩ",
+      "×IJ ×ij×Ļ",
+      "à¸ķ à¹īม",
+      "ãĤĴè¡Į ãģĦ",
+      "ĠاÙĦساب ÙĤØ©",
+      "на ÑĨи",
+      "наÑĨи она",
+      "наÑĨиона лÑĮн",
+      "Ġgest ión",
+      "ت ÙĤد",
+      "ĠاÙĦبÙĬ اÙĨ",
+      "ĠاÙĦبÙĬاÙĨ ات",
+      "ĠاÙĦ اÙĨتخاب",
+      "ĠاÙĦاÙĨتخاب ات",
+      "à¹Ģà¸Ĭ à¹Īา",
+      "×ĵ ×IJ×Ĵ",
+      "Ġ׾×Ĵ ×ŀר×Ļ",
+      "Ġت ØŃتاج",
+      "Ġth ôn",
+      "à¸ķ à¹īà¸Ńà¸Ļ",
+      "à¸ķà¹īà¸Ńà¸Ļ รัà¸ļ",
+      "女 ãģ®",
+      "女ãģ® åŃIJ",
+      "Ġth ợ",
+      "Ø· ØŃÙĨ",
+      "ารà¹Į à¸Ķ",
+      "ת ×ŀ×Ļ×ĵ",
+      "ĠÑģам Ñĭм",
+      "Ġìĭľ íĸī",
+      "إ صد",
+      "إصد ار",
+      "ĠNgh á»ĩ",
+      "ìķ ķ",
+      "س ئ",
+      "سئ ÙĦ",
+      "à¸Ń าร",
+      "à¸Ńาร ม",
+      "à¸Ńารม à¸ĵà¹Į",
+      "à¹ģ ฮ",
+      "׳×ĺ ׾",
+      "Ġì¢ĭ ìķĦ",
+      "×ķ׾ ׾",
+      "Ġ×ij ×Ľ×ª×ij",
+      "ãĤ« ãĥ©",
+      "צע ×Ļר×Ļ×Ŀ",
+      "تعب ÙĬر",
+      "Ġ×ŀ קר×Ķ",
+      "ĠÑĦак ÑĤоÑĢ",
+      "Ġت ÙħاÙħ",
+      "ĠتÙħاÙħ ا",
+      "ëį ķ",
+      "Ġv Æ°á»Ŀ",
+      "ĠvÆ°á»Ŀ n",
+      "Ġd Ä±ÅŁÄ±",
+      "ãģĦ ãģ¡",
+      "Ġ׾ק ׳×ķת",
+      "ĠاÙĦع ÙĦاÙĤات",
+      "п Ñĥб",
+      "пÑĥб ли",
+      "Ø¥ ÙĬÙħ",
+      "Ø¥ÙĬÙħ اÙĨ",
+      "à¸Ńำ à¸Ļา",
+      "à¸Ńำà¸Ļา à¸Ī",
+      "åIJ« ãģ¾ãĤĮ",
+      "ãĤĭ ãģŁãĤģãģ«",
+      "ס ×Ĵ",
+      "ס×Ĵ ׳×ķף",
+      "تØŃ Ø¯ÙĬ",
+      "Ġaup rès",
+      "ĠاÙĦج Ùĩا",
+      "ĠاÙĦجÙĩا ز",
+      "Ġ×ŀ ת×Ĺת",
+      "ен нÑĥÑİ",
+      "Ġз им",
+      "à¸ģา à¹ģà¸Ł",
+      "Ġ×ijת ×ķר",
+      "Ġngh è",
+      "Ġnghè o",
+      "ĠÐĽ Ñİ",
+      "ĠÐĽÑİ Ð±",
+      "תק צ×Ļ×ij",
+      "×ŀ×¢ ש×Ķ",
+      "ĠاÙĦبÙĬ ت",
+      "צ ×Ļפ",
+      "ĠобÑıз ан",
+      "ĠM á»Ĺi",
+      "ĠТ ÑĥÑĢ",
+      "ĠÙĪب اÙĦت",
+      "ĠÙĪباÙĦت اÙĦÙĬ",
+      "Ġdéc ision",
+      "Ġب د",
+      "Ġبد أت",
+      "Ġc ục",
+      "Ġb ask",
+      "Ġbask ı",
+      "Ġhat ırl",
+      "Ġhatırl a",
+      "å°ı ãģķãģĦ",
+      "Ġgerçek ten",
+      "à¸ľ ัà¸ģ",
+      "åı¯èĥ½ ãģª",
+      "×ŀ×IJ ס",
+      "Ġcr ÃŃtica",
+      "ĠìĿĺ ìĽIJ",
+      "عÙĤ ÙĪد",
+      "×ĺ ׼׳",
+      "×ĺ׼׳ ×ķ׾×ķ×Ĵ×Ļ×Ķ",
+      "è¨Ģ ãģĪãģ°",
+      "ĠÙĤ ÙĨا",
+      "ĠÙĤÙĨا Ø©",
+      "ĠìĿ´ê²ĥ ìĿĢ",
+      "ت صر",
+      "à¸Ł ัà¸Ļ",
+      "ĠÑĢе ÑĨеп",
+      "ĠÑĢеÑĨеп ÑĤ",
+      "ĠبÙĨ Ùģس",
+      "ÑĢо ÑĪ",
+      "ĠмаÑĢ ÑĤа",
+      "Ġson ras",
+      "Ġsonras ı",
+      "×ķ×ij ש",
+      "ãĥª ãĤ¹ãĤ¯",
+      "ĠFranç ais",
+      "á» ļ",
+      "ê° Ķ",
+      "Ġ×Ķ×ijר ×Ļת",
+      "פ ×Ļצ",
+      "פ×Ļצ ×ķ×Ļ",
+      "ĠÙĦÙħا ذا",
+      "ĠÐļи ев",
+      "ĠÑģ мÑĭÑģл",
+      "ê¸Ī ìľµ",
+      "ãĤ·ãĥ£ ãĥ«",
+      "ãĥ© ãĤ¤ãĥĪ",
+      "ìĽ ĥ",
+      "×ŀ ×Ĺר",
+      "ãĨ į",
+      "Ġkullan ım",
+      "Ġ×IJצ׾ ׳×ķ",
+      "Ġt Ãłn",
+      "ãĥı ãĥ¼",
+      "ãģ¨ ãģ¨ãĤĤ",
+      "ãģ¨ãģ¨ãĤĤ ãģ«",
+      "ÑĢ ег",
+      "ÑĢег и",
+      "ÑĢеги он",
+      "ãģªãģı ãģªãĤĭ",
+      "Ġch ảy",
+      "Ġج ÙĩØ©",
+      "ÅĦsk iej",
+      "à¸Ńี à¹Ģม",
+      "à¸Ńีà¹Ģม ล",
+      "ãģį ãģ£ãģ¨",
+      "ĠìĺĪ ìĤ°",
+      "Ġkit abı",
+      "Ġedu cação",
+      "Ġbul uÅŁ",
+      "олог иÑı",
+      "Ġкон кÑĢ",
+      "ĠконкÑĢ еÑĤ",
+      "×Ĵ ×Ļר",
+      "ĠпÑĢед лаг",
+      "ĠпÑĢедлаг аеÑĤ",
+      "ĠY ên",
+      "Ġíķľ ë²Ī",
+      "Ġ×ŀ ר׼×ĸ×Ļ",
+      "à¹Ģà¸Ľà¸´à¸Ķ à¹Ģà¸ľà¸¢",
+      "ÑĤвеÑĢ д",
+      "ĠH á»ĩ",
+      "ĠÐĵ ÑĢ",
+      "à¸Ŀ à¹īา",
+      "×Ķ שק",
+      "×Ķשק ×¢×Ķ",
+      "Ġна Ñĥк",
+      "ìłIJ ìĿĦ",
+      "Ġн елÑĮ",
+      "ĠнелÑĮ з",
+      "ĠнелÑĮз Ñı",
+      "г ин",
+      "ĠB öl",
+      "ĠBöl ge",
+      "Ġв ла",
+      "Ġвла ÑģÑĤи",
+      "à¹Ģà¸Ļ à¹ĩ",
+      "à¹Ģà¸Ļà¹ĩ à¸ķ",
+      "ê³ ¨",
+      "Ġö ld",
+      "Ġöld ür",
+      "׼׳ ×¢",
+      "ĠاÙĦÙĩ ÙĬئة",
+      "ت ارÙĬØ®",
+      "ĠÐij ÑĢ",
+      "ĠÑģ мож",
+      "ĠÑģмож еÑĤе",
+      "ĠL úc",
+      "à¹Ħà¸Ľ à¸ĸึà¸ĩ",
+      "ĠBakan ı",
+      "Ġerklä rt",
+      "ĠÐIJ на",
+      "Ġsc ène",
+      "åķı ãģĦ",
+      "åķıãģĦ åIJĪãĤıãģĽ",
+      "ÙħÙĩ ÙĨد",
+      "ÙħÙĩÙĨد س",
+      "Ġн азвание",
+      "ив аниÑı",
+      "ãĤĴ å¤īãģĪ",
+      "ä»ĺãģį åIJĪ",
+      "ãĥij ãĤ½",
+      "ãĥijãĤ½ ãĤ³ãĥ³",
+      "æĺİ ãĤī",
+      "æĺİãĤī ãģĭ",
+      "à¹Ģà¸Ńà¸ģ สาร",
+      "à¹Ģà¸ģิà¸Ļ à¹Ħà¸Ľ",
+      "л еп",
+      "ãģĹãģŁ ãĤĤãģ®",
+      "ĠC âm",
+      "ĠCâm ara",
+      "ק×ķ׾ ׳×ķ×¢",
+      "Ġ×ij×Ĵ ×Ļף",
+      "Ġoc zy",
+      "Ġoczy wiÅĽcie",
+      "att ivitÃł",
+      "ãĥĵ ãĥ¥ãĥ¼",
+      "Ġeduc ación",
+      "Ä° YE",
+      "ê¹Į ìļĶ",
+      "ãĤ¨ ãĥªãĤ¢",
+      "н еÑģÑĤи",
+      "Ġm óg",
+      "Ġmóg ÅĤ",
+      "Ġק×ĺ ׳×Ļ×Ŀ",
+      "ĠPr ä",
+      "Ġ×ľ×¢ ×ij×ķר",
+      "بÙĨ Ùī",
+      "з ол",
+      "зол оÑĤ",
+      "Ġwn ÄĻtr",
+      "ĠwnÄĻtr z",
+      "Ġconstr ução",
+      "รัà¸ļ รà¸Ńà¸ĩ",
+      "س جÙĨ",
+      "Ġק ×ķ׳",
+      "ס ×Ļפ×ķר",
+      "ĠÙħ دÙī",
+      "رض Ùī",
+      "п лав",
+      "ï¼ ¥",
+      "Ġil a",
+      "Ġila ç",
+      "ãĤĭ ãģ¹ãģį",
+      "ĠÙħ ÙĪÙĤÙģ",
+      "à¸ģร ุ",
+      "à¸ģรุ à¸ĵา",
+      "chodzÄħ c",
+      "ĠÑĤÑĭ Ñģ",
+      "Ðķ вÑĢо",
+      "ĠÙĬ ØŃدث",
+      "ãĥ¡ ãĤ¤ãĥ³",
+      "ĠاÙĦص ØŃÙĬ",
+      "ĠÐĶ ан",
+      "دع اء",
+      "ãĤ´ ãĥ¼ãĥ«",
+      "ש ×ł×ª×Ļ",
+      "×©×ł×ª×Ļ ×Ļ×Ŀ",
+      "à¸Ķà¹īวย à¸ģัà¸Ļ",
+      "Ġol acaģı",
+      "Ġ×ij ×ŀ×Ĺ×Ļר",
+      "×Ķ ק",
+      "×Ķק ×ŀת",
+      "ãĥ¢ ãĥİ",
+      "ĠçalÄ±ÅŁ tı",
+      "Ġjó venes",
+      "ãģĦãģı ãĤī",
+      "ĠÙħ عدÙĦ",
+      "ĠC Å©ng",
+      "ĠSeg ún",
+      "Ġdönem de",
+      "Ġ׾ ×Ļ×ĵ×Ļ",
+      "ãģį ãģ¡",
+      "ãģįãģ¡ ãĤĵ",
+      "ãģįãģ¡ãĤĵ ãģ¨",
+      "Ùģر ÙĨس",
+      "ÙģرÙĨس ا",
+      "åIJij ãģį",
+      "Ġcamp aña",
+      "ĠÑģам оÑģÑĤоÑı",
+      "ĠÑģамоÑģÑĤоÑı ÑĤелÑĮно",
+      "á» Ģ",
+      "ÙĤ ÙĪا",
+      "س ÙĦاØŃ",
+      "à¸ģระ à¹ģ",
+      "à¸ģระà¹ģ ส",
+      "ĠполÑĮз Ñĥ",
+      "n qu",
+      "nqu ête",
+      "รà¹Īวม à¸ģัà¸ļ",
+      "ëĬIJ ëĥIJ",
+      "à¸Ĺีม à¸Ĭาà¸ķิ",
+      "Ġyıll ık",
+      "ìĬ ¬",
+      "ĠØ£ صØŃاب",
+      "ill é",
+      "Ġdó la",
+      "Ġdóla res",
+      "Ġк ож",
+      "Ġкож и",
+      "ล à¹īà¸Ń",
+      "à¹Ģรีย à¸ļร",
+      "à¹Ģรียà¸ļร à¹īà¸Ńย",
+      "à¹Ģà¸ŀ ิ",
+      "à¹Ģà¸ŀิ à¹Īà¸ĩ",
+      "ÑĢиÑĤоÑĢ и",
+      "Ġí ijľ",
+      "Ġíijľ íĺĦ",
+      "ĠпеÑĢ ев",
+      "ĠпеÑĢев од",
+      "פ×Ĵ ×Ļ×¢×Ķ",
+      "ĠdeÄŁerlendir me",
+      "Ùģ ائ",
+      "ĠвÑĭ год",
+      "ınız ı",
+      "×ķ׼ ×Ļ×Ĺ",
+      "ĠдоÑģÑĤ иг",
+      "Ġng Ãłn",
+      "æĢĿ ãģ£ãģŁ",
+      "ĠÐķ ÑģÑĤÑĮ",
+      "ĠاÙĦر غÙħ",
+      "ĠzwiÄħz ane",
+      "رب ط",
+      "à¸Ļ ึà¸ĩ",
+      "Ġ׾×Ĺ ×ķק",
+      "Ġszczeg óln",
+      "Ġszczególn ie",
+      "Ġبا ستخداÙħ",
+      "ĠfÃŃs ico",
+      "ע ס",
+      "עס ×ķק",
+      "سÙĦ ÙĪÙĥ",
+      "Ġا ØŃد",
+      "Ñĩ ÑijÑĤ",
+      "×ĸ׼ ×Ķ",
+      "Ġl á»ĩnh",
+      "ĠÙĪ ØŃت",
+      "ĠÙĪØŃت Ùī",
+      "à¸Ħวาม สามารà¸ĸ",
+      "à¸Ńยูà¹Ī à¹ģลà¹īว",
+      "à¸ģาร à¹Ģà¸Ķิà¸Ļà¸Ĺาà¸ĩ",
+      "تخ ذ",
+      "צ×Ļ ×ķ×ĵ",
+      "ĠاÙĦØ£ س",
+      "ĠاÙĦأس ÙĩÙħ",
+      "Ġt á»ĩ",
+      "ãģ£ãģ¦ ãģĦãģ¦",
+      "สร ุ",
+      "สรุ à¸Ľ",
+      "Ġком ÑĦ",
+      "ĠкомÑĦ оÑĢÑĤ",
+      "ìĺ¤ ëĬĶ",
+      "ĠÑĢаз в",
+      "ĠÑĢазв ива",
+      "л анд",
+      "h änge",
+      "ĠبÙĨ سبة",
+      "à¹Ģà¸Ĥ ียว",
+      "עצ ×Ŀ",
+      "Ġ׾ ×ľ×Ľ×ª",
+      "Ñģо ÑĨиалÑĮн",
+      "Ġëĭ¤ìĿĮ ê³¼",
+      "Ġרש ×ķ×ŀ",
+      "×ŀר ×Ĺ×ij",
+      "س ÙĤØ·",
+      "Ġalan ı",
+      "ĠÄij á»ĩ",
+      "é£Łãģ¹ ãĤĭ",
+      "à¸Ķ ึà¸ĩ",
+      "Ġgegen über",
+      "ĠبÙĩ Ø°Ùĩ",
+      "à¸ĸืà¸Ń à¹Ģà¸Ľà¹ĩà¸Ļ",
+      "ëķ ħ",
+      "à¸Ħà¸Ļ à¹Ħà¸Ĺย",
+      "ãĤ¢ ãĤ¦",
+      "ãĤ¢ãĤ¦ ãĥĪ",
+      "ศ ัà¸ģ",
+      "ศัà¸ģ à¸Ķิ",
+      "ศัà¸ģà¸Ķิ à¹Į",
+      "ÙĤÙĪ اÙĨ",
+      "ÙĤÙĪاÙĨ ÙĬÙĨ",
+      "Ġhá»Ļ p",
+      "ãģªãģıãģª ãģ£ãģ¦",
+      "Ġ×IJ ×ŀ׳",
+      "Ġ×IJ×ŀ׳ ×Ŀ",
+      "à¹Ģà¸ķ ืà¸Ńà¸Ļ",
+      "ĠзавиÑģ им",
+      "ĠзавиÑģим оÑģÑĤи",
+      "ת ×Ļ×IJ",
+      "ת×Ļ×IJ ×ķר",
+      "å§ĭãĤģ ãģŁ",
+      "Ġng á»į",
+      "Ġngá»į t",
+      "íĴ į",
+      "ê³¼ ìŀ¥",
+      "Ġb ại",
+      "ãģ§ãģį ãģ¦",
+      "Ġcomeç ar",
+      "à¸Ľà¸£ าà¸ģ",
+      "à¸Ľà¸£à¸²à¸ģ à¸ı",
+      "Ġгод Ñĭ",
+      "м еÑģ",
+      "ĠاÙĦÙħست ÙĪÙī",
+      "ĠÑģам Ñĭе",
+      "л леÑĢ",
+      "ãģ£ãģ¦ãģĹãģ¾ ãģĦãģ¾ãģĻ",
+      "ãģ¨ãģ® ãģĵãģ¨",
+      "bi ó",
+      "à¸ģล à¹Īà¸Ńà¸ĩ",
+      "ĠاÙĦز ÙĪج",
+      "ãģ«è¡Į ãģ£ãģŁ",
+      "à¸Ħà¹Ī à¸Ńà¸Ļ",
+      "à¸Ħà¹Īà¸Ńà¸Ļ à¸Ĥà¹īาà¸ĩ",
+      "ĠbaÄŁ l",
+      "ĠbaÄŁl ant",
+      "ĠbaÄŁlant ı",
+      "確 ãģĭ",
+      "確ãģĭ ãģ«",
+      "ãĥľ ãĥ¼ãĥ«",
+      "çµĤ ãĤıãĤĬ",
+      "ש ×ŀר",
+      "à¸Ĺีà¹Ī สามารà¸ĸ",
+      "ÙĦ زÙħ",
+      "д аеÑĤÑģÑı",
+      "รัà¸ļ à¸Ľà¸£à¸°",
+      "รัà¸ļà¸Ľà¸£à¸° à¸Ĺาà¸Ļ",
+      "å¤ī ãĤıãĤĬ",
+      "ï¼ ¢",
+      "ĠìĺĪìĪĺ ëĭĺ",
+      "ãĤĪãģĨ ãģ¨",
+      "มัà¸ģ à¸Īะ",
+      "ĠH Æ°Æ¡ng",
+      "ÙĨ ÙģØ°",
+      "×ŀ×ĵ ×ĵ",
+      "ĠìĿ¸ ìłķ",
+      "Ñħод иÑĤÑĮ",
+      "ĠзавиÑģ иÑĤ",
+      "×ķ×ĵ ×Ļ×¢",
+      "ãģĵãģ¨ãģĮ ãģĤãĤĬãģ¾ãģĻ",
+      "ع راÙĤ",
+      "سط ØŃ",
+      "à¸ģำ à¹Ħร",
+      "ëĵ¤ ëıĦ",
+      "×Ļצ ×Ļר×Ķ",
+      "ãģĨ ãģĵãģ¨",
+      "ÙĦا ØŃÙĤ",
+      "ãģĦ ãĤĮãģ°",
+      "ĠиÑģполÑĮз ÑĥÑİÑĤ",
+      "ĠB ợi",
+      "Ġשק׾ ×Ļ×Ŀ",
+      "ÑĨи кл",
+      "ÐIJ Ðŀ",
+      "Ġ×ijש ׳×Ķ",
+      "ÙĨØ´ Ø·",
+      "Ġש ×Ļ׳×ķ×Ļ",
+      "Ġש×Ļ׳×ķ×Ļ ×Ļ×Ŀ",
+      "Ġpobl ación",
+      "ĠH Æ°ng",
+      "ระ ว",
+      "ระว ัà¸ĩ",
+      "رÙĬاض Ø©",
+      "ر صد",
+      "تÙĤ ÙĦÙĬ",
+      "تÙĤÙĦÙĬ د",
+      "Ġülk em",
+      "Ġülkem iz",
+      "à¸Ĭ ะ",
+      "ãĤ¯ãĥª ãĥ¼ãĥł",
+      "èģŀ ãģĦãģŁ",
+      "Ġwa ż",
+      "Ġważ ne",
+      "ê±° ëĵł",
+      "ê±°ëĵł ìļĶ",
+      "×ŀ×IJ ×ijק",
+      "×Ĺ×ĵ ש×ķת",
+      "ĠW roc",
+      "ĠWroc ÅĤaw",
+      "ĠKü ltür",
+      "s ist",
+      "sist ência",
+      "×¢×ĸר ×Ķ",
+      "Ġg Æ°Æ¡ng",
+      "รà¹īาà¸Ļ à¸Ħà¹īา",
+      "ĠÙĪØ£ ÙĪضØŃ",
+      "ánd ose",
+      "ãĤ· ãĥ¼ãĥ³",
+      "×IJ׳ ר×Ĵ",
+      "×IJ׳ר×Ĵ ×Ļ×Ķ",
+      "ãģªãģĦ ãģ§ãģĻ",
+      "Ġkh ủng",
+      "Ġ문 ìĦľ",
+      "Ġ×ij ×ĵ×ijר",
+      "×ĵ ×Ļ×ķ",
+      "×ĵ×Ļ×ķ ×ķ×Ĺ",
+      "Ġré gl",
+      "ÙħÙĪ اد",
+      "об оÑĢ",
+      "обоÑĢ оÑĤ",
+      "Ġ×Ķ ×ij׾",
+      "Ġ×Ķ×ij׾ ×ķ×Ĵ",
+      "ØŃ Ø§Ùħ",
+      "ĠاÙĦع اص",
+      "ĠاÙĦعاص ÙħØ©",
+      "пеÑĢ аÑĤоÑĢ",
+      "ت Ø®ÙĦ",
+      "تخÙĦ ص",
+      "ãģŁãģł ãģĹ",
+      "ت سÙħ",
+      "à¹Ĥรà¸ĩ à¸ŀ",
+      "à¹Ĥรà¸ĩà¸ŀ ยา",
+      "à¹Ĥรà¸ĩà¸ŀยา à¸ļาล",
+      "ĠY ük",
+      "ĠYük sek",
+      "Ġש ׳×Ļת",
+      "Ġש׳×Ļת ף",
+      "liÄŁ e",
+      "Ġפ ת",
+      "Ġפת ×ķ×Ĺ",
+      "Ġbe ÄŁ",
+      "ĠbeÄŁ en",
+      "Ġ×ŀ ×ķר",
+      "Ġ×ŀ×ķר ׼×ij",
+      "Ġرس اÙĦØ©",
+      "íĨµ ìĭł",
+      "Ġaval ia",
+      "Ġavalia ções",
+      "Ġman h",
+      "Ġmanh ã",
+      "Ġìķ ŀ",
+      "Ġìķŀ ìľ¼ë¡ľ",
+      "ÙĤ تر",
+      "ÙĤتر ØŃ",
+      "à¹Ģà¸ģ ืà¸Ń",
+      "à¹Ģà¸ģืà¸Ń à¸ļ",
+      "Ġpropos é",
+      "Ø£ Ùħا",
+      "Ø£Ùħا ÙĥÙĨ",
+      "ĠÐŀ Ðŀ",
+      "ĠÐŀÐŀ Ðŀ",
+      "ÙħÙĤ ار",
+      "ÙħÙĤار ÙĨØ©",
+      "ëĦ IJ",
+      "ãģĦãģŁãģł ãģı",
+      "ÙĤ ÙĬÙĦ",
+      "Ġна ÑĪиÑħ",
+      "ãĤ« ãĥĥãĥĹ",
+      "×Ĺ׾ ת",
+      "Ġëĭ¤ ë§Į",
+      "à¸Ĺัà¹Īว à¹Ĥลà¸ģ",
+      "ãĥį ãĤ¿",
+      "ØŃس اس",
+      "ãģ«ãģª ãĤĮ",
+      "ج ائ",
+      "جائ زة",
+      "é change",
+      "é conom",
+      "économ ie",
+      "Т Ðĺ",
+      "סת ׼׾",
+      "à¸Ĺัà¹īà¸ĩ สà¸Ńà¸ĩ",
+      "ĠاÙĦØ® اÙħ",
+      "ĠاÙĦخاÙħ س",
+      "ק ×ĺ×¢",
+      "au waż",
+      "à¸ľà¸¹à¹ī à¸Ĭาย",
+      "à¹ģà¸Ľà¸¥ à¸ģ",
+      "åIJĮæĻĤ ãģ«",
+      "зн аниÑı",
+      "ãģĦãģŁãģł ãģįãģ¾ãģĹãģŁ",
+      "Ġ×ŀ×ij ׾×Ļ",
+      "à¸Ĥà¸Ń à¹ĥหà¹ī",
+      "ĠاÙĦت ربÙĬØ©",
+      "Ġdécou vert",
+      "Ġżyc iu",
+      "apr ès",
+      "Ġy ab",
+      "Ġyab anc",
+      "Ġyabanc ı",
+      "ĠbaÅŁ layan",
+      "ìĹĪ ëįĺ",
+      "Ġhes abı",
+      "Ġë§Į ìķ½",
+      "ë§ Īëĭ¤",
+      "ĠTh ánh",
+      "ãĥ´ ãĤ¡",
+      "à¸Ľà¸£à¸±à¸ļ à¸Ľà¸£",
+      "à¸Ľà¸£à¸±à¸ļà¸Ľà¸£ ุà¸ĩ",
+      "ĠM ặc",
+      "à¹Ģหà¸ķุ à¸ľà¸¥",
+      "ĠÐij ез",
+      "Ġcapac itÃł",
+      "ÅĤe ÅĽ",
+      "ĠпÑĢе им",
+      "ĠпÑĢеим ÑĥÑīеÑģÑĤв",
+      "ĠÅļ wiÄĻt",
+      "Ġpubli é",
+      "×ŀ×¢ צ×ij",
+      "Ùħشار Ùĥات",
+      "à¸łà¸² ษ",
+      "à¸łà¸²à¸© ี",
+      "Ġdeux ième",
+      "ĠÙħØŃ Ø§Ùģظ",
+      "ĠÙħØŃاÙģظ Ø©",
+      "ĠSch ön",
+      "ï½ ¤",
+      "Ġ×Ķ ×ij×¢",
+      "Ġ×Ķ×ij×¢ ×Ļ×Ķ",
+      "ĠÙĪاÙĦ ÙĦÙĩ",
+      "è¨Ģ ãģ£ãģŁ",
+      "à¸ķ à¹īาà¸Ļ",
+      "วร รà¸ĵ",
+      "à¸Ĺิ ศ",
+      "ĠbaÅŁ ına",
+      "Ġmog ÄĻ",
+      "ש ×Ļפ×ķר",
+      "ĠÙĪ عد",
+      "ĠÙĪعد Ùħ",
+      "Ġhistó rico",
+      "Ġk ısı",
+      "ĠìĿ´ ê²Į",
+      "ĠPol ÃŃtica",
+      "ĠÑģиÑĤÑĥ аÑĨии",
+      "ĠkoÅĦ ca",
+      "×ij×ĵ ×Ļק×Ķ",
+      "ĠاÙĦسÙĬ ارات",
+      "ãģªãĤī ãģ°",
+      "ãĤµ ãĥ©",
+      "ãĤĭãģĵãģ¨ãģĮãģ§ãģį ãĤĭ",
+      "Ġdecis ão",
+      "×ķ ×ķ×ĵ",
+      "lä ss",
+      "läss ig",
+      "Ġ׾ ×Ļשר×IJ׾",
+      "ĠÙĬ أتÙĬ",
+      "ר ×ķ×ĸ",
+      "ö ÄŁ",
+      "Ã¶ÄŁ ret",
+      "Ã¶ÄŁret im",
+      "Ġд ек",
+      "Ġдек аб",
+      "Ġдекаб ÑĢÑı",
+      "Ġש ×Ĺ×ķר",
+      "ãģ¦ãģıãĤĮ ãģŁ",
+      "عب ارة",
+      "Ġélect rique",
+      "ĠاÙĦتÙĨ ÙħÙĬØ©",
+      "جر Ùī",
+      "ĠìĪĺ íĸī",
+      "à¸Ĺ ู",
+      "ĠÑĢе алÑĮно",
+      "Ñģп оÑģоб",
+      "à¸Ħล à¹īาย",
+      "Ġس عÙĪد",
+      "ön ü",
+      "ĠÙģ ÙħÙĨ",
+      "تÙĥ ÙĪ",
+      "تÙĥÙĪ ÙĬÙĨ",
+      "ĠкаÑĩ еÑģÑĤво",
+      "ĠконÑĤ ак",
+      "ĠконÑĤак ÑĤ",
+      "Ġsöz leÅŁme",
+      "à¸Ń à¹īาà¸ĩ",
+      "Ġت ÙĪÙģ",
+      "ĠتÙĪÙģ ÙĬر",
+      "×Ķ×ĸ ×ĵ",
+      "×Ķ×ĸ×ĵ ×ŀ׳×ķת",
+      "ĠØ·ÙĪÙĬÙĦ Ø©",
+      "Ġtér mino",
+      "Ġ×IJ ×Ļפ×Ķ",
+      "ãĥĵ ãĥ«",
+      "ส à¹Ĥม",
+      "สà¹Ĥม สร",
+      "ĠاÙĦ اث",
+      "ĠاÙĦاث ÙĨÙĬÙĨ",
+      "ев иÑĩ",
+      "Ġopin ión",
+      "à¸Ľ วà¸Ķ",
+      "åı¤ ãģĦ",
+      "ร à¹Īา",
+      "ĠB iaÅĤ",
+      "ĠÑģÑĤ ал",
+      "ĠÑģÑĤал о",
+      "ó logo",
+      "ĠìķĦ ëĭĪëĭ¤",
+      "Ġ×IJ ×Ļת",
+      "Ġ×IJ×Ļת ×ķ",
+      "à¹Ģหà¹ĩà¸Ļ วà¹Īา",
+      "à¸ļ ารà¹Į",
+      "çĦ ¼",
+      "çĦ¼ ãģį",
+      "ĠìĿ´ìļ© ìŀIJ",
+      "ĠнекоÑĤоÑĢ Ñĭе",
+      "ks z",
+      "ksz taÅĤ",
+      "ksztaÅĤ c",
+      "ãĤŃãĥ£ ãĥĥãĤ·",
+      "ãĤŃãĥ£ãĥĥãĤ· ãĥ³ãĤ°",
+      "Ġro ÅĽ",
+      "ĠroÅĽ lin",
+      "ÑĢаж а",
+      "×ij׳×Ļ ×Ļ×Ķ",
+      "à¸Ľà¸£ สิ",
+      "à¸Ľà¸£à¸ªà¸´ à¸ķ",
+      "Ġgörd ü",
+      "×ŀ׳×Ķ ×Ļ×Ĵ",
+      "å¤īãĤı ãģ£ãģ¦",
+      "Ġ×IJ ×Ķ",
+      "Ġ×IJ×Ķ ×ijת×Ļ",
+      "à¹Ģร à¹Īà¸ĩ",
+      "Ġön ünde",
+      "Ġê·¸ ëĥ¥",
+      "пол иÑĤ",
+      "полиÑĤ иÑĩеÑģк",
+      "ãĥ¡ ãĥĩãĤ£",
+      "ãĥ¡ãĥĩãĤ£ ãĤ¢",
+      "ĠDet ay",
+      "ĠDetay lı",
+      "ĠاÙĦصÙģ ØŃØ©",
+      "à¸ģาร à¹Ģà¸ĩิà¸Ļ",
+      "Ġìµľ ê·¼",
+      "׼ ש׾",
+      "ï¼ ©",
+      "вÑĪ его",
+      "íķĺ ìĭ¤",
+      "ĠÐŃ ÑĤ",
+      "ĠÐŃÑĤ оÑĤ",
+      "ส ื",
+      "สื à¸ļ",
+      "Ġng ừng",
+      "ĠдокÑĥменÑĤ ов",
+      "дав аÑĤÑĮ",
+      "ĠاÙĦشخص ÙĬØ©",
+      "Ġצ ×¢×Ļר",
+      "در Ùĥ",
+      "س ØŃب",
+      "à¹Ħมà¹Ī à¸Ħà¹Īà¸Ńย",
+      "Ġ×Ķ×ŀק ×ķ×ŀ×Ļ",
+      "สัà¹Īà¸ĩ à¸ĭืà¹īà¸Ń",
+      "Ġê·¸ê²ĥ ìĿĦ",
+      "ãģĤãĤĭ ãģĦ",
+      "ãģĤãĤĭãģĦ ãģ¯",
+      "×IJ×ķ×ĺ ×ķ×ij",
+      "×IJ×ķ×ĺ×ķ×ij ×ķס",
+      "к ÑĨион",
+      "ĠÐľ ожно",
+      "ãģı ãģł",
+      "ãģıãģł ãģķ",
+      "ĠинÑĦоÑĢм аÑĨиÑı",
+      "ï» Ł",
+      "Ġìŀij ìĹħ",
+      "Ġ×Ļ ×ķסף",
+      "إ دارة",
+      "ĠاÙĦØŃ Ø§Ø¬",
+      "×ł×¡ ×Ļ×¢×Ķ",
+      "из аÑĨиÑı",
+      "×IJ׾ ×ij",
+      "×IJ׾×ij ×ķ×Ŀ",
+      "п ед",
+      "Ġק×ĺ ׳×Ķ",
+      "ĠÙĨÙģس Ùĩا",
+      "ĠMinist ério",
+      "Ġп ен",
+      "Ġпен Ñģи",
+      "ãĥIJ ãĥ©ãĥ³ãĤ¹",
+      "Ġ×Ķת ×ķר×Ķ",
+      "Ġt ạm",
+      "ĠìĹŃ ìĭľ",
+      "ï½ ¡",
+      "Ġth á»±",
+      "Ġ ısı",
+      "ì» ¨",
+      "ãģĹãģ£ãģĭãĤĬ ãģ¨",
+      "Ġx Æ°a",
+      "Ġc ặp",
+      "×Ĺ ×Ļ×ij×ķר",
+      "วัà¸Ĵà¸Ļ à¸ĺรรม",
+      "st är",
+      "stär ke",
+      "ĠÑģам Ñĭй",
+      "p isa",
+      "pisa Äĩ",
+      "ĠoluÅŁ an",
+      "ĠاÙĦØ¥ ÙħاÙħ",
+      "ĠcÄĥ ng",
+      "Ġgü nl",
+      "Ġgünl ük",
+      "Ġ׳ש ×IJר",
+      "Ġkhi á»ĥn",
+      "ç¶ļ ãģijãĤĭ",
+      "stit ución",
+      "Ġcapac ité",
+      "Ġj aki",
+      "Ġjaki ÅĽ",
+      "вÑĪ иÑģ",
+      "вÑĪиÑģ ÑĮ",
+      "פע×ķ׾ ×ķת",
+      "ĠØŃ ÙĬات",
+      "ĠØŃÙĬات Ùĩ",
+      "Ġник огда",
+      "ÐĽ Ь",
+      "Ġ×Ķ×¢ ×ķ×ij",
+      "Ġ×Ķ×¢×ķ×ij ×ĵ×Ķ",
+      "Ġch Ãło",
+      "หลาย à¹Ĩ",
+      "ĠÑı н",
+      "ĠÑıн ваÑĢ",
+      "ĠÑıнваÑĢ Ñı",
+      "à¸Īำà¹Ģà¸Ľà¹ĩà¸Ļ à¸ķà¹īà¸Ńà¸ĩ",
+      "Ġhö her",
+      "ãģķãĤĮãģ¦ ãģĦãģŁ",
+      "สà¸ĩ สั",
+      "สà¸ĩสั ย",
+      "ĠاÙĦ اس",
+      "ĠاÙĦاس ÙĦاÙħ",
+      "ĠاÙĦØ´ Ùħس",
+      "สà¸ĸาà¸Ļ ี",
+      "ãĤ¯ãĥ© ãĤ¹",
+      "à¸ŀร ร",
+      "à¸ŀรร à¸Ħ",
+      "p õ",
+      "põ e",
+      "Ġpor ém",
+      "à¸Ľà¸£à¸° สà¸ĩ",
+      "à¸Ľà¸£à¸°à¸ªà¸ĩ à¸Ħà¹Į",
+      "powied zie",
+      "powiedzie Äĩ",
+      "Ġмог Ñĥ",
+      "Ġж ел",
+      "Ġжел ез",
+      "ĠاÙĦØ« ÙĤ",
+      "ĠاÙĦØ«ÙĤ اÙģÙĬ",
+      "ĠпÑĢав ило",
+      "Ġgdy ż",
+      "פש ×ķ×ĺ",
+      "ÑĢабоÑĤ ка",
+      "ĠÙĥ رة",
+      "ش دد",
+      "Ùħار Ùĥ",
+      "Ùħ ÙĥØ©",
+      "Ġпод пиÑģ",
+      "×ĺ×ķ ×ķ×Ĺ",
+      "ĠÅĽ c",
+      "ĠÅĽc ian",
+      "Ġر جاÙĦ",
+      "Ġ×ª×ľ ×ķ×Ļ",
+      "и ÑĪ",
+      "иÑĪ ÑĮ",
+      "Ġmé dec",
+      "Ġmédec in",
+      "ëįĶ ëĿ¼ëıĦ",
+      "ĠÑĤеб Ñı",
+      "Ġ׾×Ķ ×ķס×Ļ×£",
+      "ãģĬ 話",
+      "Ġà¹ģà¸ķà¹Ī à¸ģà¹ĩ",
+      "د اÙģ",
+      "داÙģ ع",
+      "ĠC ùng",
+      "ãĥ»ãĥ» ãĥ»ãĥ»",
+      "ê¶ ģ",
+      "Ġdeber ÃŃa",
+      "หà¸Ļà¹Īวย à¸ĩาà¸Ļ",
+      "Ġva ÌĢ",
+      "Ġעצ ×ŀ",
+      "Ġעצ×ŀ ×Ŀ",
+      "à¹Ģà¸Ĭืà¹Īà¸Ń วà¹Īา",
+      "שק ע",
+      "Ġ×Ķ ׼×ķ׾",
+      "Ġ×Ķ׼×ķ׾ ׾",
+      "ни бÑĥд",
+      "нибÑĥд ÑĮ",
+      "ĠëĦĪ íĿ¬",
+      "Ġоб ÑĢаÑī",
+      "ĠобÑĢаÑī а",
+      "Ġ×¢×ij×ķ×ĵ ת",
+      "ĠاÙĦÙħÙĨت خب",
+      "ıy ord",
+      "ıyord u",
+      "ÙĪ Ø°",
+      "×Ĺש ×Ļ×ij×ķת",
+      "Ġ×Ķ×¢ ×Ļק",
+      "Ġ×Ķ×¢×Ļק ר×Ļ",
+      "ì¢ Į",
+      "ยุ à¹Ĥร",
+      "ยุà¹Ĥร à¸Ľ",
+      "Ġа пÑĢ",
+      "ĠапÑĢ елÑı",
+      "sz ed",
+      "szed ÅĤ",
+      "д он",
+      "à¹Ģà¸ķิ à¸ļ",
+      "à¹Ģà¸ķิà¸ļ à¹Ĥà¸ķ",
+      "кол о",
+      "Ġkażde j",
+      "å¸ °",
+      "帰 ãĤĬ",
+      "Ġмил ли",
+      "Ġмилли он",
+      "ç¾İåij³ ãģĹãģĦ",
+      "ت ÙĤار",
+      "تÙĤار ÙĬر",
+      "ĠìĿ´ 루",
+      "ĠìĿ´ë£¨ ìĸ´",
+      "Ġsprzeda ż",
+      "×Ķ ×ķצ×IJ×ķת",
+      "ãĤ¢ãĤ¯ ãĤ»",
+      "ãĤ¢ãĤ¯ãĤ» ãĤ¹",
+      "ר ×ķ×¥",
+      "ĠгоÑģÑĥдаÑĢÑģÑĤв енн",
+      "Ø£ ØŃÙĥ",
+      "Ø£ØŃÙĥ اÙħ",
+      "ĠoluÅŁ u",
+      "ĠA ç",
+      "ĠAç ık",
+      "ãĤ¸ ãĥ¼",
+      "ç´ł æĻ´",
+      "ç´łæĻ´ ãĤīãģĹãģĦ",
+      "Ġ×ijש×ij ×ķ×¢",
+      "ب ذ",
+      "بذ ÙĦ",
+      "สา à¹Ģหà¸ķุ",
+      "Ġpoz osta",
+      "Ġpozosta ÅĤ",
+      "ØŃر Ùħ",
+      "Ġimport ância",
+      "leÅŁtir me",
+      "Ġд ÑĢев",
+      "Ġmó vil",
+      "ĠA ynı",
+      "Ġна лог",
+      "Ġналог ов",
+      "Ġ×Ĺ ×Ļפ×Ķ",
+      "ĠÑĦоÑĢм Ñĥ",
+      "à¸Ĺà¸Ķ สà¸Ńà¸ļ",
+      "ĠksiÄħż ki",
+      "Ġma ÅĤe",
+      "Ùħس Ø£ÙĦ",
+      "ÙħسأÙĦ Ø©",
+      "ï¼¾ ï¼¾",
+      "ç ãeste",
+      "év iter",
+      "Ġкон ÑģÑĤÑĢÑĥк",
+      "ĠконÑģÑĤÑĢÑĥк ÑĨи",
+      "ï¾ ŀ",
+      "Ġת×ķ׼ ׳",
+      "ãĤ¹ãĥĪ ãĥ¬ãĤ¹",
+      "ĠاÙĦاÙĤتصاد ÙĬ",
+      "×ŀ×ĵ ×Ļ",
+      "Ġw ÅĤad",
+      "ĠwÅĤad z",
+      "Ø® ÙĪÙģ",
+      "ĠмаÑĤеÑĢиал ов",
+      "ãģ¨ãģ£ãģ¦ ãĤĤ",
+      "Ġznaj du",
+      "Ġznajdu jÄħ",
+      "Ùģ ئة",
+      "ãģ©ãģ® ãĤĪãģĨãģª",
+      "æĬij ãģĪ",
+      "׳ ×Ĺ׾",
+      "Ġdü ny",
+      "Ġdüny an",
+      "Ġdünyan ın",
+      "гÑĢ ани",
+      "гÑĢани Ñĩ",
+      "Ġ×Ķש׾ ×Ļש×Ļ",
+      "Ġ×Ķ×IJ ש",
+      "åıĬ ãģ³",
+      "ìĭŃ ìĭľ",
+      "ìĭŃìĭľ ìĺ¤",
+      "Ġдол л",
+      "Ġдолл аÑĢ",
+      "Ġпов ÑĤоÑĢ",
+      "Ġ×Ĺ ×Ļ׳×Ŀ",
+      "ת פת×Ĺ",
+      "Ñĥв ели",
+      "Ñĥвели Ñĩен",
+      "ãĤ« ãĥª",
+      "raw id",
+      "rawid ÅĤow",
+      "×ķ ×ķ׾",
+      "ãĥŁ ãĥ¥",
+      "ì½ ĺ",
+      "ĠBy ÅĤ",
+      "Ðľ ÐIJ",
+      "ع ÙIJ",
+      "ĠÑģовеÑĢ ÑĪ",
+      "ĠÑģовеÑĢÑĪ енно",
+      "Ġм ой",
+      "Ġ×ķ׾×IJ ×Ĺר",
+      "æħ £",
+      "æħ£ ãĤĮ",
+      "ØŃ Ø§Ùģظ",
+      "Ġ무 ë£Į",
+      "à¸Ħà¸ĵะ à¸ģรรม",
+      "à¸Ħà¸ĵะà¸ģรรม à¸ģาร",
+      "Ġìĸ´ ëĶĶ",
+      "Ġdif eren",
+      "Ġdiferen ça",
+      "ĠاÙĦØ£ ساس",
+      "ĠاÙĦأساس ÙĬØ©",
+      "Ġ׾×IJ×Ĺר ×ķ׳×Ķ",
+      "ê· ł",
+      "Ġ×Ķש׳×Ļ ×Ļ×Ķ",
+      "ìľĦìĽIJ ìŀ¥",
+      "ลุ à¸ģ",
+      "ç iler",
+      "Ġ×Ķ×IJ ׾×ķ",
+      "èģŀ ãģı",
+      "Ġ×ķ×IJ פ×Ļ׾×ķ",
+      "ĠÑĢе ализ",
+      "ĠÑĢеализ аÑĨи",
+      "ระยะ à¹Ģวลา",
+      "Ġجدا Ùĭ",
+      "تب اع",
+      "Ġveh ÃŃculo",
+      "Ġдол г",
+      "à¸Ľà¸£à¸´ มาà¸ĵ",
+      "ì¦ IJ",
+      "Ġ׾ ×ŀק×ķ×Ŀ",
+      "ĠìĤ¬ ì§Ħ",
+      "à¸Ĭ à¹īา",
+      "Ġ×ŀ×¢ ×ķ׾×Ķ",
+      "Ġgö rm",
+      "Ġgörm ek",
+      "ĠÙĪÙĩ Ø°Ùĩ",
+      "пеÑĢ в",
+      "пеÑĢв ÑĭÑħ",
+      "ê·¸ ëŀĺ",
+      "ĠاÙĦبر ÙĬØ·",
+      "ĠاÙĦبرÙĬØ· اÙĨÙĬ",
+      "ĠиÑİ Ð½Ñı",
+      "ĠÐĵ оÑĢ",
+      "Ġ׾ ש׾×Ŀ",
+      "ÐIJ ÐĿ",
+      "Ġназ наÑĩен",
+      "о оÑĢ",
+      "ооÑĢ Ñĥж",
+      "Ġöz elli",
+      "Ġözelli ÄŁi",
+      "Ġни же",
+      "ç¶ļ ãģijãģ¦",
+      "Ġа ÑĢенд",
+      "Ġkat ılı",
+      "Ġkatılı m",
+      "ĠØ¥ Ø·ÙĦاÙĤ",
+      "ĠÙĪØ¥ ذا",
+      "Ġок ÑĤÑı",
+      "ĠокÑĤÑı бÑĢÑı",
+      "à¹Ĥà¸ķ à¹",
+      "à¹Ĥà¸ķ๠Ĭ",
+      "à¹Ĥà¸ķà¹Ĭ ะ",
+      "Ġolduk ları",
+      "Ùħ ÙĪÙĤع",
+      "ëĤ ©",
+      "ãģ¨æĢĿ ãģ£ãģ¦ãģĦãĤĭ",
+      "Ġש ×Ļ׼×ķ׾",
+      "วา à¸Ķ",
+      "س ÙĬÙĦ",
+      "à¸Ĥ วั",
+      "à¸Ĥวั à¸į",
+      "تØŃ ÙĥÙħ",
+      "ì ĤŃ",
+      "Ġconna ît",
+      "׳ פת×Ĺ",
+      "Ġch ặ",
+      "Ġchặ n",
+      "ĠÙħ ØŃÙħ",
+      "ĠÙħØŃÙħ ÙĪد",
+      "ãģ ´",
+      "ĠпÑĢодÑĥк ÑĨии",
+      "зд ÑĢав",
+      "ãģĶ è¦",
+      "ãģĶè¦ §",
+      "×IJ×ij ×IJ",
+      "Ġvé ritable",
+      "ĠØ· ÙģÙĦ",
+      "ãĥĪãĥ© ãĥĸãĥ«",
+      "ê³ ¡",
+      "Ġת ×ŀ×ķ׳×Ķ",
+      "Ġki ên",
+      "ĠÙĤ ادر",
+      "Ø¥ÙĤ ÙĦÙĬÙħ",
+      "ĠпÑĢед пÑĢи",
+      "ĠпÑĢедпÑĢи ÑıÑĤиÑı",
+      "Ġb Äĥng",
+      "Ġay ında",
+      "Ġg ấp",
+      "еÑħ ал",
+      "Ġgi Ãłnh",
+      "Ġд ав",
+      "Ġдав но",
+      "ìĺĢ ëĭ¤",
+      "à¸Ļัà¸ģ à¹Ģà¸ķ",
+      "à¸Ļัà¸ģà¹Ģà¸ķ ะ",
+      "Ùħست شار",
+      "ست راتÙĬج",
+      "ستراتÙĬج ÙĬ",
+      "رÙħ ز",
+      "Ġt Ä©nh",
+      "ë¡ Ń",
+      "ĠÑĩ еÑĤ",
+      "ĠÑĩеÑĤ Ñĭ",
+      "ĠÑĩеÑĤÑĭ ÑĢе",
+      "ĠEnt ão",
+      "Ġص غ",
+      "Ġصغ ÙĬرة",
+      "×ij×Ļ×ĺ ×ķ׾",
+      "خط ÙĪØ·",
+      "ĠÑĢазвиÑĤ ие",
+      "Ġamacı yla",
+      "à¸Ĺี วี",
+      "Ġо ÑģÑĤ",
+      "ĠоÑģÑĤ алÑĮн",
+      "ש×ķ׾׊ף",
+      "Ġ׼ ׳×Ļס",
+      "Ġ׼׳×Ļס ×Ķ",
+      "Ġd áºŃy",
+      "ĠyaÅŁ ayan",
+      "Ġ×ŀ×Ķ ×ķ×ķ×Ķ",
+      "ĠÑĥ Ñģи",
+      "ĠÑĥÑģи ли",
+      "×ŀ פ×Ļ",
+      "ĠпÑĢовед ениÑı",
+      "Ġر ب",
+      "Ġرب Ùħا",
+      "ĠاÙĦØ£ ÙĪسط",
+      "Ġìľł ì§Ģ",
+      "Ġprac ownik",
+      "Ġpracownik ów",
+      "×ŀס ×ķרת",
+      "ÙĤار ب",
+      "à¸Ħวาม รูà¹īสึà¸ģ",
+      "à¹ģหล ะ",
+      "ĠاÙĦÙĨ ÙĤد",
+      "Ġ×IJ׾ פ×Ļ",
+      "Ùħس ئ",
+      "Ùħسئ ÙĪÙĦ",
+      "ев ÑĭÑħ",
+      "клÑİÑĩ ениÑı",
+      "×ij ×Ļ׳",
+      "×ij×Ļ׳ ×Ļ×Ķ×Ŀ",
+      "ש ×ķ×IJ×Ķ",
+      "ĠÅŁ ark",
+      "ĠÅŁark ı",
+      "Ġsü rec",
+      "Ġsürec in",
+      "à¹Ģà¸Ħร à¸Ķ",
+      "à¹Ģà¸Ħรà¸Ķ ิà¸ķ",
+      "ãĥIJ ãĥ¬",
+      "ĠØ´ Ø£ÙĨ",
+      "à¹Ģà¸Ńา à¹Ħวà¹ī",
+      "niÄĻ cie",
+      "רצ ×Ĺ",
+      "ĠaÅŁ ama",
+      "׳ פ×Ĵ×¢",
+      "Ġth á»Ŀ",
+      "Ġkhu ẩn",
+      "diÄŁ inde",
+      "ÑıÑī иÑħ",
+      "ãĥĺ ãĥ«",
+      "Ġüber h",
+      "Ġüberh aupt",
+      "ĠÑĤÑĢеб ова",
+      "ĠdÅĤ ugi",
+      "×ĺ ×Ļף",
+      "à¸Ĥà¸Ļาà¸Ķ à¹ĥหà¸įà¹Ī",
+      "ĠاÙĦØ£ Ùĩ",
+      "ĠاÙĦØ£Ùĩ ÙĦÙĬ",
+      "ĠMü d",
+      "ĠMüd ürü",
+      "Ġ×Ļ×Ķ ×ķ×ĵ×Ķ",
+      "Ñĭв аеÑĤÑģÑı",
+      "س اط",
+      "×Ķת ׳×Ķ×Ĵ",
+      "×Ķ×ª×ł×Ķ×Ĵ ×ķת",
+      "à¸ģาร à¸ľà¸¥à¸´à¸ķ",
+      "íĴ Ģ",
+      "สà¸ĸาà¸Ļ à¸ģารà¸ĵà¹Į",
+      "Ġо ÑĦ",
+      "ĠоÑĦ иÑģ",
+      "ĠÙĦ عبة",
+      "Ġstron ÄĻ",
+      "Ġר×IJ ×ķ×Ļ",
+      "×Ĺ ×ij׾",
+      "ĠÑĢÑĭ н",
+      "ĠÑĢÑĭн ке",
+      "Ġ׾×ŀ×¢ ף",
+      "اس ÙĦ",
+      "ห ัà¸Ļ",
+      "Ġ×IJ ×Ĺ×Ļ",
+      "ĠпÑĢод ол",
+      "ê°Ģ ìŀħ",
+      "Ġ×ijר ×Ĺ",
+      "Ġ×ijר×Ĺ ×ij×Ļ",
+      "дж еÑĢ",
+      "Ġ׾ ×Ĺ׾",
+      "Ġ׾×Ĺ׾ ×ķ×ĺ",
+      "Ġ׾×Ĺ׾×ķ×ĺ ×Ļף",
+      "ศาส à¸Ļา",
+      "ãĤ¢ãĤ¤ ãĥĨ",
+      "ãĤ¢ãĤ¤ãĥĨ ãĥł",
+      "Ġפר ×ķפ",
+      "جز اء",
+      "ล à¸Ńย",
+      "Ġc iaÅĤa",
+      "Ġgi ết",
+      "ĠзнаÑĩ иÑĤелÑĮно",
+      "Ġolmad ıģ",
+      "Ġolmadıģ ını",
+      "н д",
+      "нд екÑģ",
+      "تأ Ùĥد",
+      "Ġìĸ ¸",
+      "Ġìĸ¸ ìłľ",
+      "ay dın",
+      "ãĥī ãĥ¬ãĤ¹",
+      "Ġs ắt",
+      "Ġíĺ¸ íħĶ",
+      "Ġë¶ ģ",
+      "Ġë¶ģ íķľ",
+      "ãĥij ãĤ¤",
+      "Ġ×ŀש×Ĺק ×Ļ",
+      "à¸Ħà¸Ļ à¸Ńืà¹Īà¸Ļ",
+      "Ġиз гоÑĤов",
+      "ĠизгоÑĤов лен",
+      "à¹Ģà¸ģีย ร",
+      "à¹Ģà¸ģียร à¸ķิ",
+      "תק שר",
+      "ĠÑĢаÑģ ÑĩеÑĤ",
+      "ส à¹Ģà¸ķ",
+      "Ġl änger",
+      "ĠiÅŁ let",
+      "ĠiÅŁlet me",
+      "Ġع ÙĦÙĬÙĨ",
+      "ĠعÙĦÙĬÙĨ ا",
+      "é lection",
+      "ĠاÙĦغ ربÙĬØ©",
+      "íĭ Ģ",
+      "ãĤĤãĤī ãģĪ",
+      "Ġкни ги",
+      "Ø£ سÙħ",
+      "أسÙħ اء",
+      "Ġth á»ı",
+      "Ġthá»ı a",
+      "หà¸Ļ ู",
+      "Ġ×ł×¢ ש×Ķ",
+      "à¸łà¸²à¸¢ à¹ĥà¸ķà¹ī",
+      "à¸ŀื à¸Ĭ",
+      "رÙĬ Ø·",
+      "Ùģ ÙĪض",
+      "ãģĤãĤĬãģĮãģ¨ãģĨãģĶãģĸ ãģĦãģ¾ãģĹãģŁ",
+      "ש ×ĵ×Ķ",
+      "Ġng á»±c",
+      "ĠÑģеÑĢ ÑĮ",
+      "ĠÑģеÑĢÑĮ езн",
+      "T ôi",
+      "Ġfiyat ları",
+      "ĠвÑģ Ñİ",
+      "ĠC ódigo",
+      "Ġ×Ķש ×IJ",
+      "Ġ×Ķש×IJ ׾×Ķ",
+      "ĠP ública",
+      "Ø¥ Ø®",
+      "إخ ÙĪاÙĨ",
+      "ĠзаÑıв ил",
+      "ãĥ¦ ãĥ¼",
+      "ר×IJ ×Ļת",
+      "vol ución",
+      "Ġsz ko",
+      "Ġszko ÅĤy",
+      "جرÙĬ دة",
+      "Ġpens é",
+      "ìī ¬",
+      "ĠBüyük ÅŁehir",
+      "ĠØ£Ùħ رÙĬ",
+      "ĠØ£ÙħرÙĬ ÙĥÙĬ",
+      "à¸Ļัà¸ģ ศึà¸ģษา",
+      "Ġtod av",
+      "Ġtodav ÃŃa",
+      "ĠС ан",
+      "ĠСан кÑĤ",
+      "íķĺ ìŀIJ",
+      "ØŃÙĪ اÙĦ",
+      "׼ ×ķשר",
+      "à¹Ģลย à¸Ħรัà¸ļ",
+      "Ġal gu",
+      "Ġalgu ém",
+      "Ùģ ز",
+      "Ġçek il",
+      "Ġ×ĵ ר׼×Ļ×Ŀ",
+      "ãĥIJ ãĥ©",
+      "à¸ģà¹ĩ สามารà¸ĸ",
+      "สà¹Īวà¸Ļ ลà¸Ķ",
+      "íı °",
+      "ĠP úb",
+      "ĠPúb lico",
+      "à¹ģà¸Ļว à¸Ĺาà¸ĩ",
+      "×IJת ×Ĵר",
+      "ش اش",
+      "شاش ة",
+      "ci ÅĽni",
+      "ĠÃľ rün",
+      "ÙĦÙĪ ØŃ",
+      "ĠاÙĦ بÙĨ",
+      "ĠاÙĦبÙĨ Ùĥ",
+      "ì¡° ì¹ĺ",
+      "Ġorganiz ación",
+      "ãģĤãĤĬãģĮãģ¨ãģĨãģĶãģĸ ãģĦãģ¾ãģĻ",
+      "s ätze",
+      "ĠÑģем ей",
+      "ÙĤ صد",
+      "ÑģÑĤв еннÑĭе",
+      "Ġpréc éd",
+      "Ġprécéd ent",
+      "à¸ģรุà¸ĩà¹Ģà¸Ĺà¸ŀ ฯ",
+      "ãģ¨è¨Ģ ãģĦ",
+      "×ij׳×Ļ ×Ļף",
+      "ĠØŃ ÙĪ",
+      "ĠØŃÙĪ اÙĦÙĬ",
+      "סק ס",
+      "ĠsaÄŁlam ak",
+      "Ġ׾ צ×Ļ×Ļף",
+      "ק×ĵ ש",
+      "Ġ×Ķ×ŀ ×¢×¨×Ľ×ª",
+      "Ġ׾×Ķ ×¢×ij×Ļר",
+      "Ġg ünd",
+      "Ġgünd em",
+      "ĠнаÑĪ его",
+      "à¹ĥà¸Ļ à¸ŀืà¹īà¸Ļà¸Ĺีà¹Ī",
+      "à¹Ģà¸Ħร ืà¸Ń",
+      "à¹Ģà¸Ħรืà¸Ń à¸Ĥ",
+      "à¹Ģà¸Ħรืà¸Ńà¸Ĥ à¹Īาย",
+      "ظ اÙĩرة",
+      "ÙħÙĨ ظÙħ",
+      "ÙħÙĨظÙħ ات",
+      "Ùħت از",
+      "追 ãģĦ",
+      "dı kt",
+      "dıkt an",
+      "ĠëįĶ ìļ±",
+      "ĠÐĿ апÑĢимеÑĢ",
+      "tw ór",
+      "×ŀ×ķ×¢ צ×Ķ",
+      "Ùĥ ÙĪÙĥ",
+      "Ð ©",
+      "×ŀ×ĺ פ׾",
+      "ó lica",
+      "訪 ãĤĮ",
+      "ĠëĮĢ ë¶Ģ",
+      "ĠëĮĢë¶Ģ ë¶Ħ",
+      "ãĤ¯ãĥª ãĥĥãĤ¯",
+      "ãĤĴ éģ¸",
+      "ãĤĴéģ¸ ãģ¶",
+      "Ġpow sta",
+      "Ġpowsta ÅĤ",
+      "Ġraz ón",
+      "×ij ×ķ×Ĺר",
+      "ĠÑģообÑī ил",
+      "Ġק ×ij×ķ×¢",
+      "r êt",
+      "à¸Ķี à¸Ĥึà¹īà¸Ļ",
+      "×ŀס ×¢×ĵ",
+      "×ŀסע×ĵ ×ķת",
+      "ĠÃĸ sterreich",
+      "Ġ׳ ×Ĺש×ij",
+      "Ùħباد رة",
+      "ì´ ī",
+      "×Ĵ ׳×ĺ×Ļ",
+      "ä¿¡ ãģĺ",
+      "du ÄŁ",
+      "duÄŁ unu",
+      "Ġph ú",
+      "ĠاÙĦØ£ Ø®ÙĬر",
+      "Ġت عتبر",
+      "landır ıl",
+      "ãģ¨ãģ¯ ãģĦ",
+      "ãģ¨ãģ¯ãģĦ ãģĪ",
+      "ĠاÙĦ Ø·ÙĦ",
+      "ĠاÙĦØ·ÙĦ اب",
+      "ĠN º",
+      "éģ¿ ãģij",
+      "اÙĦ Ùħع",
+      "اÙĦÙħع رÙĪÙģ",
+      "ส à¸łà¸²",
+      "éĽ¢ ãĤĮ",
+      "ĠпомоÑī ÑĮ",
+      "Ġзна еÑĤ",
+      "ãĥĹãĥ¬ ãĤ¼",
+      "ãĥĹãĥ¬ãĤ¼ ãĥ³ãĥĪ",
+      "Ġsup érieur",
+      "Ġש׾ ×Ļש×Ļ",
+      "ĠاÙĦÙĨ ÙĪع",
+      "ãĤĵãģ§ãģĻ ãģŃ",
+      "à¸Ńà¸ļ รม",
+      "Ġgi á»įng",
+      "Ġwzgl ÄĻd",
+      "ĠاÙĦÙģ ÙĤر",
+      "è rent",
+      "Ġ×ŀ×IJ ×Ĺ",
+      "Ġ×ŀ×IJ×Ĺ ×ķר×Ļ",
+      "×Ĵ ×Ĵ",
+      "×Ļ ×Ļ×ij",
+      "ÙħÙĦ اب",
+      "ÙħÙĦاب س",
+      "Ġhük ü",
+      "Ġhükü met",
+      "Ġ×ŀ×Ĵ ×Ļ×ij",
+      "ĠÐŀ Ñĩ",
+      "ĠÐŀÑĩ енÑĮ",
+      "æĹ© ãģĦ",
+      "Ġconstr ucción",
+      "Ġth ượng",
+      "ï¼ ĭ",
+      "Ġcor ação",
+      "à¹Ģหล à¹ĩà¸ģ",
+      "ĠBaÅŁ b",
+      "ĠBaÅŁb akan",
+      "éĢ£ ãĤĮ",
+      "ãģĻãĤĭ ãģĵãģ¨ãģĮãģ§ãģįãģ¾ãģĻ",
+      "ĠÙĤ اÙħت",
+      "Ġا Ùĥثر",
+      "Ùģاع ÙĦ",
+      "ĠÑĦ оÑĢ",
+      "ĠÑĦоÑĢ Ñĥм",
+      "غ Ø°ÙĬ",
+      "ĠiÅŁ le",
+      "ĠiÅŁle ml",
+      "ĠiÅŁleml eri",
+      "ĠìĤ¬ëŀĮ ìĿĢ",
+      "Ġìŀij ìĦ±",
+      "Ġë§Ī 볨",
+      "Ùħ جÙĦس",
+      "หม ู",
+      "д в",
+      "дв иг",
+      "двиг а",
+      "à¹Ģสีย à¸Ĭีวิà¸ķ",
+      "×Ķת פת×Ĺ",
+      "×Ķתפת×Ĺ ×ķת",
+      "ĠмеÑĤ ÑĢо",
+      "ĠÑģ енÑĤ",
+      "ĠÑģенÑĤ Ñı",
+      "ĠÑģенÑĤÑı бÑĢÑı",
+      "ê³ §",
+      "Ġ׾ פע",
+      "Ġ×ľ×¤×¢ ×ŀ×Ļ×Ŀ",
+      "à¹Ģà¸ļ ีย",
+      "詳 ãģĹãģı",
+      "çķ° ãģªãĤĭ",
+      "ĠÄ°l çe",
+      "ĠAt at",
+      "ĠAtat ür",
+      "ĠAtatür k",
+      "รุ à¹Īà¸ĩ",
+      "Ġkald ı",
+      "Ġ주 ìŀ¥",
+      "Ġprés ence",
+      "Ġн аб",
+      "Ġнаб лÑİ",
+      "ĠнаблÑİ Ð´Ð°",
+      "ĠÑģам ого",
+      "×Ĵ ×ķש",
+      "×ŀ×ĺ ×ķפ",
+      "×ŀ×ĺ×ķפ ׾",
+      "ĠвÑĭб иÑĢа",
+      "ĠìŀIJ 리",
+      "åĪĨ ãģĭãĤīãģªãģĦ",
+      "Ġз Ñĥб",
+      "Ġש׼ ×ijר",
+      "Ġد ائ",
+      "Ġدائ Ùħا",
+      "ĠпаÑĢ ÑĤи",
+      "ï¼ ²",
+      "ĠاÙĬ ضا",
+      "ĠÑħ оз",
+      "ĠÑħоз Ñı",
+      "ĠÑħозÑı й",
+      "ĠÑħозÑıй ÑģÑĤв",
+      "ĠاÙĦØ£ ج",
+      "ĠاÙĦأج ÙĨب",
+      "ĠاÙĦأجÙĨب ÙĬØ©",
+      "ĠÐĹ Ð½Ð°",
+      "ĠAp ós",
+      "ĠÑį неÑĢ",
+      "ĠÑįнеÑĢ ги",
+      "Ġy ans",
+      "Ġyans ı",
+      "ĠJust i",
+      "ĠJusti ça",
+      "Ġpré vu",
+      "ม วล",
+      "ìŀ¥ ëĭĺ",
+      "à¸ģระ à¸ļ",
+      "à¸ģระà¸ļ วà¸Ļ",
+      "à¸ģระà¸ļวà¸Ļ à¸ģาร",
+      "×ŀ ×ŀ",
+      "×ŀ×ŀ ×ķצע",
+      "Ġh ẹ",
+      "Ġhẹ n",
+      "зд ание",
+      "Ġak ÅŁ",
+      "ĠakÅŁ am",
+      "×ĺ ×ķפ",
+      "Ġgere kt",
+      "Ġgerekt i",
+      "Ġgerekti ÄŁini",
+      "Ġnar z",
+      "Ġnarz ÄĻdzi",
+      "é po",
+      "épo que",
+      "ĠTh ần",
+      "Ġwys oko",
+      "Ġwysoko ÅĽci",
+      "à¸ľà¸¹à¹ī à¸Ľ",
+      "à¸ľà¸¹à¹īà¸Ľ à¹Īวย",
+      "ĠÙĬ بدÙĪ",
+      "ÑĤелÑĮ ного",
+      "Ġвз глÑıд",
+      "Ġjed nÄħ",
+      "ĠìĿĺ 견",
+      "Ġ à¸Ĥà¸ĵะà¸Ĺีà¹Ī",
+      "פ ×Ļ×ĵ",
+      "ìĥģ ëĭ´",
+      "Ġm ỡ",
+      "×Ķ ×ŀ׾",
+      "×Ķ×ŀ׾ צ×ķת",
+      "ĠÑģоÑģÑĤ о",
+      "ĠÑģоÑģÑĤо иÑĤ",
+      "Ġав и",
+      "Ġави а",
+      "ĠL änder",
+      "تص ÙĪÙĬر",
+      "×ŀ×ĵ ×Ļ×Ķ",
+      "ìłĪ ì°¨",
+      "ãģ¨ ãĤĬ",
+      "ãģ¨ãĤĬ ãģĤ",
+      "ãģ¨ãĤĬãģĤ ãģĪ",
+      "ãģ¨ãĤĬãģĤãģĪ ãģļ",
+      "ĠÑĢ Ñıд",
+      "ĠÑĢÑıд ом",
+      "ĠNh ất",
+      "ĠاÙĦÙĥ اÙħÙĦ",
+      "×Ĺ׾ ׾",
+      "ĠGi ấy",
+      "צ ×ĺר",
+      "צ×ĺר ×£",
+      "Ġ׾×ij ×ĺ׾",
+      "Ġим еÑĤÑĮ",
+      "ס×ŀ ×ķ×ļ",
+      "Ġparticip ação",
+      "íķľëĭ¤ ë©´",
+      "ÙħÙĨت دÙĬ",
+      "ÙħÙĨتدÙĬ ات",
+      "ĠeÄŁ len",
+      "g änge",
+      "رب ØŃ",
+      "ãĤ® ãĥ£",
+      "ĠاÙĦر ÙĤÙħ",
+      "à¸ĭ à¹īำ",
+      "ĠH óa",
+      "×ŀר ×Ĺק",
+      "ØŃÙħ اÙħ",
+      "بÙĪ Ùĥ",
+      "ĠArt ÃŃculo",
+      "ãĥĦ ãĤ¢ãĥ¼",
+      "×Ķפ ׼×Ķ",
+      "×Ĺ׾ ×ķף",
+      "ĠпеÑĢе Ñħод",
+      "len miÅŁ",
+      "زر اعة",
+      "Ġseñ or",
+      "ãģ£ãģ¦ ãģįãģ¦",
+      "Ø¥ Ø´",
+      "إش ارة",
+      "Ġpod ÃŃa",
+      "ĠÃľ lke",
+      "н ÑģкаÑı",
+      "Ġadapt é",
+      "Ġdüzen len",
+      "Ġdüzenlen en",
+      "ĠÑģÑĤ ала",
+      "ĠÙĬ ØŃتاج",
+      "Ġn ier",
+      "Ġnier uch",
+      "Ġnieruch omo",
+      "Ġnieruchomo ÅĽci",
+      "ãģĵãģ¨ãģĮ ãģĤãĤĭ",
+      "ยà¸Ńà¸Ķ à¹Ģยีà¹Īยม",
+      "ĠÙħ ج",
+      "ĠÙħج اÙĨÙĬ",
+      "Ġз аб",
+      "Ġзаб ол",
+      "Ġзабол ев",
+      "Ġзаболев аниÑı",
+      "ĠÅĽ ro",
+      "ĠÅĽro dk",
+      "ĠÅĽrodk ów",
+      "Ġ×Ķ ׾×IJ×ķ×ŀ×Ļ",
+      "Ġdok ÅĤad",
+      "ĠdokÅĤad nie",
+      "ãģŁãģı ãģªãģĦ",
+      "ãģ¯ãģļ ãģ§ãģĻ",
+      "ãģ¨æĢĿ ãģ£ãģ¦ãģĦãģŁ",
+      "é cran",
+      "ìĹħ ì²´",
+      "trzym aÅĤ",
+      "ÑģÑĤв еннÑĭй",
+      "ĠNot ÃŃc",
+      "ĠNotÃŃc ias",
+      "Ùħ رÙĬ",
+      "ÙħرÙĬ ض",
+      "æ°Ĺ è»",
+      "æ°Ĺè» ½",
+      "æ°Ĺ軽 ãģ«",
+      "ëĵ £",
+      "Ġ×ĵ ×ķ×IJר",
+      "Ġ׾ ×ŀ׳",
+      "Ġ׾×ŀ׳ ×ķ×¢",
+      "ĠçalÄ±ÅŁ ıyor",
+      "ĠÅŁ idd",
+      "ĠÅŁidd et",
+      "ĠM ặt",
+      "Ġate ÅŁ",
+      "ĠполÑĥÑĩ ениÑı",
+      "à¹Ģà¸Ħรืà¹Īà¸Ńà¸ĩ มืà¸Ń",
+      "Ġgrö ÃŁer",
+      "د ائ",
+      "دائ رة",
+      "Ġbul un",
+      "Ġbulun maktadır",
+      "à¹Ģห ร",
+      "à¹Ģหร ีย",
+      "à¹Ģหรีย à¸į",
+      "à¸Ļัà¸ģ à¸Ĺà¹Īà¸Ńà¸ĩà¹Ģà¸Ĺีà¹Īยว",
+      "Ġalan ında",
+      "ĠÑĥ зна",
+      "Ġл еÑĩение",
+      "売 ãĤĮ",
+      "Ġçev ir",
+      "Ġdeste ÄŁi",
+      "ĠheiÃŁ t",
+      "âĸ ²",
+      "ØŃ Ø·",
+      "à¸Ħำ à¸ķà¸Ńà¸ļ",
+      "ãĤªãĥ³ ãĥ©ãĤ¤ãĥ³",
+      "Ġ×ij×Ĺ×Ļ ×Ļ×Ŀ",
+      "ãĥ¦ ãĥĭ",
+      "Ġdüzenle me",
+      "Ġmodal itÃł",
+      "سر ط",
+      "سرط اÙĨ",
+      "×ŀ׼ ×ķף",
+      "ĠданнÑĭ й",
+      "تر ت",
+      "ترت ÙĬب",
+      "à¸ļาà¸ĩ à¸Ħà¸Ļ",
+      "ĠÄIJ á»ĭnh",
+      "ม ูล",
+      "มูล à¸Ħà¹Īา",
+      "ÙĨ ÙĤص",
+      "à¸ģาร รัà¸ģษา",
+      "ĠÑĦ он",
+      "ĠÑĦон д",
+      "ãĤĪãģĨ ãģ«ãģªãģ£ãģŁ",
+      "Ùħع اÙĦ",
+      "ÙħعاÙĦ جة",
+      "ĠOs man",
+      "ĠOsman lı",
+      "иÑĩеÑģк ом",
+      "à¸Ńยาà¸ģ à¸Īะ",
+      "ãģķãģ¾ ãģĸ",
+      "ãģķãģ¾ãģĸ ãģ¾",
+      "ãģķãģ¾ãģĸãģ¾ ãģª",
+      "Ġת ×ķ׼׾",
+      "×¢ צ×ij",
+      "ĠاÙĦع سÙĥ",
+      "ĠاÙĦعسÙĥ رÙĬ",
+      "Ġvé hic",
+      "Ġvéhic ule",
+      "Ġ×Ļצ ×Ĺק",
+      "ĠاÙĦÙĪ ØŃ",
+      "ĠاÙĦÙĪØŃ ÙĬد",
+      "ĠاÙĦع دÙĪ",
+      "ĠQu ản",
+      "Ġê³µ ëıĻ",
+      "بد ÙĦ",
+      "ĠÄij ảng",
+      "Ġm á»ĩnh",
+      "Ġnie zb",
+      "Ġniezb ÄĻ",
+      "ĠniezbÄĻ dn",
+      "Ġyayın lan",
+      "обÑī и",
+      "Ġgö tür",
+      "צ פ",
+      "צפ ×ķ×Ļ",
+      "ĠÙĦÙĬ بÙĬ",
+      "ĠÙĦÙĬبÙĬ ا",
+      "ØŃ ÙĪا",
+      "Ġд об",
+      "Ġдоб ÑĢо",
+      "иÑĢÑĥ ем",
+      "ĠاÙĦØŃÙĥÙĪÙħ ÙĬØ©",
+      "m Ã¤ÃŁig",
+      "Ġed ición",
+      "влек аÑĤелÑĮ",
+      "влекаÑĤелÑĮ н",
+      "Ġת ש׾×ķ×Ŀ",
+      "Ġ×Ķש ×ķ׳×Ļ×Ŀ",
+      "มิ à¸ĸุ",
+      "มิà¸ĸุ à¸Ļ",
+      "มิà¸ĸุà¸Ļ ายà¸Ļ",
+      "é£Łãģ¹ ãģ¦",
+      "ĠìĪĺ ì§ij",
+      "ס ×ij×Ļ",
+      "ĠиÑİ Ð»Ñı",
+      "Ġà¹Ħà¸Ķà¹ī à¹ģà¸ģà¹Ī",
+      "׾×Ĺ ×Ŀ",
+      "tr ä",
+      "trä gt",
+      "ãģĿãĤĤ ãģĿãĤĤ",
+      "ÐĿ Ðķ",
+      "Ġв нÑĥÑĤ",
+      "ĠвнÑĥÑĤ ÑĢи",
+      "ãģ¨ ä¸Ģç·Ĵãģ«",
+      "ãĤ« ãĥķãĤ§",
+      "Ġ×ij×Ĺ ×ĵר",
+      "×Ĺ ×ŀש",
+      "ãĤ¨ ãĥį",
+      "ãĤ¨ãĥį ãĥ«",
+      "ãĤ¨ãĥįãĥ« ãĤ®",
+      "ãĤ¨ãĥįãĥ«ãĤ® ãĥ¼",
+      "à¸Ĥà¸Ńà¸ĩ à¸ķัวà¹Ģà¸Ńà¸ĩ",
+      "بÙĤ اء",
+      "פס ×Ļ׼",
+      "פס×Ļ׼ ×ķ׾×ķ×Ĵ",
+      "ãĥ¡ ãĥĥ",
+      "ãĥ¡ãĥĥ ãĤ»",
+      "ãĥ¡ãĥĥãĤ» ãĥ¼ãĤ¸",
+      "ÙĦ ÙĤب",
+      "A Äŀ",
+      "שק ×Ļ×¢",
+      "ÙĤ ساÙħ",
+      "×ĵ×ķ×Ĵ ×ŀ×Ķ",
+      "æ·± ãģĦ",
+      "íĸĪ ëĬĶëį°",
+      "ĠrozwiÄħz anie",
+      "à¸Ļัà¹Īà¸Ļ à¹Ģà¸Ńà¸ĩ",
+      "×Ļצ ×ij",
+      "Ġtr ông",
+      "à¹ĥà¸Ĭà¹ī à¸ļริà¸ģาร",
+      "ĠاÙĦÙħÙĪ سÙħ",
+      "ĠдеÑĤ и",
+      "ãģĹãģĭ ãģªãģĦ",
+      "ס ×Ļף",
+      "Ġréfé rence",
+      "à¹ģห à¹īà¸ĩ",
+      "ãĤĤãĤī ãģ£ãģŁ",
+      "Ġ׾ ר׼",
+      "Ġ׾ר׼ ×ķש",
+      "شع ÙĪر",
+      "ĠÐij ог",
+      "Ġlaz ım",
+      "Ġ×Ļש ׳×Ŀ",
+      "Ġп аÑĢÑĤ",
+      "ĠпаÑĢÑĤ неÑĢ",
+      "ĠÑĥ ника",
+      "ĠÑĥника лÑĮн",
+      "Ġmaté riel",
+      "×ŀר ק",
+      "Ġph Æ°á»Ŀng",
+      "Ġз ай",
+      "Ġзай м",
+      "Ùģ ÙĤد",
+      "Univers itÃł",
+      "×¢ ר׼×Ļ×Ŀ",
+      "Ġba ño",
+      "Ġн оÑı",
+      "ĠноÑı бÑĢÑı",
+      "à¸Ľ à¹īาย",
+      "Ġt ats",
+      "Ġtats äch",
+      "Ġtatsäch lich",
+      "ĠÑĤÑĢ еÑĤÑĮ",
+      "Ñį м",
+      "ãĥĻ ãĥ¼ãĤ¹",
+      "Ġnh á»±a",
+      "ìĬ¤ íģ¬",
+      "ĠعبداÙĦ ÙĦÙĩ",
+      "Ġת ×ķר×Ķ",
+      "أش ÙĬ",
+      "أشÙĬ اء",
+      "ĠÙĦÙĦ غا",
+      "ĠÙĦÙĦغا ÙĬØ©",
+      "Ùħ ÙĪاÙĤ",
+      "ÙħÙĪاÙĤ Ùģ",
+      "ĠgÅĤówn a",
+      "Ġart Ä±ÅŁ",
+      "Ġ×ŀק ×ķ×ŀ×Ļ",
+      "ãĤ¯ãĥ© ãĥĸ",
+      "Ġس ÙĪÙī",
+      "ĠìŬ ìĦ±",
+      "اس ر",
+      "اسر ائÙĬÙĦ",
+      "Ġ׳ ×Ľ×ª×ij",
+      "ย à¹īà¸Ńà¸Ļ",
+      "Ġdeber á",
+      "Ġph ẫu",
+      "ÑİÑī ем",
+      "ĠÙĦدÙĬ ÙĨا",
+      "×ŀ×ĺ ×Ķ",
+      "Ġ׳ ×ķ׾×ĵ",
+      "ĠвÑģÑĤÑĢ еÑĩа",
+      "ãĤīãĤĮ ãģ¦ãģĦãģ¾ãģĻ",
+      "ĠcaÅĤ ej",
+      "ย ึ",
+      "ยึ à¸Ķ",
+      "поÑĤ ен",
+      "поÑĤен ÑĨи",
+      "Ġл иÑĤ",
+      "ĠлиÑĤ еÑĢ",
+      "ĠлиÑĤеÑĢ аÑĤÑĥÑĢ",
+      "Ġкажд ом",
+      "ĠíĮ IJ",
+      "ĠíĮIJ ëĭ¨",
+      "à¸Ī ู",
+      "Ġpres ença",
+      "ãģªãĤĵ ãģ§",
+      "Ùħ ÙĬاÙĩ",
+      "ин ÑĦоÑĢм",
+      "инÑĦоÑĢм аÑĨион",
+      "инÑĦоÑĢмаÑĨион н",
+      "ĠìŀIJ ìĹ°",
+      "ר׼ ש",
+      "Ġöd ül",
+      "ç¶ļ ãģı",
+      "Ġп Ñģ",
+      "ĠпÑģ иÑħ",
+      "ĠпÑģиÑħ олог",
+      "ت Ø°Ùĥر",
+      "Ġìŀħ ìŀ¥",
+      "ล à¸Ķà¹Į",
+      "ìĦł ê±°",
+      "ãģ£ãģ¦ ãģĬãĤĬãģ¾ãģĻ",
+      "Ġ×Ļ ×¢",
+      "Ġ×Ļ×¢ ק×ij",
+      "ĠاÙĦØ· عاÙħ",
+      "ãĥĨ ãĤ¹ãĥĪ",
+      "ĠTu ấn",
+      "Ġparticip ación",
+      "×ŀ×ķ×ŀ ×Ĺ×Ķ",
+      "×Ĵר ס×Ķ",
+      "ĠاÙĦتÙĨ ÙģÙĬ",
+      "ĠاÙĦتÙĨÙģÙĬ Ø°ÙĬ",
+      "ĠбезопаÑģ н",
+      "ge f",
+      "gef ähr",
+      "Ø´ ÙĪر",
+      "Ġmy ÅĽli",
+      "ÙĪا Ø´ÙĨ",
+      "ÙĪاشÙĨ Ø·ÙĨ",
+      "׳×ķס ×¢",
+      "Ùĥ Ùĩ",
+      "ÙĥÙĩ رب",
+      "ÙĥÙĩرب اء",
+      "Ġmus iaÅĤ",
+      "ìĭ ¸",
+      "ãĥĸãĥ© ãĥĥãĤ¯",
+      "Ġcré é",
+      "ÙĨÙĩ ار",
+      "owo ÅĽÄĩ",
+      "ÙħØŃا ÙĥÙħ",
+      "ĠwÅĤa ÅĽ",
+      "ĠwÅĤaÅĽ c",
+      "ĠwÅĤaÅĽc iciel",
+      "ĠÙĬ ؤ",
+      "ĠÙĬؤ دÙĬ",
+      "×ŀ×¢ ×ķ׳",
+      "×IJ ×ij׾",
+      "خط أ",
+      "ĠÑħ олод",
+      "×ĸ ×ķ׾",
+      "ãģĵãĤĮ ãĤī",
+      "ãģĵãĤĮãĤī ãģ®",
+      "Ġbás ica",
+      "ฤ à¸Ķ",
+      "ฤà¸Ķ ูà¸ģ",
+      "ฤà¸Ķูà¸ģ า",
+      "ฤà¸Ķูà¸ģา ล",
+      "èIJ½ãģ¡ çĿĢ",
+      "ãģªãģĦ ãģĵãģ¨",
+      "ص ÙĪÙħ",
+      "ÙĨج ØŃ",
+      "׳ק ×ķ×ĵ",
+      "׳ק×ķ×ĵ ת",
+      "кл аÑģÑģ",
+      "íķĺìĭľ ëĬĶ",
+      "ëĦ ĺ",
+      "Ġש×IJ ×Ļ׳×ķ",
+      "ĠС ейÑĩаÑģ",
+      "may acaģı",
+      "Ġyap ılır",
+      "Ġcategor ÃŃa",
+      "عب اد",
+      "ĠТ еп",
+      "ĠТеп еÑĢÑĮ",
+      "×Ķ×Ļס×ĺ ×ķר×Ļ",
+      "h ế",
+      "ãĤ³ ãĥ¼ãĥī",
+      "Ġcabe ça",
+      "ج Ùħا",
+      "جÙħا Ùĩ",
+      "جÙħاÙĩ ÙĬر",
+      "ä½İ ãģĦ",
+      "ĠÑĤоваÑĢ ов",
+      "à¸Ĭาว à¸ļà¹īาà¸Ļ",
+      "ĠÑģÑĤан ов",
+      "ĠÑģÑĤанов иÑĤÑģÑı",
+      "ĠавÑĤом обилÑĮ",
+      "ĠÑģлÑĥÑĩ ай",
+      "à¸Ńั à¸ŀ",
+      "ĠG iriÅŁ",
+      "ĠìĿ¼ ëĭ¨",
+      "ĠпÑĢ оÑģ",
+      "ĠпÑĢоÑģ моÑĤÑĢ",
+      "ãģªãģıãģª ãģ£ãģŁ",
+      "มี à¸Ľà¸±à¸įหา",
+      "ïº İ",
+      "éc oute",
+      "ĠÙħ ÙĪجÙĪد",
+      "Ġس رÙĬع",
+      "ĠÙĪÙĩ ÙĨا",
+      "ĠÙĪÙĩÙĨا Ùĥ",
+      "à¸Ħุà¸ĵ สม",
+      "à¸Ħุà¸ĵสม à¸ļัà¸ķิ",
+      "Ġìļ° ìĦł",
+      "à¸ŀระ à¸ŀุà¸Ĺà¸ĺ",
+      "好 ãģ¿",
+      "ظ ÙĦÙħ",
+      "Ġм акÑģ",
+      "ĠмакÑģ ималÑĮ",
+      "ĠмакÑģималÑĮ но",
+      "ãĥª ãĤ¢ãĥ«",
+      "à¹ģมà¹ī วà¹Īา",
+      "ĠاÙĦØŃ ÙĪار",
+      "ãĥĹãĥ© ãĤ¹",
+      "Ġع ÙĦاÙĤØ©",
+      "Ġíĸī ëıĻ",
+      "Ġgönder il",
+      "Ġl ãi",
+      "ĠsaÄŁ lıkl",
+      "ĠsaÄŁlıkl ı",
+      "ĠÑĪ аг",
+      "Ġ×ij×IJר ×Ķ",
+      "prowadzi Äĩ",
+      "ãģĦãģı ãģ¤ãģĭ",
+      "Ġبت ارÙĬØ®",
+      "Ġ×ij×IJ×ķת ×Ķ",
+      "Ġmó c",
+      "ĠÐľ не",
+      "ãĥĹãĥ¬ ãĥ¼",
+      "×IJ ×ĸר×Ĺ",
+      "åł´åIJĪ ãģ«ãģ¯",
+      "使 ãģĪ",
+      "à¹Ģร ืà¸Ńà¸Ļ",
+      "ĠÐŁ еÑĤ",
+      "ĠÐŁÐµÑĤ ÑĢ",
+      "ãģ«åħ¥ ãĤĭ",
+      "Ùħ ادة",
+      "à¹Ģà¸ĩ ืà¹Īà¸Ńà¸Ļ",
+      "à¹Ģà¸ĩืà¹Īà¸Ńà¸Ļ à¹Ħà¸Ĥ",
+      "ĠÑģоÑģÑĤоÑı ние",
+      "ôn ica",
+      "ĠÑĦ ев",
+      "ĠÑĦев ÑĢа",
+      "ĠÑĦевÑĢа лÑı",
+      "Ġ×ķ ×ĸ",
+      "Ġ×ķ×ĸ ×IJת",
+      "à¸Ħร ิ",
+      "à¸Ħริ ส",
+      "ĠÐķ Ñīе",
+      "ãģ£ãģ¦ãģĹãģ¾ ãģĦãģ¾ãģĹãģŁ",
+      "ĠпÑĢав иÑĤелÑĮ",
+      "ĠпÑĢавиÑĤелÑĮ ÑģÑĤв",
+      "Ġtä glich",
+      "Ġëĭ¹ ìĭľ",
+      "×ŀ×ķ×¢ ×ŀ×ĵ",
+      "Ġдв оÑĢ",
+      "æī ķ",
+      "æīķ ãģĦ",
+      "ĠÑģÑĤан еÑĤ",
+      "Ġвозд ейÑģÑĤв",
+      "ĠвоздейÑģÑĤв и",
+      "Ġf ête",
+      "à¹Ģส า",
+      "תק ×ķ×ķ×Ķ",
+      "Ġu yar",
+      "Ġuyar ı",
+      "à¸ģลัà¸ļ à¹Ħà¸Ľ",
+      "Ġgi Æ°á»Ŀng",
+      "Ġв а",
+      "Ġва ÑĪи",
+      "ĠÄij áºŃu",
+      "ĠSpa ÃŁ",
+      "ĠìķĦ ë§Ī",
+      "à¹Ħà¸Ķà¹ī à¸ĩà¹Īาย",
+      "Ġ×Ķ×ŀ ×ijקש",
+      "æĸ° ãģŁ",
+      "æĸ°ãģŁ ãģª",
+      "ılı yor",
+      "пл ан",
+      "Ġ×Ķ×ijר ×Ļ×IJ×ķת",
+      "ĠaÄŁ rı",
+      "Ġsay gı",
+      "建 ãģ¦",
+      "Ġnaj wyż",
+      "Ġnajwyż sz",
+      "سÙĬاس ات",
+      "ãģĬ å¾Ĺ",
+      "ĠاÙĦع ÙĦÙĬ",
+      "ĠاÙĦعÙĦÙĬ ا",
+      "Ġcoraz ón",
+      "ì¹ĺ ë£Į",
+      "หัว à¸Ĥà¹īà¸Ń",
+      "Ġب ØŃÙĬ",
+      "ĠبØŃÙĬ Ø«",
+      "зв езд",
+      "بÙĪ ابة",
+      "ÐĽ Ðĺ",
+      "ÙĦا زÙħ",
+      "Ġroz p",
+      "Ġrozp oc",
+      "Ġrozpoc zÄĻ",
+      "触 ãĤĮ",
+      "ĠاÙĦج ÙħÙĩ",
+      "ĠاÙĦجÙħÙĩ ÙĪر",
+      "Ġsp ÄĻd",
+      "ĠspÄĻd z",
+      "วิà¸Ĺยา ศาสà¸ķรà¹Į",
+      "ив аеÑĤÑģÑı",
+      "Ġдан ной",
+      "Ġreprés ente",
+      "ĠÄij á»ĭch",
+      "Ġ×¢×ŀ ×ķק",
+      "à¸Ńัà¸Ļ à¸ķร",
+      "à¸Ńัà¸Ļà¸ķร าย",
+      "Ġestr atég",
+      "Ġestratég ia",
+      "pad ÅĤ",
+      "Ġв полн",
+      "Ġвполн е",
+      "ĠпÑĢедоÑģÑĤав лен",
+      "×Ĺ׾ ×ķק",
+      "×Ĺ׾×ķק ת",
+      "ãĤ¢ ãĥĬ",
+      "ĠاÙĦغ Ø°",
+      "ĠاÙĦغذ ائÙĬ",
+      "ĠÑĥ зн",
+      "ĠÑĥзн аÑĤÑĮ",
+      "à¸ĭ à¹īาย",
+      "å½ĵ ãģ¦",
+      "ØŃÙĬ اء",
+      "Ġbás ico",
+      "ק×ķ×ij ×¢",
+      "ĠاÙĦÙħ باراة",
+      "ĠاÙĦÙĩ اتÙģ",
+      "Ġ׼ ׳×Ĵ×ĵ",
+      "à¸Ľà¸£à¸° หย",
+      "à¸Ľà¸£à¸°à¸«à¸¢ ัà¸Ķ",
+      "Ðļ ак",
+      "à¸Ĺีà¹Ī à¸Ļà¹Īา",
+      "à¸Ĺีà¹Īà¸Ļà¹Īา สà¸Ļà¹ĥà¸Ī",
+      "ãģ¾ ãģģ",
+      "ï½ ¢",
+      "Ñģк оп",
+      "Ġson rasında",
+      "Ġur zÄħd",
+      "ĠurzÄħd zenia",
+      "׼×ķ ×ķ׳",
+      "׼×ķ×ķ׳ ת",
+      "Ġ׾×Ķת ×ŀ×ķ×ĵ",
+      "Ġ׾×Ķת×ŀ×ķ×ĵ ×ĵ",
+      "ĠÑģ ли",
+      "ĠÑģли ÑĪ",
+      "ĠÑģлиÑĪ ком",
+      "ĠÑģÑĤ Ñĥд",
+      "ĠÑģÑĤÑĥд енÑĤ",
+      "Ġ×Ķ ×ķ×ĵ",
+      "Ġ×Ķ×ķ×ĵ ×¢×Ķ",
+      "ë¹Ħ ìļ©",
+      "à¸Ńยาà¸ģ à¹ĥหà¹ī",
+      "Ġb á»ģ",
+      "ยุ à¸Ĺà¸ĺ",
+      "Ðĺ ÐĿ",
+      "س ائر",
+      "Ø£ صÙĪÙĦ",
+      "ĠاÙĦغ رÙģ",
+      "ãģĵãģ¨ãĤĤ ãģĤãĤĬãģ¾ãģĻ",
+      "è¾¼ ãģ¾ãĤĮ",
+      "ĠاÙĦساب ع",
+      "Ġc ủ",
+      "ãģĦãģŁãģł ãģĦãģŁ",
+      "ì§ ĵ",
+      "ìĤ¬ 무",
+      "powied ź",
+      "تÙģ Ùĥ",
+      "تÙģÙĥ ÙĬر",
+      "иÑĢов ки",
+      "ĠíĨµ íķ´ìĦľ",
+      "ãĤ¨ ãĤ¹ãĥĨ",
+      "ĠдеÑıÑĤелÑĮ ноÑģÑĤÑĮ",
+      "ĠданнÑĭ м",
+      "Ġ×¢ ×ķר",
+      "Ġ×¢×ķר ׼×Ļ",
+      "×ķ×ĵ עת",
+      "Ġhayat ını",
+      "Ġb Äħd",
+      "ĠbÄħd ź",
+      "obs ÅĤug",
+      "à¹Ģà¸ŀียà¸ĩ à¹ģà¸Ħà¹Ī",
+      "à¸ĭ à¹Īา",
+      "è²ł ãģij",
+      "ĠÑģÑĤÑĢ ем",
+      "ĠÄij á»īnh",
+      "ĠÐł ÑĥÑģ",
+      "ĠN ữ",
+      "Ġ׾×Ķש ×Ļ×Ĵ",
+      "Ġjed noc",
+      "Ġjednoc ze",
+      "Ġjednocze ÅĽnie",
+      "Ġ×Ķ×Ĵ ×ij×ķ×Ķ",
+      "أخ ÙĦاÙĤ",
+      "ĠнаÑģ ел",
+      "ĠнаÑģел ениÑı",
+      "ĠÙĬ ÙĨب",
+      "ĠÙĬÙĨب غÙĬ",
+      "ãģĮ ãģĭ",
+      "ãģĮãģĭ ãģĭ",
+      "×Ĵ עת",
+      "Ðŀ Ðł",
+      "ĠналиÑĩ ии",
+      "Ġë§Ī ì§Ģ",
+      "Ġë§Īì§Ģ ë§ī",
+      "Ġíĸī ìĤ¬",
+      "Ġtre ÅĽci",
+      "Ġê°Ģ ì¹ĺ",
+      "ì¦ ĺ",
+      "Ġана лог",
+      "×Ķצע ת",
+      "в лад",
+      "влад е",
+      "ĠÑģдел ал",
+      "Ġ׳ ×Ĵ×Ļש",
+      "Ġ׳×Ĵ×Ļש ×ķת",
+      "полн ение",
+      "à¸Ĩ à¹Īา",
+      "ĠD ön",
+      "׼׾׼ ׾×Ķ",
+      "×ŀ×ĸ ×Ĵ",
+      "Ùħ Ùģ",
+      "ÙħÙģ Ùĩ",
+      "ÙħÙģÙĩ ÙĪÙħ",
+      "×Ķ ×ĵ",
+      "×Ķ×ĵ פס",
+      "×Ķ×ĵפס ×Ķ",
+      "ãģĻãģİ ãģ¦",
+      "Ġг ÑĢ",
+      "ĠгÑĢ н",
+      "×ŀ×ĺ ×ķס",
+      "Ġ기 ìĸµ",
+      "ï¾ Ł",
+      "ĠpÅĤ yn",
+      "ĠGr ünde",
+      "ĠBü cher",
+      "Ġwed ÅĤug",
+      "ãģ¾ãģł ãģ¾ãģł",
+      "Ġ׳×Ķ ×ĵר",
+      "ĠÙĬست Ø·ÙĬع",
+      "ĠHi á»ĩp",
+      "ãĤŃãĥ£ãĥ³ ãĥļ",
+      "ãĤŃãĥ£ãĥ³ãĥļ ãĥ¼ãĥ³",
+      "Ġth á»ķ",
+      "Ġeuropé enne",
+      "à¸ļ ัà¸ĩ",
+      "à¸ļัà¸ĩ à¸Ħัà¸ļ",
+      "ĠszczegóÅĤ owo",
+      "׳ שק",
+      "ãĥķ ãĥ©ãĥ³ãĤ¹",
+      "×ŀ×ķ×ŀ ×Ĺ×Ļ",
+      "Ġcom ún",
+      "Ġç arp",
+      "ØŃت ÙĬا",
+      "ØŃتÙĬا ج",
+      "ØŃتÙĬاج ات",
+      "ëĭ´ ëĭ¹",
+      "ä½ķ 度",
+      "ä½ķ度 ãĤĤ",
+      "×ĵ ×ijק",
+      "ãģį ãĤĮ",
+      "ãģįãĤĮ ãģĦ",
+      "Ġк ам",
+      "Ġкам еÑĢ",
+      "ĠespecÃŃf ico",
+      "Ġtel éfono",
+      "à¸ķัà¹īà¸ĩ à¸Ńยูà¹Ī",
+      "I Åŀ",
+      "ãģ© ãĤĵãģ©",
+      "ãģ©ãĤĵãģ© ãĤĵ",
+      "עצ ×ŀ×IJ×Ļ",
+      "à¸Ķัà¸ĩ à¸Ļีà¹ī",
+      "ĠÑĦоÑĢм иÑĢов",
+      "ĠÑĦоÑĢмиÑĢов а",
+      "×ķ×ŀ ×ij",
+      "Ġkullan ımı",
+      "Ðľ Ðŀ",
+      "×¢ ש×Ļ",
+      "עש×Ļ ×Ļ×Ķ",
+      "Ġön lem",
+      "à¹Ģà¸Ń à¹ĩ",
+      "à¹Ģà¸Ńà¹ĩ ม",
+      "×ŀשק ×Ļ×¢",
+      "ר ×Ļ×Ĺ",
+      "à¸Ĥ ัà¸Ķ",
+      "ĠíĻ ľ",
+      "ĠíĻľ ìļ©",
+      "à¸ĭ ะ",
+      "ãĤĪãģĨ ãģ«ãģªãĤĬãģ¾ãģĹãģŁ",
+      "ĠÑĢаÑģ пÑĢ",
+      "ĠÑĢаÑģпÑĢ оÑģÑĤ",
+      "ĠÑĢаÑģпÑĢоÑģÑĤ ÑĢан",
+      "ĠÑĢаÑģпÑĢоÑģÑĤÑĢан ен",
+      "׼×Ļ ×ķף",
+      "ÙĤب ض",
+      "تص رÙĬØŃ",
+      "تصرÙĬØŃ Ø§Øª",
+      "Ġо ÑĢи",
+      "ĠоÑĢи г",
+      "ĠоÑĢиг ина",
+      "ĠоÑĢигина л",
+      "ĠاÙĦع اÙĦÙĬ",
+      "à¹ģหà¹Īà¸ĩ à¸Ļีà¹ī",
+      "ãĥķãĤ¡ ãĥ¼",
+      "ãģ¦ãģĦ ãģį",
+      "ãģ¦ãģĦãģį ãģŁãģĦ",
+      "פ תר",
+      "פתר ×ķ׳×ķת",
+      "Ġ×ij ×Ļ×Ĺ",
+      "Ġ×ij×Ļ×Ĺ ×ĵ",
+      "Ġod by",
+      "Ġodby ÅĤ",
+      "ĠоÑĩеÑĢ ед",
+      "Ġtr Æ°Æ¡ng",
+      "ãĤŃ ãĥ³",
+      "×ŀ ×ķפ",
+      "×ŀ×ķפ ×¢",
+      "ëĵľ 립",
+      "ëĵľë¦½ ëĭĪëĭ¤",
+      "à¸ŀืà¹īà¸Ļ à¸IJาà¸Ļ",
+      "ìŀIJ 격",
+      "ĠVi á»ĩn",
+      "ĠDes pués",
+      "Ġ×IJ׾ ×Ļ׳×ķ",
+      "Ġdur ée",
+      "íĩ ´",
+      "Ġmü zik",
+      "i ếu",
+      "ĠÑĢаз меÑīен",
+      "Ġк Ñĥд",
+      "ĠкÑĥд а",
+      "غ ض",
+      "غض ب",
+      "ĠTamb ém",
+      "à¸Īัà¸Ķ สà¹Īà¸ĩ",
+      "à¸ģาร à¹ģสà¸Ķà¸ĩ",
+      "onom ÃŃa",
+      "Ġан г",
+      "Ġанг ли",
+      "Ġангли й",
+      "Ġанглий Ñģк",
+      "Ġzn al",
+      "Ġznal az",
+      "Ġznalaz ÅĤ",
+      "תר ×Ĵ",
+      "תר×Ĵ ×ķ×Ŀ",
+      "ĠÑģ нов",
+      "ĠÑģнов а",
+      "ĠÑĩаÑģ а",
+      "Ġcommun auté",
+      "ĠespecÃŃf ica",
+      "ĠL á»ĭch",
+      "Ġli é",
+      "Ùģ جر",
+      "à¹Ģà¸ģ à¹Īà¸ĩ",
+      "ع اÙĦ",
+      "عاÙĦ ج",
+      "Ø£ÙĨ ظ",
+      "Ø£ÙĨظ ÙħØ©",
+      "ES Ä°",
+      "ĠاÙĦØŃ Ø¯ÙĬد",
+      "à¸ŀระ à¸Ńà¸ĩà¸Ħà¹Į",
+      "Ġפר שת",
+      "Ġдв иж",
+      "Ġдвиж ениÑı",
+      "ĠاÙĦج ارÙĬ",
+      "à¸ĺาà¸Ļ ี",
+      "неÑģ ен",
+      "ĠاÙĦÙĨ ÙĩائÙĬ",
+      "Ġб еÑĢ",
+      "ĠбеÑĢ ем",
+      "ĠбеÑĢем енн",
+      "Ġdépart ement",
+      "à¹Ģà¸Ĺ ีย",
+      "à¹Ģà¸Ĺีย à¸ļ",
+      "ĠÐľ аÑĢи",
+      "ĠнекоÑĤоÑĢ ÑĭÑħ",
+      "об еÑģп",
+      "обеÑģп еÑĩен",
+      "×Ĺ ×ķ×ĸ",
+      "×Ĺ×ķ×ĸ ×Ķ",
+      "ÙĨت ج",
+      "à¸Īะ à¹Ħà¸Ķà¹īรัà¸ļ",
+      "á» °",
+      "Ġél éments",
+      "ع ط",
+      "عط اء",
+      "Ġt ắt",
+      "i á»ĩm",
+      "ÑİÑīиÑħ ÑģÑı",
+      "ãģĹãģ °",
+      "ãģĹãģ° ãĤīãģı",
+      "Ġпом ожеÑĤ",
+      "à¸Ĥà¸ĵะ à¸Ļีà¹ī",
+      "Ġ×¢ שר×ķת",
+      "éģķ ãģ£ãģ¦",
+      "ĠпÑĢ ог",
+      "ĠпÑĢог н",
+      "ĠпÑĢогн оз",
+      "Ġt ÅĤ",
+      "ĠtÅĤ um",
+      "ĠtÅĤum acz",
+      "T ür",
+      "Tür kiye",
+      "ãģį ãģ£",
+      "ãģįãģ£ ãģĭãģij",
+      "Ġ×Ķ׳ ×ķ׼",
+      "Ġ×Ķ׳×ķ׼ ×Ĺ×Ļ",
+      "ĠìĥĿ ìĤ°",
+      "ĠÑĦоÑĢм Ñĭ",
+      "ç¾İ ãģĹãģĦ",
+      "à¸Ľà¸£ ึà¸ģ",
+      "à¸Ľà¸£à¸¶à¸ģ ษา",
+      "Ġlum ière",
+      "ãĤª ãĥ¼ãĥĹ",
+      "ãĤªãĥ¼ãĥĹ ãĥ³",
+      "à¸Ľ ืà¸Ļ",
+      "วั สà¸Ķ",
+      "วัสà¸Ķ ุ",
+      "еÑĢÑĤ в",
+      "ÙĥÙĦ Ùģ",
+      "ï½ £",
+      "à¸ĺรรม à¸Ķา",
+      "׳ ×ĺר",
+      "ĠпÑĢедÑģÑĤав лÑıеÑĤ",
+      "Ġanál isis",
+      "Ġb ãi",
+      "با ÙĤÙĬ",
+      "à¸Ľà¸£à¸° à¹Ģà¸Ķ",
+      "à¸Ľà¸£à¸°à¹Ģà¸Ķ à¹ĩà¸Ļ",
+      "ĠÑģлÑĥÑĩ аÑı",
+      "ĠÑģлÑĥÑĩаÑı Ñħ",
+      "ÐĽ ÐIJ",
+      "สัà¸ĩ à¹Ģà¸ģ",
+      "สัà¸ĩà¹Ģà¸ģ à¸ķ",
+      "Ġprz ec",
+      "Ġprzec ież",
+      "Ùħ صÙĦ",
+      "ÙħصÙĦ ØŃØ©",
+      "ש×ķק ×ķ׾×ĵ",
+      "ĠобоÑĢÑĥд ованиÑı",
+      "Ġtr waÅĤ",
+      "رÙĪ Ùħ",
+      "ìķĪ ëĤ´",
+      "ĠNgh á»ĭ",
+      "Ø® Ø´",
+      "à¸ļา à¸Ħาร",
+      "à¸ļาà¸Ħาร à¹Īา",
+      "Ġоп ÑĨион",
+      "ĠÑģозд аниÑı",
+      "ãĤ³ ãĤ¹ãĥĪ",
+      "Ġ×Ķ×¢ ׾×Ļ",
+      "Ġ×Ķ×¢×ľ×Ļ ×ķף",
+      "lä uft",
+      "ãĥĻ ãĤ¹ãĥĪ",
+      "Ġr ê",
+      "Ġrê ve",
+      "×IJ ×ij×Ļ×ij",
+      "×Ļ ×Ļ×ļ",
+      "ë¶ Ļ",
+      "ãĤ¤ãĥ³ ãĥī",
+      "ÅĤo ży",
+      "ÅĤoży Äĩ",
+      "ع ائÙĦ",
+      "عائÙĦ Ø©",
+      "Ø£ ÙĪر",
+      "Ø£ÙĪر اÙĤ",
+      "à¸Ĺà¹īà¸Ńà¸ĩ à¸ĸ",
+      "à¸Ĺà¹īà¸Ńà¸ĩà¸ĸ ิà¹Īà¸Ļ",
+      "Ġä hn",
+      "Ġähn lich",
+      "ãĥŁ ãĥĭ",
+      "à¸ľ ู",
+      "à¸ľà¸¹ à¹īà¸Ļ",
+      "à¸ľà¸¹à¹īà¸Ļ ำ",
+      "ĠмаÑĤеÑĢиал Ñĭ",
+      "Ġкап иÑĤ",
+      "ĠкапиÑĤ ал",
+      "ï¼ ¦",
+      "Ġseç il",
+      "Ġh ứng",
+      "Ġintéress ant",
+      "ãģ£ãģ¦ ãģĦãģı",
+      "Ġe ÄŁer",
+      "ëIJĺ ìĹĪìĬµëĭĪëĭ¤",
+      "Ġan laÅŁma",
+      "ãģĶ åĪ©çĶ¨",
+      "Ġ×ij ×ĸ׼",
+      "Ġ×ij×ĸ׼ ×ķת",
+      "ëĿ¼ ë©´",
+      "ĠÙĬ ÙĪس",
+      "ĠÙĬÙĪس Ùģ",
+      "أسÙĦ ØŃØ©",
+      "ĠGef ühl",
+      "ĠноÑĢм алÑĮн",
+      "ãĥĻ ãĥ³",
+      "ãģķãĤĮ ãĤĭãģĵãģ¨",
+      "ĠÐij еÑģ",
+      "ãģ¨ãģĦ ãģĪãģ°",
+      "ĠÙħ ÙĩÙħ",
+      "ĠÙħÙĩÙħ Ø©",
+      "ãģ§ãģĹãĤĩãģĨ ãģŃ",
+      "ĠêµŃ ëĤ´",
+      "à¹Ģม à¹ĩà¸Ķ",
+      "×ŀ×ij קר",
+      "ĠاÙĦد ÙĨÙĬ",
+      "ĠاÙĦدÙĨÙĬ ا",
+      "à¸Ĭ ู",
+      "к ÑĢÑĥÑĤ",
+      "Ġtho áng",
+      "Ġ׳ ×ĵר",
+      "Ġ׳×ĵר ש",
+      "ĠÑĢаÑģÑģ казал",
+      "ĠAu ÃŁerdem",
+      "פ ×IJר",
+      "פ×IJר ק",
+      "Ġ×ŀש×Ĺק ×Ļ×Ŀ",
+      "צ ר׼×Ļ×Ŀ",
+      "×ŀ×ĵ ×ķ",
+      "×ŀ×ĵ×ķ ×Ļק",
+      "èĭ¦ ãģĹ",
+      "ĠÑģ иг",
+      "ĠÑģиг нал",
+      "ĠM á»įi",
+      "Ġtr ữ",
+      "Ġnast ÄĻp",
+      "ĠnastÄĻp nie",
+      "Ġì¶Ķ ì§Ħ",
+      "ĠاÙĦÙģ ÙĨد",
+      "ĠاÙĦÙģÙĨد ÙĤ",
+      "koÅĦ czyÅĤ",
+      "ส ีà¹Ī",
+      "ק ×Ļ×ij",
+      "ק×Ļ×ij ×ķ×¥",
+      "ĠнÑĥж нÑĭ",
+      "大 åĪĩ",
+      "大åĪĩ ãģª",
+      "æıĽ ãģĪ",
+      "ת ×ķס",
+      "ת×ķס פת",
+      "ãģ£ãģ¦ ãģĦãģªãģĦ",
+      "Ġм Ñı",
+      "ĠмÑı г",
+      "ĠмÑıг к",
+      "Ġjak ie",
+      "Ġjakie ÅĽ",
+      "à¸ķำ à¸ļ",
+      "à¸ķำà¸ļ ล",
+      "ĠìŀĪ ì§Ģ",
+      "×ij×ĺ ×IJ",
+      "ĠоÑĤлиÑĩ но",
+      "ÙĤ ÙIJ",
+      "ĠавÑĤом об",
+      "ĠавÑĤомоб и",
+      "ĠавÑĤомоби лÑı",
+      "دÙĬÙħÙĤرا Ø·ÙĬ",
+      "ĠاÙĦ ÙĪا",
+      "ĠاÙĦÙĪا ØŃد",
+      "Ġس ÙĪرÙĬØ©",
+      "Ø£ غÙĦ",
+      "أغÙĦ ب",
+      "ĠÑįк ÑĢан",
+      "ãĥĹ ãĥ©ãĤ¤",
+      "Ġjeste ÅĽ",
+      "ãĥIJ ãĥª",
+      "Ġ×Ķ×IJ ×ķ×ķ×Ļר",
+      "ائ Ùĥ",
+      "à¸Ńยà¹Īาà¸ĩ ยิà¹Īà¸ĩ",
+      "ÑĢ екÑĤ",
+      "Ġum o",
+      "Ġumo ż",
+      "Ġumoż li",
+      "Ġumożli w",
+      "Ġumożliw ia",
+      "Ġnäch ste",
+      "ĠìŀĪ ì§Ģë§Į",
+      "ĠпÑĢед н",
+      "ĠпÑĢедн аз",
+      "ĠпÑĢедназ наÑĩен",
+      "Ġma çı",
+      "Ġp omi",
+      "Ġpomi ÄĻd",
+      "ĠpomiÄĻd zy",
+      "ĠاÙĦÙĦ ÙĤاء",
+      "à¹Ģà¸Ķ à¸Ńะ",
+      "Ġнов оÑģÑĤи",
+      "×ŀ׊׾×Ķ",
+      "رÙĬاض ÙĬ",
+      "à¸Ķ à¸Ļ",
+      "à¸Ķà¸Ļ à¸ķรี",
+      "ب صر",
+      "ìĬ¤ íĥĢ",
+      "scri pción",
+      "Ġnap isa",
+      "Ġnapisa ÅĤ",
+      "Ġ׳ש ×ŀ×¢",
+      "ĠاÙĦÙħØŃ ÙĦÙĬ",
+      "Ġhi á»ĥn",
+      "×IJ ×Ĺ",
+      "×IJ׊ר×IJ×Ļ",
+      "Ġг ÑĢаниÑĨ",
+      "æīĭ ç¶ļãģį",
+      "Ùĥ سب",
+      "Ġà¹ģà¸ķà¹Ī à¸ĸà¹īา",
+      "à¸Ķาว à¸Ļà¹Į",
+      "à¸Ķาวà¸Ļà¹Į à¹Ĥหลà¸Ķ",
+      "ãĤĭãģĵãģ¨ãģĮãģ§ãģį ãģ¾ãģĻ",
+      "åŁºæľ¬ çļĦãģ«",
+      "ÙĪÙĦ اد",
+      "rä ume",
+      "د Ùģاع",
+      "×Ļצ ×¢",
+      "ĠO czy",
+      "ĠOczy wiÅĽcie",
+      "ĠÅ ģ",
+      "ĠÅģ a",
+      "اÙĦÙĬ اب",
+      "اÙĦÙĬاب اÙĨ",
+      "áºł I",
+      "ĠBir liÄŁi",
+      "×Ķ ×ķצ",
+      "×Ķ×ķצ ×IJת",
+      "ĠÄij ua",
+      "Ġê·¸ëŁ¬ ëĭĪê¹Į",
+      "Ġréal ité",
+      "ع ÙĦاÙĤات",
+      "J este",
+      "Jeste ÅĽ",
+      "Ġмн ож",
+      "Ġмнож еÑģÑĤво",
+      "ï¼ «",
+      "ãĥĹãĥŃ ãĤ¸ãĤ§",
+      "ãĥĹãĥŃãĤ¸ãĤ§ ãĤ¯ãĥĪ",
+      "ĠÑĦ л",
+      "ظ ÙĨ",
+      "×Ĵ׾ ×Ĵ׾",
+      "ĠmÅĤod zie",
+      "ĠmÅĤodzie ż",
+      "à¸Ļà¹īำ à¸ķา",
+      "à¸Ļà¹īำà¸ķา ล",
+      "ÐĽ Ðķ",
+      "×ij ×ķ×ĺ",
+      "Ġ׾×Ķ ×Ĵ×Ļ×ĵ",
+      "ãģĵãģ¨ãĤĤ ãģĤãĤĭ",
+      "ز اد",
+      "×ŀ×Ļ×ĵ ×¢",
+      "ĠgÅĤówn ie",
+      "ãĥı ãĤ¦",
+      "ãĥıãĤ¦ ãĤ¹",
+      "б ел",
+      "Ġét ape",
+      "ðŁĺ Ģ",
+      "Ġмод елÑĮ",
+      "a ģını",
+      "ש ×Ĺק",
+      "ש×Ĺק ף",
+      "Ġni ño",
+      "à¸Ĭ à¹īาà¸ĩ",
+      "à¹Ģล ีย",
+      "ĠÑĦоÑĢм е",
+      "ĠاÙĦØ´ رÙĬÙģ",
+      "ĠÑĥд аÑĢ",
+      "arr iv",
+      "arriv ée",
+      "Ġmies iÄĻ",
+      "ĠmiesiÄĻ cy",
+      "ØŃ Ø±Ùĥ",
+      "ØŃرÙĥ ات",
+      "ĠDi á»ħn",
+      "ÐĿ Ы",
+      "ãģ¾ãģ£ãģŁ ãģı",
+      "Ġ×Ļ ר×ķק",
+      "еÑģÑĤ еÑģÑĤв",
+      "еÑģÑĤеÑģÑĤв енн",
+      "Ġê·¸ ëŁ¼",
+      "ĠاÙĦÙħ تÙĪ",
+      "ĠاÙĦÙħتÙĪ سط",
+      "Ġbéné fic",
+      "Ġbénéfic ie",
+      "Ġwy bra",
+      "Ġwybra Äĩ",
+      "ĠاÙĦز ÙħÙĨ",
+      "ĠпÑĢин Ñı",
+      "ĠпÑĢинÑı л",
+      "Ùģر ØŃ",
+      "Ġk sz",
+      "Ġksz taÅĤ",
+      "ĠksztaÅĤ t",
+      "ק׾ ×ĺ",
+      "×ij×ĵ×Ļק ת",
+      "Ġgi ấ",
+      "Ġgiấ c",
+      "Ġpropriet Ãł",
+      "деÑĢж ан",
+      "ĠKö ln",
+      "ĠGü zel",
+      "×Ļפ ×ķ×Ļ",
+      "ĠCu á»Ļc",
+      "ÑįÑĤ аж",
+      "تر ÙĥÙĬ",
+      "ترÙĥÙĬ ز",
+      "лож ений",
+      "Ġп Ñĥ",
+      "ĠпÑĥ ÑĤи",
+      "اخت ÙĦاÙģ",
+      "åĩºãģ¦ ãģıãĤĭ",
+      "à¸ļุ à¸ģ",
+      "âĿ ¤",
+      "ÑĦ ан",
+      "פש ×ĺ",
+      "à¸ļัà¸Ļ à¹Ģà¸Ĺ",
+      "à¸ļัà¸Ļà¹Ģà¸Ĺ ิà¸ĩ",
+      "ĠاÙĦس اد",
+      "ĠاÙĦساد س",
+      "ĠاÙĦÙĤ ÙĪÙħ",
+      "ĠاÙĦÙĤÙĪÙħ ÙĬ",
+      "Ġyönet ici",
+      "Ùĩ ÙĪات",
+      "ÙĩÙĪات Ùģ",
+      "Ġrespons ável",
+      "Ġпод деÑĢжива",
+      "ĠاÙĦسÙĦ Ø·",
+      "ĠاÙĦسÙĦØ· ات",
+      "ãģĹãģ¦ ãģĬãģı",
+      "ãĥļ ãĥĥãĥĪ",
+      "à¸Ľ ุà¹Īม",
+      "Ġogl Äħda",
+      "ÙĨا ÙĤ",
+      "ÙĨاÙĤ Ø´",
+      "à¸Ħà¸Ńà¸Ļ à¹Ĥà¸Ķ",
+      "ĠMü sl",
+      "ĠMüsl ü",
+      "ĠMüslü man",
+      "ĠMo ż",
+      "ĠMoż na",
+      "Ġnum érique",
+      "Ġv á»ı",
+      "ĠسÙĬ تÙħ",
+      "Ġyer leÅŁ",
+      "монÑĤ аж",
+      "Ġgo ût",
+      "ãģ¦ ãģĬãĤĬãģ¾ãģĻ",
+      "ĠKh ánh",
+      "Ġе дин",
+      "Ġедин ÑģÑĤв",
+      "اÙĨ Ø®Ùģ",
+      "اÙĨØ®Ùģ اض",
+      "ìĭľ íĹĺ",
+      "Ġl ặng",
+      "ĠÑĢ олÑĮ",
+      "à¸ķัว à¹ģà¸Ĺà¸Ļ",
+      "à¸Ħà¹Īา à¹ĥà¸Ĭà¹ī",
+      "à¸Ħà¹Īาà¹ĥà¸Ĭà¹ī à¸Īà¹Īาย",
+      "Ġver füg",
+      "Ġverfüg bar",
+      "ìĻĶ ëĭ¤",
+      "ãģĦ ãģļ",
+      "ãģĦãģļ ãĤĮ",
+      "ĠиÑģÑģлед ованиÑı",
+      "меÑī а",
+      "×Ķ ×Ĺ",
+      "×Ķ×Ĺ ×ĸר",
+      "à¹ģà¸Ł à¸Ĭัà¹Īà¸Ļ",
+      "ت صرÙģ",
+      "Ø¥ رÙĩاب",
+      "Ġexerc ÃŃcio",
+      "Ġé lev",
+      "Ġélev é",
+      "สัà¸įà¸įา à¸ĵ",
+      "Ãĸ Z",
+      "ãĥĹ ãĥŃãĤ°",
+      "ãĥĹãĥŃãĤ° ãĥ©",
+      "ãĥĹãĥŃãĤ°ãĥ© ãĥł",
+      "Ġw ewnÄĻtrzn",
+      "Ġhen üz",
+      "é£Ľ ãģ³",
+      "à¹Ģà¸Ķ à¸Ńรà¹Į",
+      "Ñģ Ñĥж",
+      "ÑģÑĥж ден",
+      "شع ÙĪب",
+      "ãģ²ãģ¨ ãĤĬ",
+      "Ġwy ÅĤÄħ",
+      "ĠwyÅĤÄħ cznie",
+      "Ġпло Ñħо",
+      "ÐĶ Ðķ",
+      "Ạ¦",
+      "Ùģع اÙĦÙĬ",
+      "ÙģعاÙĦÙĬ ات",
+      "ĠاÙĦع شر",
+      "ÑģÑĤÑĥп ил",
+      "Ġy arg",
+      "Ġyarg ı",
+      "нÑİ Ñİ",
+      "×ķ×IJ ×ij",
+      "Ġu ç",
+      "Ġuç ak",
+      "ë² ½",
+      "تÙĪ ÙĤÙĬ",
+      "تÙĪÙĤÙĬ ع",
+      "Ġì¤ij ìĭ¬",
+      "׳×Ļ×ķ ×ķ×ĺ",
+      "Ø£ ÙĥÙĦ",
+      "ç½® ãģĦãģ¦",
+      "éłĤ ãģį",
+      "Ġ×Ķת ×ij",
+      "Ġ×Ķת×ij ×Ļ×¢×Ķ",
+      "Ġdür fen",
+      "Ùħ ÙĤاÙĦ",
+      "ÙħÙĤاÙĦ ات",
+      "Ġز ÙħÙĨ",
+      "à¸ŀฤ ศ",
+      "à¸ŀฤศ à¸Ī",
+      "à¸ŀฤศà¸Ī ิà¸ģ",
+      "à¸ŀฤศà¸Īิà¸ģ ายà¸Ļ",
+      "ĠнеÑģк олÑĮ",
+      "ĠнеÑģколÑĮ ки",
+      "ĠнеÑģколÑĮки Ñħ",
+      "Ġcrian ça",
+      "มิ à¸ķร",
+      "×ŀ׼ ×Ļר×ķת",
+      "à¸ģาร à¸ļริหาร",
+      "Ġtélé charg",
+      "Ġ×IJ×ķ×Ķ ×ijת",
+      "ĠBü ro",
+      "ä½ľ ãģ£ãģŁ",
+      "ĠKi ÅŁi",
+      "ç¾İåij³ ãģĹ",
+      "à¹Ģลย à¸Ħà¹Īะ",
+      "à¸ŀà¸ļ à¸ģัà¸ļ",
+      "à¸Ī à¹īา",
+      "Ġç er",
+      "Ġçer ç",
+      "Ġçerç eve",
+      "ãĤĴä½ľ ãģ£ãģ¦",
+      "ĠпеÑĢв ÑĥÑİ",
+      "×ŀצ ר×Ļ×Ŀ",
+      "×IJ׾ ×ķ×Ķ",
+      "×IJ׾×ķ×Ķ ×Ļ×Ŀ",
+      "Ġagr é",
+      "Ġagré able",
+      "Ġay ır",
+      "Ä°L Ä°",
+      "ãĤ ¥",
+      "Ġíĺ Ħ",
+      "ĠíĺĦ ìĭ¤",
+      "ثاÙĦ Ø«",
+      "ת ×ĸ",
+      "ת×ĸ ×ķ׳×Ķ",
+      "ãģ¨ãģĦ ãģ£ãģ¦",
+      "ãģ¨ãģĦãģ£ãģ¦ ãĤĤ",
+      "Ġا بÙĪ",
+      "ĠÑģоб ак",
+      "é£Łãģ¹ ãģŁ",
+      "Ġдан ном",
+      "à¹Ģล ิ",
+      "à¹Ģลิ ศ",
+      "Ġí ļ",
+      "Ġíļ ¨",
+      "Ġíļ¨ ê³¼",
+      "ãĤĤãĤī ãģĪãĤĭ",
+      "׳ צ׾",
+      "ÑĦ ик",
+      "ÑĦик Ñģ",
+      "Ġjeste ÅĽmy",
+      "ת×Ĺ×ķש ×Ķ",
+      "à¹Ħมà¹Ī à¸Ħวร",
+      "ĠØŃ Ø³ÙĬÙĨ",
+      "à¸ģาร ลà¸ĩà¸Ĺุà¸Ļ",
+      "ë´ ¤",
+      "ĠÐĺ менно",
+      "à¸ļ à¸Ńรà¹Į",
+      "à¸ļà¸Ńรà¹Į à¸Ķ",
+      "ĠC ảnh",
+      "ìĦľ ë¹ĦìĬ¤",
+      "Ġпол ов",
+      "Ġполов ин",
+      "Ġзам еÑĩа",
+      "ãģĦãĤį ãĤĵãģª",
+      "Ġ×ij ×Ļק",
+      "Ġ×ij×Ļק ש",
+      "л ÑĥÑĪ",
+      "ãĤĴ è¿İ",
+      "ãĤĴè¿İ ãģĪ",
+      "جرÙĬ ÙħØ©",
+      "Ġt ây",
+      "ĠاÙĦÙĨ ÙĪ",
+      "ĠاÙĦÙĨÙĪ ÙĪÙĬ",
+      "ÃĤ N",
+      "ì¿ ł",
+      "หà¸Ļ าว",
+      "Ġ×ij׊ש×ij×ķף",
+      "ز ار",
+      "à¸Ķ าร",
+      "à¸Ķาร า",
+      "ĠÅĽ l",
+      "ĠÅĽl ub",
+      "มีà¸Ħวาม สุà¸Ĥ",
+      "Ġn hu",
+      "Ġnhu áºŃn",
+      "ÙħØŃ Ø·Ø©",
+      "à¹Ģสืà¹īà¸Ń à¸ľà¹īา",
+      "ĠТ олÑĮко",
+      "ĠÙĥ س",
+      "ĠÙĥس ارة",
+      "ÙħØ´ رÙĪع",
+      "niÄĻ cia",
+      "×¢ ׼ש×Ļ×ķ",
+      "ت ÙĦÙģ",
+      "تÙĦÙģ زÙĬ",
+      "تÙĦÙģزÙĬ ÙĪÙĨ",
+      "Ġl Æ°á»Ľi",
+      "ĠÐľÐ¾Ñģк вÑĭ",
+      "Ġré serve",
+      "Ġan laÅŁ",
+      "ĠanlaÅŁ ıl",
+      "Ġed eceÄŁi",
+      "รà¸Ńà¸ĩ à¹Ģà¸Ĺà¹īา",
+      "Ġب Ø·",
+      "Ġبط رÙĬ",
+      "ĠبطرÙĬ ÙĤØ©",
+      "ãģ¦ãģĹãģ¾ ãģ£ãģ¦",
+      "ãĤĤãĤī ãģ£ãģ¦",
+      "بر ج",
+      "æ± ļ",
+      "æ±ļ ãĤĮ",
+      "Ġch oc",
+      "Ġchoc ia",
+      "Ġchocia ż",
+      "Ġzob ac",
+      "Ġzobac zyÄĩ",
+      "пÑĢ Ñı",
+      "пÑĢÑı жен",
+      "ĠÑĨ иÑĦ",
+      "ĠÑĨиÑĦ ÑĢ",
+      "Ġм ам",
+      "Ġвз ÑıÑĤÑĮ",
+      "Ġch ạm",
+      "ج سÙħ",
+      "ØŃÙħ اس",
+      "à¹Ģล à¹Īม",
+      "à¸ŀิ ษ",
+      "×Ķפ ׼×ķ",
+      "à¸Ĭà¹Īà¸Ńà¸ĩ à¸Ĺาà¸ĩ",
+      "Ġв ек",
+      "Ġвек а",
+      "Æ¡ Ìģ",
+      "Æ¡Ìģ i",
+      "ĠTi á»ģn",
+      "Ġtr ầm",
+      "мÑĭ ÑĪ",
+      "мÑĭÑĪ л",
+      "ĠÑĤ Ñĥ",
+      "ĠÑĤÑĥ ÑĢиÑģÑĤ",
+      "Ġch c",
+      "Ġchc Äħ",
+      "Ġав г",
+      "Ġавг ÑĥÑģÑĤ",
+      "ĠавгÑĥÑģÑĤ а",
+      "ס ×IJ×ķת",
+      "Ġר ×Ĵ׾",
+      "à¸ľà¸¥ à¸ģระà¸Ĺ",
+      "à¸ľà¸¥à¸ģระà¸Ĺ à¸ļ",
+      "å¤īãĤı ãĤĭ",
+      "Ġ×Ķ×IJ×Ĺר ×ķ׳×Ļ×Ŀ",
+      "سÙģ ÙĬر",
+      "ĠÑĩа Ñīе",
+      "ãģĦ ãĤī",
+      "ãģĦãĤī ãģ£",
+      "ãģĦãĤīãģ£ ãģĹãĤĥ",
+      "×ķ×ŀ ׳×Ļ×Ŀ",
+      "Ġart tır",
+      "ĠCh á»ĭ",
+      "Ġì¡° ì§ģ",
+      "ĠÑĥÑģп еÑħ",
+      "Ġ×¢ ×ķס",
+      "Ġ×¢×ķס ק",
+      "ĠìĥĿ ëªħ",
+      "ÑĨ иÑĤ",
+      "Ġreg ión",
+      "Ðŀ ÐĿ",
+      "ĠdoÄŁ um",
+      "ĠyaÅŁ ad",
+      "ĠyaÅŁad ıģı",
+      "à¸Ĺà¸Ķ ลà¸Ńà¸ĩ",
+      "Ġgöz ü",
+      "ש ×Ļר×Ķ",
+      "дÑĥм ал",
+      "Ġda ģı",
+      "Ġdaģı t",
+      "à¸Ĺีม à¸ĩาà¸Ļ",
+      "Ġti á»ģm",
+      "ĠاÙĦÙĥ بر",
+      "ĠاÙĦÙĥبر Ùī",
+      "ì¹ Ń",
+      "ĠGü nc",
+      "ĠGünc elle",
+      "ĠGüncelle me",
+      "ê¹ Ĭ",
+      "ĠобоÑĢÑĥд ование",
+      "ĠÑĢеÑĪ а",
+      "á» ¤",
+      "Ġп иÑĤ",
+      "ĠпиÑĤ аниÑı",
+      "à¹Ģรีย à¸ļ",
+      "×Ľ×ª ×Ļ×ij×Ķ",
+      "Ġп он",
+      "Ġпон ÑĢав",
+      "ĠпонÑĢав и",
+      "Ġ×Ķ ×ķ׾×ĵ",
+      "Ġ×Ķ×ķ׾×ĵ ת",
+      "Ġê² ģ",
+      "Ġê²ģ ëĭĪëĭ¤",
+      "ĠпеÑĢв ой",
+      "ãĥ©ãĤ¤ ãĥķ",
+      "ĠÅŁi ir",
+      "kr ÄĻ",
+      "krÄĻ c",
+      "Ġthi á»ĥu",
+      "à¹Ģลย à¸Ĺี",
+      "à¹Ģลยà¸Ĺี à¹Ģà¸Ķียว",
+      "×ĺ×¢ ׳×ķת",
+      "ائ ÙĩÙħ",
+      "Ġ×IJ ס×ķר",
+      "ĠплаÑĤ еж",
+      "تر دد",
+      "Ġmożli we",
+      "Ġkh Ỽ",
+      "ĠkhỼ p",
+      "تÙģاع ÙĦ",
+      "ĠÑĪ колÑĮ",
+      "ĠÑĪколÑĮ н",
+      "ĠÙĤ صة",
+      "Ġmét ier",
+      "nÄĻ ÅĤa",
+      "หล à¹Īà¸Ń",
+      "Ġ ủng",
+      "Ġprz egl",
+      "Ġprzegl Äħd",
+      "ĠاÙĦÙħ تعÙĦ",
+      "ĠاÙĦÙħتعÙĦ ÙĤØ©",
+      "ĠÑģÑĭ н",
+      "Ġв олн",
+      "ãĥĩ ãĥ¼ãĥĪ",
+      "ĠÐŃ ÑĤи",
+      "Ġк ÑĢоме",
+      "à¸Ħ ารà¹Į",
+      "׳ק ×ķ×ĵ×Ķ",
+      "Ġ׾ש×ŀ ×ķ×¢",
+      "Ġ×ĸ ×ķ׼ר",
+      "ï¼ §",
+      "ÙĬ Ùİا",
+      "Ġgi á»ıi",
+      "åĥį ãģı",
+      "ĠÑģ ни",
+      "ĠÑģни жен",
+      "à¹ģà¸Ķ à¸Ķ",
+      "รุ à¸Ļ",
+      "รุà¸Ļ à¹ģรà¸ĩ",
+      "Ġhi á»ĩp",
+      "ograf ÃŃa",
+      "à¹Ģà¸Ī à¸Ńรà¹Į",
+      "Ġдв иг",
+      "Ġдвиг аÑĤ",
+      "ĠдвигаÑĤ ел",
+      "Ġü y",
+      "Ġüy eler",
+      "Ġüyeler i",
+      "Ġб Ñĥк",
+      "ĠбÑĥк в",
+      "ãĤĤ å¤ļãģı",
+      "Ġthi á»ĩt",
+      "ĠPa ÃŃs",
+      "ĠØ· بÙĬعÙĬ",
+      "à¹ģà¸Ī à¸ģ",
+      "ĠاÙĦص ØŃÙĬØŃ",
+      "Ġapp ré",
+      "Ġappré ci",
+      "Ġdecis ión",
+      "Ġë°ĺ ëĵľ",
+      "Ġë°ĺëĵľ ìĭľ",
+      "ĠÑĤеб е",
+      "ãĤ· ãĥ¼ãĤº",
+      "ãĤ·ãĥ¼ãĤº ãĥ³",
+      "Ġд алÑĮн",
+      "ĠìĬ ¤",
+      "ĠìĬ¤ ìĬ¤",
+      "ĠìĬ¤ìĬ¤ ë¡ľ",
+      "ĠTh á»ĥ",
+      "Ġkar ÅŁ",
+      "ĠkarÅŁ ıs",
+      "ĠkarÅŁÄ±s ında",
+      "ĠK ön",
+      "ĠKön ig",
+      "ив ание",
+      "×ij ×ķצע",
+      "г лаÑģ",
+      "Ġtw ó",
+      "Ġtwó rc",
+      "à¸Ľà¸ģ à¸Ħร",
+      "à¸Ľà¸ģà¸Ħร à¸Ńà¸ĩ",
+      "ĠG ÅĤ",
+      "ĠGÅĤ ówn",
+      "ĠUnter stüt",
+      "ĠUnterstüt zung",
+      "Ġд ÑĥÑħ",
+      "ĠдÑĥÑħ ов",
+      "Ø£ ÙħاÙĨ",
+      "×Ĺש ש",
+      "ت ظ",
+      "تظ اÙĩر",
+      "ĠлÑİб ом",
+      "à¸ķ าร",
+      "à¸ķาร าà¸ĩ",
+      "Ġkr ól",
+      "Ø£ ØŃدث",
+      "ì¡Į ëĭ¤",
+      "Ðļ ÑĥÑĢÑģ",
+      "ãĥĥ ãĥĦ",
+      "×ŀק ×ķ×ij׾",
+      "ĠÑģимв ол",
+      "Ġdés orm",
+      "Ġdésorm ais",
+      "w üns",
+      "wüns che",
+      "Ñĥ ни",
+      "Ñĥни ÑĨип",
+      "ÑĥниÑĨип алÑĮн",
+      "หลัà¸ģ สูà¸ķร",
+      "ÙĨت شر",
+      "Ġа л",
+      "Ġал к",
+      "Ġалк ог",
+      "Ġалког ол",
+      "ĠÑĥ ÑĩиÑĤÑĭва",
+      "à¸ģำ à¸ģัà¸ļ",
+      "Ġ׾ פע×ķ׾",
+      "ĠìĹ° ê²°",
+      "s Äħd",
+      "ĠاÙĦØ£ ÙĬ",
+      "ĠاÙĦØ£ÙĬ اÙħ",
+      "غÙĬ اب",
+      "Ġна ÑĢ",
+      "ĠнаÑĢ ко",
+      "×ŀ×ķ×ĵ ×¢",
+      "ĠÑģеÑĢ ии",
+      "пиÑģ Ñĭва",
+      "สิ ว",
+      "ç¶ļ ãģĦãģ¦",
+      "çĶ³ãģĹ è¾¼ãģ¿",
+      "Ġ׾ ×Ĵר",
+      "Ġ׾×Ĵר ×ķ×Ŀ",
+      "Ġд ем",
+      "Ġдем о",
+      "Ġë³´ ëĤ´",
+      "تÙĩ دÙĬد",
+      "ĠÙħØ´ ÙĬرا",
+      "Ġdu y",
+      "Ġduy á»ĩt",
+      "ĠwiÄĻks ze",
+      "Ùħع اÙĬ",
+      "ÙħعاÙĬ ÙĬر",
+      "ĠG da",
+      "ĠGda ÅĦsk",
+      "Ġr ah",
+      "Ġrah ats",
+      "Ġrahats ız",
+      "ר ×ķצ×Ķ",
+      "l ös",
+      "lös ung",
+      "ĠТак им",
+      "ÑĪ ед",
+      "ÑĪед ÑĪ",
+      "ع زÙĦ",
+      "Ġרש ×Ļ×ŀת",
+      "Ġ׾×Ķ ×Ļ׼",
+      "Ġ׾×Ķ×Ļ׼ ×ł×¡",
+      "Ġп ÑĥÑĤ",
+      "ĠпÑĥÑĤ еÑĪ",
+      "ĠпÑĥÑĤеÑĪ еÑģÑĤв",
+      "Ġnot ÃŃcia",
+      "Ġal Ä±ÅŁ",
+      "ĠalÄ±ÅŁ ver",
+      "ĠalÄ±ÅŁver iÅŁ",
+      "ĠwÅĤ os",
+      "ĠwÅĤos ów",
+      "Ġب غ",
+      "Ġبغ داد",
+      "Ġver öffent",
+      "Ġveröffent licht",
+      "ĠKh á",
+      "Ġt án",
+      "ëIJĺ 기",
+      "Ġë°© 문",
+      "Ùģ ÙĬÙĦ",
+      "à¹Ģà¸ģิà¸Ķ à¸Īาà¸ģ",
+      "åı¯ æĦĽ",
+      "åı¯æĦĽ ãģĦ",
+      "à¸ĸ ุà¸ĩ",
+      "Ġz ewnÄĻtrzn",
+      "à¸łà¸²à¸©à¸² à¸Ńัà¸ĩà¸ģฤษ",
+      "Ġmá xima",
+      "Ġul us",
+      "Ġulus lararası",
+      "Ġ׳×Ķ ׳",
+      "à¸Ĥà¹Īาว สาร",
+      "ĠìĿĺ ìĤ¬",
+      "à¹Ģหล ืà¸Ńà¸ĩ",
+      "Ġد ÙĤ",
+      "ĠدÙĤ ائÙĤ",
+      "สืà¹Īà¸Ń สาร",
+      "ë¨ ¼",
+      "ĠÑģоÑģÑĤоÑı нии",
+      "สมา à¸Ħม",
+      "á» Ĥ",
+      "ĠÐľÐ¾Ñģ ков",
+      "ĠÐľÐ¾Ñģков Ñģк",
+      "×ŀס ×ķ×Ĵ׾",
+      "ãģĭ ãģĭãĤĬ",
+      "ĠTr uyá»ģn",
+      "à¹ģà¸Ĥà¹ĩà¸ĩ à¹ģรà¸ĩ",
+      "×ŀ×Ĺ ×ĸ×Ļק",
+      "à¹Ĥà¸ģ à¹ī",
+      "ÙĬس ر",
+      "ìĶ ©",
+      "×IJ ×ķק",
+      "×IJ×ķק ×ĺ",
+      "×IJ×ķק×ĺ ×ķ×ijר",
+      "Ġprox imité",
+      "ÙħÙĨ Ùĩج",
+      "ĠاÙĦج ز",
+      "ĠاÙĦجز ائ",
+      "ĠاÙĦجزائ رÙĬ",
+      "ĠÄIJi á»ĥm",
+      "Ġден еж",
+      "Ġденеж н",
+      "ÙģØŃ Øµ",
+      "Ùģ ئ",
+      "ĠÐij Ñĥд",
+      "×Ĵ×Ļ×ĵ ×ķ׾",
+      "ĠÐĴ едÑĮ",
+      "عÙĦ اÙħØ©",
+      "Ġ×IJ×Ĺר ×ķ׳×ķת",
+      "ãģĦãģŁãģł ãģĦãģ¦",
+      "سÙĦ ØŃ",
+      "ØŃ ÙĦÙħ",
+      "ز ÙĪار",
+      "Ùĥ سر",
+      "×ĺ קס",
+      "Ġб ан",
+      "Ġбан ков",
+      "ĠпÑĢ ож",
+      "ĠпÑĢож ива",
+      "li wo",
+      "liwo ÅĽci",
+      "ĠTi ếp",
+      "ĠاÙĦÙħÙĨ اسب",
+      "ĠاÙĦØ® ÙĬار",
+      "ãģĬ ãģĭ",
+      "ãģĬãģĭ ãģĴ",
+      "à¸Ķà¸Ńà¸ģ à¹Ħมà¹ī",
+      "ä mp",
+      "ämp fe",
+      "à¸ķัà¹īà¸ĩ à¹ĥà¸Ī",
+      "Ġза ÑīиÑĤ",
+      "ĠзаÑīиÑĤ Ñĭ",
+      "ĠTh Æ°á»Ŀng",
+      "Ġص Ùģ",
+      "ĠصÙģ ØŃØ©",
+      "×Ĺ×ķר ×£",
+      "ãĥIJ ãĥĥãĤ°",
+      "Ġ×ĵ ×Ļ×Ĵ",
+      "Ġ×ĵ×Ļ×Ĵ ×Ļ×ĺ",
+      "Ġ×ĵ×Ļ×Ĵ×Ļ×ĺ ׾×Ļ",
+      "Ġ×Ķ×Ĺ ×ķ׾×Ļ×Ŀ",
+      "в еÑī",
+      "веÑī а",
+      "Ġк ÑĥлÑĮÑĤ",
+      "ĠкÑĥлÑĮÑĤ Ñĥ",
+      "ĠкÑĥлÑĮÑĤÑĥ ÑĢÑĭ",
+      "ĠاÙĦاÙĨ ترÙĨت",
+      "Ġhö ch",
+      "Ġhöch st",
+      "Ġíĺ ķ",
+      "Ġíĺķ íĥľ",
+      "Ġв ой",
+      "Ġвой нÑĭ",
+      "ÐĽ Ðŀ",
+      "ìĭł ìļ©",
+      "Ġ×ŀ×ij ×ķס",
+      "Ġ×ŀ×ij×ķס ס",
+      "×ŀ׳ ×Ļ×¢",
+      "Ġfiyat ı",
+      "ĠÑģл Ñĥж",
+      "ĠÑģлÑĥж бÑĭ",
+      "à¸Ĺั ศ",
+      "à¸Ĺัศ à¸Ļ",
+      "ãģĵãģ¨ãģĮ å¤ļãģĦ",
+      "Ġ×Ķ×ŀש ת",
+      "Ġ×Ķ×ŀשת ×ŀש",
+      "å¯Ħ ãģĽ",
+      "×ŀש׾ ×ķ×Ĺ",
+      "æĻĤ çĤ¹",
+      "æĻĤçĤ¹ ãģ§",
+      "à¸ŀร ี",
+      "à¸ŀรี à¹Ģมีย",
+      "à¸ŀรีà¹Ģมีย รà¹Į",
+      "à¸ŀรีà¹Ģมียรà¹Į ลีà¸ģ",
+      "Ġdiffic olt",
+      "Ġdifficolt Ãł",
+      "ãĥ¬ ãĤ¹ãĥĪ",
+      "ãĥ¬ãĤ¹ãĥĪ ãĥ©ãĥ³",
+      "สม à¹Ģà¸Ķà¹ĩ",
+      "สมà¹Ģà¸Ķà¹ĩ à¸Ī",
+      "Ġж ид",
+      "Ġжид к",
+      "Ġzu peÅĤ",
+      "ĠzupeÅĤ nie",
+      "ĠÙħ جر",
+      "ĠÙħجر د",
+      "ãģĮ å§ĭ",
+      "ãģĮå§ĭ ãģ¾",
+      "ãĤŃãĥ£ ãĥ©",
+      "Ġ×IJ ×ķ×ķ×Ļר",
+      "ãģĬ äºĴ",
+      "ãģĬäºĴ ãģĦ",
+      "Ġpot rÃł",
+      "ĠPa ÅĦst",
+      "ĠPaÅĦst wo",
+      "Ġب ÙĬاÙĨ",
+      "ĠبÙĬاÙĨ ات",
+      "Ġин огда",
+      "ĠÑĢ а",
+      "ĠÑĢа ÑģÑĤв",
+      "ĠÑĢаÑģÑĤв оÑĢ",
+      "Ġ×ĸ ×ŀ׳",
+      "ยิ à¹īม",
+      "Ä Ĩ",
+      "ãģ¾ ãģķ",
+      "ãģ¾ãģķ ãģ«",
+      "ãĥķãĤ¡ ãĤ¤ãĥ«",
+      "Ġgörd Ã¼ÄŁÃ¼",
+      "สà¸ĩ à¸Ħร",
+      "สà¸ĩà¸Ħร าม",
+      "ĠArk adaÅŁ",
+      "ĠrozwiÄħz ania",
+      "×ŀ ×ķ×ĺ",
+      "pi ÄĻ",
+      "piÄĻ t",
+      "ص غر",
+      "ส ย",
+      "สย าม",
+      "ãĤĨ ãģ£ãģıãĤĬ",
+      "Ġtr ần",
+      "Ġeconom ÃŃa",
+      "Ġgeh ören",
+      "ãĤ·ãĥ§ ãĥ¼",
+      "ĠsÅĤ ucha",
+      "à¸ŀà¸Ń à¹ĥà¸Ī",
+      "ĠоÑĤмеÑĤ ил",
+      "ÙĨت ÙĤÙĦ",
+      "Ġprop ósito",
+      "ĠваÑĪ его",
+      "Ġnh ắn",
+      "à¹ģà¸ĸ ว",
+      "Ġком иÑģ",
+      "ĠкомиÑģ Ñģи",
+      "waż nie",
+      "Ġy avaÅŁ",
+      "×ŀ ×Ļק",
+      "×ŀ×Ļק ×ķ×Ŀ",
+      "ש×IJ׾ ת",
+      "Ġyıll arda",
+      "ĠÐ ®",
+      "ĠЮ ÑĢ",
+      "×ł×¡ ×Ļ×ij×ķת",
+      "ת צ",
+      "תצ ×ķ×Ĵ",
+      "Ġод нÑĥ",
+      "Ġ à¸Ńยà¹Īาà¸ĩà¹Ħร",
+      "Ġà¸Ńยà¹Īาà¸ĩà¹Ħร à¸ģà¹ĩà¸ķาม",
+      "ëģ ¼",
+      "à¹Ħล à¹Ī",
+      "تس ÙĦÙĬÙħ",
+      "بÙĦ اغ",
+      "Ġì ī",
+      "Ġìī ½",
+      "Ġìī½ ê²Į",
+      "ãĥļ ãĥ³",
+      "зв ÑĥÑĩ",
+      "ĠW äh",
+      "ĠWäh rend",
+      "Ġ×Ļ ×Ļת",
+      "Ġ×Ļ×Ļת ׼ף",
+      "Ġkh uyên",
+      "Ġv ẽ",
+      "Ġа меÑĢ",
+      "ĠамеÑĢ ик",
+      "ĠамеÑĢик ан",
+      "ĠамеÑĢикан Ñģк",
+      "ع جب",
+      "ãĥĽãĥ¼ãĥł ãĥļãĥ¼ãĤ¸",
+      "Ġник ÑĤо",
+      "ĠÙĤ Ùİ",
+      "ĠÙĤÙİ Ø§ÙĦ",
+      "ĠÙĤÙİاÙĦ Ùİ",
+      "ÐIJ ÐĹ",
+      "Ùħ جÙħÙĪع",
+      "ÙħجÙħÙĪع ات",
+      "Ġnecess itÃł",
+      "Ġpob li",
+      "Ġpobli żu",
+      "Ġph ấn",
+      "ĠСо обÑī",
+      "ÙħÙĤ اط",
+      "ÙħÙĤاط ع",
+      "Ġ×Ķצ ×ķר×ļ",
+      "la ÅŁtırma",
+      "ว ิà¸Ķ",
+      "วิà¸Ķ ี",
+      "วิà¸Ķี à¹Ĥà¸Ń",
+      "Ġ그리 ìĬ¤",
+      "Ġ그리ìĬ¤ ëıĦ",
+      "ãĤ¿ãĤ¤ ãĥŁ",
+      "ãĤ¿ãĤ¤ãĥŁ ãĥ³ãĤ°",
+      "ק×ĺ ×Ĵ×ķר",
+      "ק×ĺ×Ĵ×ķר ×Ļ×Ķ",
+      "Ġ×Ĺ ×ķפ",
+      "Ġ×Ĺ×ķפ ש×Ļ",
+      "أ جر",
+      "Ġим ени",
+      "ĠÑĢан ее",
+      "à¹Ģà¸ŀืà¹Īà¸Ńà¸Ļ à¹Ĩ",
+      "ĠJes ús",
+      "Ñģо един",
+      "Ñģоедин ен",
+      "Ġר ×Ĺ×ķק",
+      "à¹Ĥà¸ļ รา",
+      "à¹Ĥà¸ļรา à¸ĵ",
+      "ĠH Æ¡n",
+      "Ġth áºŃp",
+      "تع ÙĬÙĬÙĨ",
+      "Ġtart Ä±ÅŁ",
+      "ĠtartÄ±ÅŁ ma",
+      "ĠGes pr",
+      "ĠGespr äch",
+      "תר ×ķפ",
+      "תר×ķפ ×ķת",
+      "Ġcat égorie",
+      "Ġоказ Ñĭва",
+      "ĠналиÑĩ ие",
+      "Ġprésent é",
+      "Ġk ull",
+      "Ġkull and",
+      "Ġkulland ı",
+      "Ġü nl",
+      "Ġünl ü",
+      "ĠÙģ Ùĥرة",
+      "из аÑĤоÑĢ",
+      "×IJ ×ķ׳",
+      "×IJ×ķ׳ ×Ļ×ij",
+      "×IJ×ķ׳×Ļ×ij רס",
+      "×IJ×ķ׳×Ļ×ijרס ×Ļ×ĺת",
+      "ĠÑĢаÑģÑģ маÑĤ",
+      "ĠÑĢаÑģÑģмаÑĤ ÑĢ",
+      "ĠÑĢаÑģÑģмаÑĤÑĢ ива",
+      "تÙĥÙĦ Ùħ",
+      "Ùĥت رÙĪ",
+      "ÙĥترÙĪ ÙĨÙĬ",
+      "ĠÑģо ÑĩеÑĤ",
+      "ĠÑģоÑĩеÑĤ а",
+      "ãĤĴè¦ĭ ãģĽ",
+      "Ġng ừa",
+      "ĠÐł еÑģп",
+      "ĠÐłÐµÑģп Ñĥб",
+      "ĠÐłÐµÑģпÑĥб лик",
+      "ãĤ¦ ãĤ©",
+      "ãĤ¦ãĤ© ãĥ¼",
+      "ĠÐľ еждÑĥ",
+      "ĠìŀĪ ê²Į",
+      "Ġm â",
+      "ĠìļĶ ì²Ń",
+      "ض ار",
+      "ลุ à¹īà¸Ļ",
+      "ëĮĢ íķĻêµIJ",
+      "×ĸ ×Ļ׼",
+      "×ĸ×Ļ׼ ר×ķף",
+      "ãĤ¹ ãĥļ",
+      "ãĤ¹ãĥļ ãĥ¼ãĤ¹",
+      "ĠкÑĢаÑģ оÑĤ",
+      "ï¼ ¨",
+      "ê¼ Ń",
+      "ãĤĴ éĽĨ",
+      "ãĤĴéĽĨ ãĤģ",
+      "ë° Ŀ",
+      "Ġ×Ķ׳ ×IJ",
+      "Ġ×Ķ׳×IJ ש×Ŀ",
+      "Ġê°Ģ ìļ´",
+      "Ġê°Ģìļ´ ëį°",
+      "تÙĥÙĦ ÙģØ©",
+      "ĠØŃ ÙĤÙĬÙĤÙĬ",
+      "Ġh alk",
+      "Ġhalk ın",
+      "ÑİÑī ÑĥÑİ",
+      "ĠÑģп ин",
+      "סר×ĺ ף",
+      "ĠпеÑĢв ого",
+      "Ġпол ож",
+      "Ġполож иÑĤелÑĮн",
+      "Ġд л",
+      "Ġдл иÑĤелÑĮн",
+      "ĠV Ä©nh",
+      "ê´ ´",
+      "ĠÑģÑĭ ÑĢ",
+      "ĠíĨµ íķĺìŬ",
+      "ë³ij ìĽIJ",
+      "à¹Ĥรà¸ĩ à¸ĩาà¸Ļ",
+      "รัà¸ļ à¸ľà¸´à¸Ķ",
+      "รัà¸ļà¸ľà¸´à¸Ķ à¸Ĭà¸Ńà¸ļ",
+      "تج ÙĨب",
+      "s ÅĤ",
+      "sÅĤ uch",
+      "ãĤ¢ãĥ« ãĥIJ",
+      "ãĤ¢ãĥ«ãĥIJ ãĥł",
+      "ëī´ ìĬ¤",
+      "Ġpat ië",
+      "Ġpatië nt",
+      "Ġìĺ ¤í",
+      "Ġìĺ¤í ŀ",
+      "Ġìĺ¤íŀ Ī",
+      "Ġìĺ¤íŀĪ 볤",
+      "ĠDer ne",
+      "ĠDerne ÄŁi",
+      "wró ci",
+      "wróci Äĩ",
+      "Ġоб Ñī",
+      "ĠобÑī еÑģÑĤв",
+      "ĠобÑīеÑģÑĤв енно",
+      "ĠêµIJ ìĪĺ",
+      "tıģ ımız",
+      "Ġ×Ķ×ŀש ×Ļ×ij",
+      "k örper",
+      "Ġпозв ол",
+      "Ġпозвол иÑĤ",
+      "ĠChi ến",
+      "أخ ÙĪ",
+      "ĠAy dın",
+      "à¸Ķà¹īาà¸Ļ ล",
+      "à¸Ķà¹īาà¸Ļล à¹Īาà¸ĩ",
+      "Ġdr u",
+      "Ġdru ż",
+      "Ġdruż yn",
+      "Ġë°ľ íijľ",
+      "ĠTh ảo",
+      "جÙĩ اد",
+      "à¸ģระà¸Ĺ ูà¹ī",
+      "Ġк ÑĢов",
+      "ĠкÑĢов и",
+      "Ġiçer ik",
+      "Ġnad zie",
+      "Ġnadzie jÄĻ",
+      "ĠС моÑĤÑĢ",
+      "Ġph ức",
+      "ج تÙħاع",
+      "جتÙħاع ÙĬØ©",
+      "ком пон",
+      "компон енÑĤ",
+      "Ġб ил",
+      "Ġбил еÑĤ",
+      "ãĥIJ ãĥ³ãĥī",
+      "ĠPol ÃŃcia",
+      "اÙĦ تÙĩ",
+      "اÙĦتÙĩ اب",
+      "ØŃر Ùģ",
+      "ت خط",
+      "تخط ÙĬØ·",
+      "ãĤ³ ãĥ¼ãĥ",
+      "ãĤ³ãĥ¼ãĥ Ĵ",
+      "ãĤ³ãĥ¼ãĥĴ ãĥ¼",
+      "･･ ･",
+      "à¸ĭ à¸Ńย",
+      "Ġcréd it",
+      "è²· ãģ£ãģŁ",
+      "ĠпоÑĢ Ñıд",
+      "ĠпоÑĢÑıд ке",
+      "Ġph ó",
+      "Ġw ida",
+      "Ġwida Äĩ",
+      "جر ائÙħ",
+      "à¸ľ ี",
+      "ĠbÄĻd ÄĻ",
+      "Ġ×ŀ פת×Ĺ",
+      "ãĥij ãĥ¼ãĥ",
+      "ãĥijãĥ¼ãĥ Ĩ",
+      "ãĥijãĥ¼ãĥĨ ãĤ£",
+      "ãĥijãĥ¼ãĥĨãĤ£ ãĥ¼",
+      "ĠKa ż",
+      "ĠKaż dy",
+      "ĠнеобÑħодим оÑģÑĤи",
+      "à¸Ł à¸Ńรà¹Į",
+      "à¸Łà¸Ńรà¹Į ม",
+      "Ġмал ÑĭÑĪ",
+      "Ġпл оÑĤ",
+      "ĠÑĥ ÑģÑĤÑĢой",
+      "ĠÑĥÑģÑĤÑĢой ÑģÑĤва",
+      "à¸ĸ à¸Ńà¸Ļ",
+      "ĠoluÅŁtur ul",
+      "ĠÅĽwi ad",
+      "ĠÅĽwiad om",
+      "Ùħع Ùĩد",
+      "ĠпÑĢоиз веден",
+      "Æ ł",
+      "ר ×Ļש",
+      "Ùħست Ø«",
+      "Ùħستث Ùħر",
+      "׳×Ļ ×Ļר",
+      "pa ñ",
+      "Ġ; -)",
+      "Ġë°ľ 견",
+      "Ġgör üyor",
+      "Ùħؤ ÙĦÙģ",
+      "ĠÄIJ á»ģ",
+      "ĠاÙĦÙĨ ÙĪاب",
+      "×Ĺק ×Ļר×Ķ",
+      "Ġm á»ıi",
+      "è¿° ãģ¹",
+      "ÐĿ ик",
+      "ìŀĸ ìķĦ",
+      "ìŀĸìķĦ ìļĶ",
+      "prowadzi ÅĤ",
+      "l óg",
+      "lóg ica",
+      "פס ×ĺ",
+      "פס×ĺ ×Ļ×ij׾",
+      "Ġ×ŀ ×ĵ×Ķ",
+      "Ġ×ŀ×ĵ×Ķ ×Ļ×Ŀ",
+      "ãģĵãģĵ ãģ¾ãģ§",
+      "×Ķ ת×Ĺ",
+      "×Ķת׊׾×Ķ",
+      "Ġפ ×ķס",
+      "Ġפ×ķס ×ĺ×Ļ×Ŀ",
+      "Ġн ев",
+      "Ġнев оз",
+      "Ġневоз можно",
+      "ĠdostÄĻp ny",
+      "Ġغ اÙĦ",
+      "ĠغاÙĦ ب",
+      "Ġbez pieczeÅĦst",
+      "ĠbezpieczeÅĦst wa",
+      "åĪĨ ãģĭãĤĭ",
+      "ĠF ührung",
+      "à¸ģ ีà¹ī",
+      "gem Ã¤ÃŁ",
+      "à¸Ĭà¹Īวà¸ĩ à¹Ģวลา",
+      "Ġìļ°ë¦¬ ëĤĺ",
+      "Ġìļ°ë¦¬ëĤĺ ëĿ¼",
+      "ãģ¥ ãģıãĤĬ",
+      "ĠاÙĦÙħ سÙĦ",
+      "ĠاÙĦÙħسÙĦ ØŃØ©",
+      "Ġlibert é",
+      "клÑİÑĩ ение",
+      "Ġzam ów",
+      "Ġzamów ienia",
+      "รà¸ĸ à¹Ħà¸Ł",
+      "Ø£ ÙģÙĦ",
+      "Ø£ÙģÙĦ اÙħ",
+      "Ùħ راج",
+      "Ùħراج عة",
+      "Ġë¹Ħ êµIJ",
+      "ĠاÙĦت اب",
+      "ĠاÙĦتاب عة",
+      "Ġë§Į ëĤĺ",
+      "Ġб Ñĥм",
+      "ĠбÑĥм аг",
+      "Ġgé nero",
+      "Ġìŀĺ 못",
+      "×ŀ פ×ķר×ĺ",
+      "è²·ãģĦ çī©",
+      "ĠÙĦدÙĬ Ùĥ",
+      "Ġ×ľ×¢ ×Ļת",
+      "Ġ×ľ×¢×Ļת ×Ļ×Ŀ",
+      "ĠsÅĤ ab",
+      "ĠпÑĢедÑģÑĤав лÑı",
+      "ãĤ¿ ãĤ¤ãĥĪ",
+      "ãĤ¿ãĤ¤ãĥĪ ãĥ«",
+      "Ùħ ص",
+      "Ùħص Ø·Ùģ",
+      "ÙħصطÙģ Ùī",
+      "Ġdifficult é",
+      "ãĥĨãĤ£ ãĥĸ",
+      "Ġpew noÅĽci",
+      "ĠpewnoÅĽci Äħ",
+      "Ġ무 ìĬ¨",
+      "إ رس",
+      "إرس اÙĦ",
+      "Ġд алÑĮ",
+      "ĠдалÑĮ ÑĪе",
+      "Ġ׾ ×ł×¡",
+      "Ġ×ľ×ł×¡ ×ķת",
+      "หมูà¹Ī à¸ļà¹īาà¸Ļ",
+      "×ŀס×ŀ ׼×Ļ",
+      "أسÙĦ ÙĪب",
+      "Ġzw ÅĤ",
+      "ĠzwÅĤ as",
+      "ĠzwÅĤas zc",
+      "ĠzwÅĤaszc za",
+      "ĠпÑĢ еж",
+      "ĠпÑĢеж де",
+      "ĠоÑĢганиз аÑĨиÑı",
+      "Ġdön emin",
+      "Ġdönemin de",
+      "Ġ Ủ",
+      "ĠỦ y",
+      "ä¸ĭ ãģĴ",
+      "ĠпоÑģлед ние",
+      "Ġgü ne",
+      "Ġgüne ÅŁ",
+      "Ġ×IJ ×ĸר",
+      "Ġ×IJ×ĸר ×Ĺ×Ļ",
+      "ãģ§ãģĤ ãĤįãģĨ",
+      "ĠÙĨ ÙĤ",
+      "ĠÙĨÙĤ اط",
+      "æŃ£ ãģĹãģĦ",
+      "ĠÑĢ ег",
+      "ĠÑĢег иона",
+      "ĠFör der",
+      "ê²½ ìĺģ",
+      "dıkl ar",
+      "dıklar ını",
+      "trzym aÄĩ",
+      "أش Ùĥ",
+      "أشÙĥ اÙĦ",
+      "×Ķת ×IJ",
+      "×Ķת×IJ ×ŀ×Ķ",
+      "à¸Ĺำà¹ĥหà¹ī à¹Ģà¸ģิà¸Ķ",
+      "ĠGeb ä",
+      "ĠGebä ude",
+      "ĠСеÑĢ г",
+      "ĠСеÑĢг ей",
+      "Ġз доÑĢов",
+      "ĠздоÑĢов ÑĮÑı",
+      "Ġr ãi",
+      "ĠпÑĢед ÑĥÑģ",
+      "ĠпÑĢедÑĥÑģ моÑĤÑĢ",
+      "ĠпÑĢедÑĥÑģмоÑĤÑĢ ен",
+      "Ġ×Ķצ ×Ļ×ij",
+      "Ġ×Ķצ×Ļ×ij ×ķר×Ļ",
+      "Ġdés ir",
+      "Ġн оÑĩ",
+      "ĠноÑĩ ÑĮ",
+      "möglich keiten",
+      "Ġ×IJ×Ĺר ×ķ׳×Ļ×Ŀ",
+      "Ġsoir ée",
+      "ĠNh áºŃn",
+      "Ù ª",
+      "à¸Ľà¸£à¸°à¸§à¸±à¸ķิ ศาสà¸ķรà¹Į",
+      "êµIJ íĨµ",
+      "ĠØ£ Ø®ÙĬ",
+      "Ġdé cid",
+      "Ġdécid é",
+      "Ġwy ja",
+      "Ġwyja ÅĽni",
+      "Ġ สิ",
+      "Ġสิ à¸ĩ",
+      "Ġสิà¸ĩ หา",
+      "Ġสิà¸ĩหา à¸Ħม",
+      "à¹ģ à¸Ńรà¹Į",
+      "หà¸Ļà¹īา à¸Īà¸Ń",
+      "ס תר",
+      "Ġê ¶",
+      "Ġê¶ Į",
+      "Ġê¶Į 리",
+      "pl ätze",
+      "ب Ø·ÙĦ",
+      "ê±´ ìĦ¤",
+      "Ġ×IJ ×Ļ×ŀ×Ļ",
+      "Ġ×IJ×Ļ×ŀ×Ļ ×Ļ׾",
+      "ãģ ½",
+      "تر اث",
+      "×IJ׾ ×Ļ×ŀ×ķת",
+      "Ġdispon ÃŃveis",
+      "Ġz ale",
+      "Ġzale ży",
+      "à¸Ľà¸£à¸°à¸Ĭา สัมà¸ŀัà¸Ļà¸ĺà¹Į",
+      "ĠÅļw iat",
+      "Ġpor ówn",
+      "Ġporówn a",
+      "Ġ׾×ĺ ×ķ×ijת",
+      "×Ķ×ĸ ×ŀ׳×Ķ",
+      "Ġ×Ľ×ª ×ķצ×IJ×Ķ",
+      "Ġ×ij ק׾",
+      "Ġ×ijק׾ ×ķת",
+      "ĠоÑĤ кÑĢ",
+      "ĠоÑĤкÑĢ Ñĭва",
+      "ãĥij ãĥ¯ãĥ¼",
+      "ë¿IJ ë§Į",
+      "Ġв ÑģÑı",
+      "ĠвÑģÑı к",
+      "ãģ¨ãģª ãģ£ãģ¦ãģĦãĤĭ",
+      "Ġgi áºŃn",
+      "Ġок ÑĢÑĥ",
+      "ĠокÑĢÑĥ жа",
+      "ĠокÑĢÑĥжа ÑİÑī",
+      "ĠUnivers ität",
+      "ĠÑĢ ож",
+      "ĠÑĢож д",
+      "ĠÑĢожд ениÑı",
+      "Ø® ÙĬÙĦ",
+      "Ġкомпани й",
+      "ĠÑĢазлиÑĩ нÑĭе",
+      "ĠЦ ена",
+      "׳×Ļ ×ķ×ĸ",
+      "׳×Ļ×ķ×ĸ ׾",
+      "׳×Ļ×ķ×ĸ׾ ×ĺר",
+      "Ġê³µ ê°Ħ",
+      "Ġê°ľ ëħIJ",
+      "landır ma",
+      "ĠÑĥдал ен",
+      "à¸ŀัà¸ģ à¸ľ",
+      "à¸ŀัà¸ģà¸ľ à¹Īà¸Ńà¸Ļ",
+      "Ġprote cción",
+      "Ġb ÅĤ",
+      "ĠbÅĤ ÄĻd",
+      "Ã Ī",
+      "Ġíĸī ë³µ",
+      "ĠÅŁ ü",
+      "ĠÅŁÃ¼ phe",
+      "Ġí Ķ",
+      "ĠíĶ ¼",
+      "ĠíĶ¼ íķ´",
+      "Ġëĭ¤ 르",
+      "à¹Ħมà¹Ī à¹Ģà¸ģิà¸Ļ",
+      "ãģ¿ ãģª",
+      "ãģ¿ãģª ãģķãĤĵ",
+      "ĠпоÑĤ ÑĢеб",
+      "ĠпоÑĤÑĢеб иÑĤел",
+      "ĠاÙĦÙĥÙĦ اÙħ",
+      "ìķĦ ë²Ħ",
+      "ìķĦë²Ħ ì§Ģ",
+      "ãĤĴ使 ãģ£ãģŁ",
+      "Ġbụ i",
+      "ĠпоÑĤ еÑĢ",
+      "ĠпоÑĤеÑĢ Ñı",
+      "ĠØ¢ ÙĦاÙģ",
+      "ĠнаÑģÑĤоÑıÑī ее",
+      "ãģıãģªãĤĬ ãģ¾ãģĹãģŁ",
+      "clus ão",
+      "ãĤ³ ãĥĶãĥ¼",
+      "צ פ×Ļ",
+      "צפ×Ļ ×Ļ×Ķ",
+      "Ø® ÙĦا",
+      "Ø®ÙĦا ص",
+      "ล à¹īำ",
+      "ãĥ¯ ãĤ¤ãĥ³",
+      "Ġมี à¸Ļา",
+      "Ġมีà¸Ļา à¸Ħม",
+      "ش خص",
+      "شخص ÙĬات",
+      "Ġ×ĸ ק",
+      "Ġ×ĸק ×ķק",
+      "×Ļ ×Ļצ",
+      "×Ļ×Ļצ ×Ĵ",
+      "èĢĥãģĪ æĸ¹",
+      "Ġürün ü",
+      "ĠиÑģп ол",
+      "ĠиÑģпол ни",
+      "Ġcompañ ero",
+      "ק צ×Ķ",
+      "×ŀ×¢ ׳×Ļק",
+      "Ùħ ØŃÙħد",
+      "Ġc ámara",
+      "Ġп ед",
+      "Ġпед аг",
+      "Ġпедаг ог",
+      "м аÑĢ",
+      "маÑĢ к",
+      "×Ķת ׳×Ĵ×ĵ",
+      "ĠìĨĮ ê°ľ",
+      "Ġcom unitÃł",
+      "ê³ ¤",
+      "ĠNg Ãłi",
+      "สà¸ĩ à¸ļ",
+      "ĠmieszkaÅĦ ców",
+      "ĠÙĨ ÙĩائÙĬ",
+      "iv ité",
+      "Ġи де",
+      "Ġиде алÑĮн",
+      "ĠØ£ سبÙĪع",
+      "Ġ×Ļ ×¢×ľ",
+      "Ġ׾ ר×IJש",
+      "Ġ׾ר×IJש ×ķ׳×Ķ",
+      "ĠзапиÑģ и",
+      "ĠкоÑĢ пÑĥÑģ",
+      "วà¸ĩ ศ",
+      "วà¸ĩศ à¹Į",
+      "ĠÐĶ м",
+      "ĠÐĶм иÑĤ",
+      "ĠÐĶмиÑĤ ÑĢ",
+      "Ġkön nt",
+      "Ġböl ges",
+      "Ġbölges inde",
+      "׼ ×Ļ׼",
+      "׼×Ļ׼ ר",
+      "ĠاÙĦØ¥ Ø«ÙĨ",
+      "ĠاÙĦإثÙĨ ÙĬÙĨ",
+      "Ġng á»Ļ",
+      "ì¹ ł",
+      "د راج",
+      "Ġu da",
+      "Ġuda ÅĤo",
+      "ìº IJ",
+      "بر ÙĨاÙħج",
+      "ĠÑģÑĥд еб",
+      "ĠÑģÑĥдеб н",
+      "Ġzun ächst",
+      "ĠEduc ación",
+      "ãģ¨ãģª ãģ£ãģ¦ãģĦãģ¾ãģĻ",
+      "Ġ×Ķ×IJ ×ŀ×Ļת×Ļ",
+      "ĠÄ° nt",
+      "ĠÄ°nt ernet",
+      "ĠcaÅĤ ego",
+      "ãĥĹãĥª ãĥ³",
+      "إ بد",
+      "إبد اع",
+      "ĠпоÑĢ ÑĤал",
+      "à¹Ĥà¸ķ à¹ī",
+      "Ġ×Ķק ש×ķר",
+      "пл од",
+      "ĠÙħ د",
+      "ĠÙħد رÙĬد",
+      "×ŀסע ×ĵ×Ķ",
+      "ĠØ´ÙĬ ئ",
+      "ĠØ´ÙĬئ ا",
+      "à¸ģà¹Īà¸Ń สรà¹īาà¸ĩ",
+      "Ġì°¸ ê³ł",
+      "à¹Ģà¸Ĺ ร",
+      "à¹Ģà¸Ĺร à¸Ķ",
+      "Ġ×ij×ŀ קר×Ļ×Ŀ",
+      "Ġb ât",
+      "Ġbât iment",
+      "åij¼ ãģ³",
+      "ç´ł æķµ",
+      "ç´łæķµ ãģª",
+      "przedsiÄĻbior st",
+      "przedsiÄĻbiorst w",
+      "Ġ×ł×ª ×ķ׳×Ļ×Ŀ",
+      "×Ĺ׾ ×ķ×Ŀ",
+      "ร วย",
+      "Ùħ ÙĪضÙĪع",
+      "ĠÑģоб ÑĢан",
+      "вед ÑĥÑī",
+      "ĠÑĤе аÑĤ",
+      "ĠÑĤеаÑĤ ÑĢ",
+      "m eye",
+      "meye ceÄŁi",
+      "Ġpien iÄħ",
+      "ĠpieniÄħ d",
+      "ĠpieniÄħd ze",
+      "ÑĢез иденÑĤ",
+      "ØŃ ØµØ±",
+      "ìĺ ¥",
+      "à¹Ģย ืà¸Ńà¸Ļ",
+      "ĠÑĥ ни",
+      "ĠÑĥни веÑĢ",
+      "ĠÑĥнивеÑĢ Ñģ",
+      "ĠÑĥнивеÑĢÑģ иÑĤеÑĤ",
+      "ĠاÙĦر ØŃ",
+      "ĠاÙĦرØŃ ÙħÙĨ",
+      "ĠÑĤеÑħ нолог",
+      "ĠÑĤеÑħнолог ии",
+      "ìĹIJ ëĦĪ",
+      "ìĹIJëĦĪ ì§Ģ",
+      "Ġíķ Ń",
+      "ĠíķŃ ìĥģ",
+      "à¸ĺ า",
+      "à¸ĺา à¸ķุ",
+      "ĠEspañ ol",
+      "×ĵ×Ĵ ש",
+      "Ġêµ ī",
+      "Ġêµī ìŀ¥",
+      "Ġêµīìŀ¥ íŀĪ",
+      "ĠÅĤ at",
+      "ĠÅĤat wo",
+      "Ġk á»ĭch",
+      "إ ز",
+      "إز اÙĦØ©",
+      "ĠдейÑģÑĤв ие",
+      "ĠsaÄŁ layan",
+      "สุà¸Ķ ยà¸Ńà¸Ķ",
+      "Ġzosta Äĩ",
+      "Ġdispon ÃŃvel",
+      "ïº į",
+      "ver ständ",
+      "verständ lich",
+      "tw or",
+      "twor zyÄĩ",
+      "ع جز",
+      "à¹Ģà¸Ĥ à¹īม",
+      "ยà¹Ī à¸Ńม",
+      "Ġstrat ég",
+      "Ġstratég ie",
+      "à¸ľà¸¥ à¹Ħมà¹ī",
+      "Ġê°ģ ì¢ħ",
+      "ĠÙħ ÙĪا",
+      "ĠÙħÙĪا ض",
+      "ĠÙħÙĪاض ÙĬع",
+      "اØŃ ØªØ¬",
+      "اØŃتج اج",
+      "Ġ Ấ",
+      "ĠẤ n",
+      "×ŀ ×ŀש׾×Ķ",
+      "ĠÅŁek il",
+      "×ŀ ×Ĺ׾",
+      "×ŀ×Ĺ׾ ×ķת",
+      "Ġ à¸ĺ",
+      "Ġà¸ĺ ัà¸Ļ",
+      "Ġà¸ĺัà¸Ļ วา",
+      "Ġà¸ĺัà¸Ļวา à¸Ħม",
+      "Ġìĭ¤ ìłľ",
+      "Ġìĭ¤ìłľ ë¡ľ",
+      "ì¤ij ìķĻ",
+      "ëįĶ ëĿ¼",
+      "ĠÑĪ иÑĢ",
+      "ĠÑĪиÑĢ око",
+      "Ġsol ución",
+      "วาà¸ĩ à¹ģà¸ľà¸Ļ",
+      "×IJ×ķ×ĺ ×ķ×ŀ",
+      "×IJ×ķ×ĺ×ķ×ŀ ×ĺ×Ļ",
+      "ĠÑĢ еÑģÑĤ",
+      "ĠÑĢеÑģÑĤ оÑĢ",
+      "ĠÑĢеÑģÑĤоÑĢ ан",
+      "ëį ¸",
+      "ÑĤ ÑĢад",
+      "ÑĤÑĢад и",
+      "ÑĤÑĢади ÑĨион",
+      "ÑĤÑĢадиÑĨион н",
+      "มะ à¹Ģรà¹ĩ",
+      "มะà¹Ģรà¹ĩ à¸ĩ",
+      "à¹Ĥ ส",
+      "Ġol masını",
+      "×ŀ×ķס ר",
+      "ĠоÑĤноÑĪ ении",
+      "Ġê°ĢëĬ¥ ìĦ±",
+      "Ġy uk",
+      "Ġyuk arı",
+      "ìĨ Ķ",
+      "ĠÑģ ÑĦ",
+      "ĠÑģÑĦ еÑĢе",
+      "Ġק ×ķפ",
+      "ãĤ± ãĥ¼ãĤ",
+      "ãĤ±ãĥ¼ãĤ Ń",
+      "âĢķ âĢķ",
+      "ĠاÙĦØ£ ÙĦÙħ",
+      "ĠاÙĦØ£ÙĦÙħ اÙĨÙĬ",
+      "Ả N",
+      "ת×ķ׼ ׳×Ļ×ķת",
+      "ĠÑģÑĥÑīеÑģÑĤв ÑĥеÑĤ",
+      "æĪij ãĢħ",
+      "ĠاÙĦص ادر",
+      "ĠTr á»įng",
+      "Ġа д",
+      "Ġад миниÑģÑĤ",
+      "ĠадминиÑģÑĤ ÑĢа",
+      "ĠадминиÑģÑĤÑĢа ÑĨи",
+      "ĠдÑĢÑĥг ими",
+      "Ñģп еÑĪ",
+      "عÙĦاÙħ ات",
+      "Ġа б",
+      "Ġаб Ñģол",
+      "ĠабÑģол ÑİÑĤ",
+      "ĠабÑģолÑİÑĤ но",
+      "ฤ à¸Ķู",
+      "é tr",
+      "étr anger",
+      "нÑı ÑĤи",
+      "нÑıÑĤи е",
+      "×¢ ×ķ׳",
+      "×¢×ķ׳ ש",
+      "ĠÙĤ ائ",
+      "ĠÙĤائ ÙĦا",
+      "Ġм аÑģ",
+      "ĠмаÑģ ло",
+      "ãĥī ãĤ¤",
+      "ãĥīãĤ¤ ãĥĦ",
+      "å¿ħè¦ģ ãģĮãģĤãĤĬãģ¾ãģĻ",
+      "×ŀ×ķ×ĸ ×Ļ×IJ",
+      "×ŀ×ķ×ĸ×Ļ×IJ ×ķף",
+      "ĠNgo ại",
+      "Ġkê nh",
+      "à¸ģาร à¸Ńà¸Ńà¸ģà¹ģà¸ļà¸ļ",
+      "×ŀ פק",
+      "×ŀפק ×ĵ",
+      "ÙħÙĨ از",
+      "ÙħÙĨاز ÙĦ",
+      "ë· °",
+      "íĹ ¤",
+      "ÙħÙĩ ارات",
+      "Ġpropri été",
+      "פ×Ĵ ×Ļש×Ķ",
+      "Ñĩ ÑĢ",
+      "ÑĩÑĢ еж",
+      "ÑĩÑĢеж ден",
+      "×Ķ ×ķצ×IJ×Ķ",
+      "ØŃÙĥ ÙĬÙħ",
+      "ĠíĻ Ī",
+      "ĠíĻĪ íİĺìĿ´ì§Ģ",
+      "åİ ³",
+      "åݳ ãģĹãģĦ",
+      "×¢ ×ŀ×ĵ×Ķ",
+      "ĠAu ÃŁen",
+      "سÙĪ Ø¡",
+      "ë¹ Ī",
+      "ĠÙĪ Ø®",
+      "ĠÙĪØ® اصة",
+      "ин ÑĤеÑĢ",
+      "инÑĤеÑĢ еÑģ",
+      "èĩ´ ãģĹãģ¾ãģĻ",
+      "Ġhük üm",
+      "à¹Ħà¸Ĥ มัà¸Ļ",
+      "Ġdav ran",
+      "Ġdavran Ä±ÅŁ",
+      "à¹Ģà¸ķ ียà¸ĩ",
+      "в ÑĢем",
+      "вÑĢем енно",
+      "à¹Ģà¸Ĺศ à¸ģา",
+      "à¹Ģà¸Ĺศà¸ģา ล",
+      "å¼ķ ãģ£",
+      "å¼ķãģ£ è¶ĬãģĹ",
+      "×IJר ×ķ×Ĺ",
+      "×IJר×ķ×Ĺ ×ª",
+      "à¹Ģ วิ",
+      "à¹Ģวิ รà¹Į",
+      "à¸Ńยà¹Īาà¸ĩ รวà¸Ķà¹Ģรà¹ĩว",
+      "ĠìŬ íĸī",
+      "ĠÑĢан ÑĮ",
+      "ĠÑĢанÑĮ ÑĪе",
+      "Ġzob ow",
+      "Ġzobow iÄħ",
+      "ĠzobowiÄħ z",
+      "Ġ×ķ׼ ×ŀ×ķ×ijף",
+      "ĠاÙĦÙħ Ùĩ",
+      "ĠاÙĦÙħÙĩ ÙĨÙĬ",
+      "ãĤ¢ ãĤ¸",
+      "ãĤ¢ãĤ¸ ãĤ¢",
+      "ë°© ìĨ¡",
+      "à¸Ńà¸Ńà¸ģ à¸ģำลัà¸ĩ",
+      "à¸Ńà¸Ńà¸ģà¸ģำลัà¸ĩ à¸ģาย",
+      "am éli",
+      "améli orer",
+      "å½ĵãģŁãĤĬ åīį",
+      "Ġreg elm",
+      "Ġregelm Ã¤ÃŁig",
+      "ãģĬ åĭ",
+      "ãģĬåĭ §",
+      "ãģĬåĭ§ ãĤģ",
+      "Ġm Æ°á»Ŀi",
+      "بر Ùħج",
+      "ĠNat ürlich",
+      "ĠD Å©ng",
+      "ĠاÙĦر جاÙĦ",
+      "Ġthé p",
+      "Ġol muÅŁtur",
+      "×ŀ×ķס ×Ļק×Ķ",
+      "f älle",
+      "주 íĥĿ",
+      "ĠاÙĦÙģ رص",
+      "Ġnaj wiÄĻks",
+      "ĠnajwiÄĻks zy",
+      "Ġça ÄŁ",
+      "ĠçaÄŁ rı",
+      "ì¸ ł",
+      "ĠvÃŃ ct",
+      "ĠvÃŃct ima",
+      "ĠÑģовеÑĢ ÑĪен",
+      "×Ķ×Ļ ×Ļת×Ļ",
+      "à¹Ģà¸Ķ ี",
+      "à¹Ģà¸Ķี à¹ĭ",
+      "à¹Ģà¸Ķีà¹ĭ ยว",
+      "ü yü",
+      "Ġд оп",
+      "Ġдоп олн",
+      "Ġдополн иÑĤелÑĮно",
+      "à¹ģà¸ķà¸ģà¸ķà¹Īาà¸ĩ à¸ģัà¸Ļ",
+      "Ġá l",
+      "Ġál bum",
+      "à¸Ľà¸£à¸°à¸Īำ à¸Ľà¸µ",
+      "ĠÑĦ едеÑĢ",
+      "ĠÑĦедеÑĢ алÑĮн",
+      "Ġobs ÅĤ",
+      "ĠobsÅĤ ugi",
+      "à¹Ģร ืà¹Ī",
+      "à¹Ģรืà¹Ī à¸Ńย",
+      "à¹Ģรืà¹Īà¸Ńย à¹Ĩ",
+      "ëģ Į",
+      "Ġngh ìn",
+      "ĠBaÅŁkan lıģı",
+      "تأ سÙĬ",
+      "تأسÙĬ س",
+      "Ġ×ij×ij ×ķקר",
+      "Ġ×¢×ij×ķ×ĵ ×ķת",
+      "Ġبص ÙĪرة",
+      "ãĤıãģij ãģ§ãģ¯ãģªãģĦ",
+      "führ er",
+      "ãĤ¹ ãĤŃ",
+      "ãĤ¹ãĤŃ ãĥ«",
+      "ĠاÙĦÙĤ ض",
+      "ĠاÙĦÙĤض ÙĬØ©",
+      "Ġдолж ноÑģÑĤ",
+      "Ùģار ÙĤ",
+      "Ġcomeç ou",
+      "Ġorganis é",
+      "Ġxu ân",
+      "ĠÑģообÑī аеÑĤ",
+      "ĠпÑĢи д",
+      "ĠпÑĢид еÑĤÑģÑı",
+      "TÃľ RK",
+      "ãĥ¬ ãĥ¼ãĤ·ãĥ§ãĥ³",
+      "Kh ông",
+      "است Ùģ",
+      "استÙģ ادة",
+      "ä¸ĬãģĮ ãģ£ãģ¦",
+      "Ġum ie",
+      "Ġumie jÄĻ",
+      "ĠumiejÄĻ tn",
+      "ĠumiejÄĻtn oÅĽci",
+      "ëĤ ¸",
+      "à¹Ģà¸Ļ à¸Ńรà¹Į",
+      "×ĵ×ķ ×ķ×Ĺ",
+      "ÃŃs imo",
+      "I ÃĬ",
+      "IÃĬ N",
+      "Ġalcan ç",
+      "Ġ à¸ķุ",
+      "Ġà¸ķุ ลา",
+      "Ġà¸ķุลา à¸Ħม",
+      "ש׾ ×ĺ×ķף",
+      "Ġél è",
+      "Ġélè ves",
+      "ĠÄij u",
+      "ĠÄiju á»ķi",
+      "ĠØ£ Ùģ",
+      "ĠØ£Ùģ رÙĬ",
+      "ĠØ£ÙģرÙĬ ÙĤÙĬ",
+      "ĠØ£ÙģرÙĬÙĤÙĬ ا",
+      "ãĤĴæİ¢ ãģĻ",
+      "ĠпÑĢед ложениÑı",
+      "ج اد",
+      "ĠÑħоÑĤ ÑĮ",
+      "Ñģ ал",
+      "Ñģал он",
+      "à¸Ľà¸£à¸° à¹Ģม",
+      "à¸Ľà¸£à¸°à¹Ģม ิà¸Ļ",
+      "ãĤŃ ãĥĥãĥģ",
+      "ãĤŃãĥĥãĥģ ãĥ³",
+      "×ij×ĵ×Ļק ×ķת",
+      "Ġch ù",
+      "Ġchù a",
+      "ÐĴ иде",
+      "ÐĴиде о",
+      "иÑĢов ка",
+      "ĠÑħоÑĤ иÑĤе",
+      "Ġspéc ifique",
+      "รส à¸Ĭาà¸ķิ",
+      "è¾¼ ãĤĵãģł",
+      "伸 ãģ³",
+      "×Ķצ׾ ×Ĺת",
+      "ãģ©ãģ® ãĤĪãģĨãģ«",
+      "سع ادة",
+      "Ġл ид",
+      "Ġлид еÑĢ",
+      "ม à¸ĩ",
+      "มà¸ĩ à¸Ħล",
+      "ØŃ Ø§ÙħÙĦ",
+      "หล ุà¸Ķ",
+      "à¸Ńยà¹Īาà¸ĩ à¸ķà¹Īà¸Ń",
+      "à¸Ńยà¹Īาà¸ĩà¸ķà¹Īà¸Ń à¹Ģà¸Ļืà¹Īà¸Ńà¸ĩ",
+      "ãģķãģĽãģ¦ éłĤ",
+      "تس ÙĪÙĬ",
+      "تسÙĪÙĬ ÙĤ",
+      "ĠaÅŁaģı d",
+      "ĠaÅŁaģıd aki",
+      "ĠÑĨ елÑĮ",
+      "ĠÑĨелÑĮ Ñİ",
+      "ĠAra ÅŁtırma",
+      "à¸Ĥัà¸ļ รà¸ĸ",
+      "Ùĩ Ø°Ùĩ",
+      "ลà¸ĩ à¸Ĺะ",
+      "ลà¸ĩà¸Ĺะ à¹Ģà¸ļ",
+      "ลà¸ĩà¸Ĺะà¹Ģà¸ļ ียà¸Ļ",
+      "تÙĥ اÙħÙĦ",
+      "Ġc io",
+      "Ġcio è",
+      "ãģ¦ ãģĬãģı",
+      "ĠاÙĦصØŃ ÙģÙĬ",
+      "ĠíĬ¹ ìłķ",
+      "полн иÑĤÑĮ",
+      "ãĤĵ ãģĺãĤĥãģªãģĦ",
+      "ãĤĵãģĺãĤĥãģªãģĦ ãģĭ",
+      "ĠاÙĦج Ùĩ",
+      "ĠاÙĦجÙĩ ات",
+      "ĠÑĥÑģпеÑĪ но",
+      "Ġв ок",
+      "Ġвок ÑĢÑĥг",
+      "ĠÑģиÑĤÑĥ аÑĨиÑı",
+      "Ġ×Ķ×IJ ×ŀר",
+      "Ġ×Ķ×IJ×ŀר ×Ļק",
+      "Ġ×Ķ×IJ×ŀר×Ļק ×IJ×Ļ",
+      "×ŀ ×Ĵ×ĸ",
+      "×ŀ×Ĵ×ĸ ×Ļף",
+      "Ġак ÑĤÑĥ",
+      "ĠакÑĤÑĥ алÑĮн",
+      "é ta",
+      "éta is",
+      "Ġmog ÅĤa",
+      "ĠÑĤоÑĩ ки",
+      "Ġ×ŀ×Ķ ×ŀ×¢",
+      "Ġ×ŀ×Ķ×ŀ×¢ ×¨×Ľ×ª",
+      "มี à¸Ľà¸£à¸°à¸ªà¸´à¸Ĺà¸ĺà¸´à¸łà¸²à¸ŀ",
+      "×Ļר ×Ļ×ĵ×Ķ",
+      "×Ĵר ×ŀ׳",
+      "×Ĵר×ŀ׳ ×Ļ×Ķ",
+      "Ġг лав",
+      "Ġглав ное",
+      "Ġ미 ëŀĺ",
+      "Ġ׳׼ ×ķ׳×Ķ",
+      "ĠÙĪ Ø·ÙĨÙĬ",
+      "op port",
+      "opport unitÃł",
+      "Ġh ủy",
+      "ĠÙĦ تØŃ",
+      "ĠÙĦتØŃ ÙĤÙĬÙĤ",
+      "Ġó rg",
+      "Ġórg ão",
+      "ãĤ¹ ãĥĶ",
+      "ãĤ¹ãĥĶ ãĥ¼ãĥī",
+      "Ġön ü",
+      "Ġönü ne",
+      "Ùħع اÙħÙĦ",
+      "ש×ŀ ×Ļר×Ķ",
+      "ĠвеÑģÑĮ ма",
+      "ĠwiÄĻks zo",
+      "ĠwiÄĻkszo ÅĽÄĩ",
+      "Ġاست راتÙĬج",
+      "ĠاستراتÙĬج ÙĬØ©",
+      "ĠÙģ Ø¥",
+      "ĠÙģØ¥ ذا",
+      "à¹Ģà¸Ĭืà¹Īà¸Ń ม",
+      "à¹Ģà¸Ĭืà¹Īà¸Ńม à¸ķà¹Īà¸Ń",
+      "Ġ׾ פר",
+      "Ġ׾פר ×ĺ×Ļ×Ŀ",
+      "Ùħض ÙĬ",
+      "ĠGer çek",
+      "Ġçocuk ların",
+      "ÙĪØ« ائÙĤ",
+      "ĠÙħساء Ùĭ",
+      "Ġunterstüt zt",
+      "Ġpré st",
+      "Ġprést amo",
+      "ĠÐłÐ°Ð· меÑĢ",
+      "ĠÅŁ eker",
+      "Ġsé culo",
+      "×ij×Ķ ×Ļר",
+      "Ø´Ùĩ ÙĪر",
+      "Ġ à¸Ńีà¸ģ",
+      "Ġà¸Ńีà¸ģ à¸Ĺัà¹īà¸ĩ",
+      "Ġlleg ó",
+      "à¸¨à¸´à¸¥à¸Ľ ะ",
+      "æĪij ãģĮ",
+      "æĪijãģĮ 家",
+      "ع ÙĤÙĪ",
+      "عÙĤÙĪ بات",
+      "ĠF älle",
+      "Ġs ÅĤuż",
+      "ĠsÅĤuż b",
+      "ĠاÙĦØŃÙĤ ÙĪÙĤ",
+      "Ġпл иÑĤ",
+      "Ġи ноÑģÑĤ",
+      "ĠиноÑģÑĤ ÑĢан",
+      "ĠиноÑģÑĤÑĢан н",
+      "à¹ĥà¸Ļ à¸Ĥà¸ĵะà¸Ĺีà¹Ī",
+      "ãĤ« ãĥĨ",
+      "ãĤ«ãĥĨ ãĤ´",
+      "ãĤ«ãĥĨãĤ´ ãĥª",
+      "à¸Ńิ ส",
+      "à¸Ńิส ระ",
+      "à¹Ģà¸ľà¸¢ à¹ģ",
+      "à¹Ģà¸ľà¸¢à¹ģ à¸ŀร",
+      "à¹Ģà¸ľà¸¢à¹ģà¸ŀร à¹Ī",
+      "ãģĬ ãģĦ",
+      "ãģĬãģĦ ãģĹãģĦ",
+      "است ÙĤÙĦ",
+      "استÙĤÙĦ اÙĦ",
+      "تØŃ Ø¶",
+      "تØŃض ÙĬر",
+      "åĬ© ãģij",
+      "Ùħر اÙģÙĤ",
+      "Ġ×ĵ ×ķר",
+      "Ġ×ĵ×ķר ש",
+      "×ŀת×Ļ ×Ļ×Ĺס",
+      "ס ×Ļ׼",
+      "ס×Ļ׼ ×ķ×Ŀ",
+      "íĮĮ íĬ¸",
+      "Ġwy ÅĽ",
+      "ĠwyÅĽ w",
+      "ĠwyÅĽw iet",
+      "ĠwyÅĽwiet l",
+      "ĠاÙĦاÙĨ ساÙĨ",
+      "ĠStra ÃŁen",
+      "ï¼ ¬",
+      "ãģ« åŁº",
+      "ãģ«åŁº ãģ¥",
+      "Ġcap ÃŃtulo",
+      "ลุ ย",
+      "Ġ×Ķ×ŀק צ×ķ×¢×Ļ",
+      "ãģĤãĤĭ ç¨ĭ度",
+      "á» ¢",
+      "ĠاÙĦ ÙĦا",
+      "ĠاÙĦÙĦا زÙħØ©",
+      "æķĻ ãģĪ",
+      "Ġרש ×IJ×Ļ",
+      "з ав",
+      "зав иÑģ",
+      "завиÑģ им",
+      "à¸Ľà¸±à¸Ī à¸Īัย",
+      "à¹Ģà¸ĭ ล",
+      "à¹Ģà¸ĭล ลà¹Į",
+      "Ġdiffé rence",
+      "ĠAlt ın",
+      "Ġк ÑĢай",
+      "ĠкÑĢай не",
+      "Ġз ло",
+      "Ġgün ümüz",
+      "Ġн аÑĤÑĥÑĢ",
+      "ĠнаÑĤÑĥÑĢ алÑĮн",
+      "×Ĵ×ķ׾ ש×Ļ×Ŀ",
+      "Ġк аÑĤегоÑĢ",
+      "ĠкаÑĤегоÑĢ ии",
+      "Ġз нак",
+      "à¸ģà¹Īà¸Ńà¸Ļ หà¸Ļà¹īา",
+      "à¸ģà¹Īà¸Ńà¸Ļหà¸Ļà¹īา à¸Ļีà¹ī",
+      "ĠÙħÙĨ ت",
+      "ĠÙħÙĨت خب",
+      "ãĥĽ ãĥ¼ãĥ«",
+      "Ġе вÑĢо",
+      "ส ว",
+      "สว ม",
+      "ĠìľĦ ìĽIJ",
+      "ĠìľĦìĽIJ ëĭĺ",
+      "ĠاÙĦØŃ ÙĪØ«",
+      "ĠاÙĦØŃÙĪØ« ÙĬ",
+      "ĠÑģодеÑĢж иÑĤ",
+      "ãĥķãĤ¡ ãĥĥãĤ·ãĥ§ãĥ³",
+      "Ġ à¸ģัà¸Ļ",
+      "Ġà¸ģัà¸Ļ ย",
+      "Ġà¸ģัà¸Ļย ายà¸Ļ",
+      "ãĤª ãĥª",
+      "ãĤªãĥª ãĤ¸",
+      "ãĤªãĥªãĤ¸ ãĥĬãĥ«",
+      "Ġб ÑĢенд",
+      "ãĤĴæĮģ ãģ£ãģ¦ãģĦãĤĭ",
+      "Ġinvers ión",
+      "Ġê° ĸ",
+      "Ġê°ĸ ê³ł",
+      "Ġnov itÃł",
+      "ê´Ģ ê´ij",
+      "Ġà¸ŀ ฤษ",
+      "Ġà¸ŀฤษ à¸łà¸²",
+      "Ġà¸ŀà¸¤à¸©à¸łà¸² à¸Ħม",
+      "×ķר ×Ĺ×Ļ×Ŀ",
+      "׼׾ ×ķ׾",
+      "Ġng ạc",
+      "×Ļ ×Ļש",
+      "×Ļ×Ļש ×ķ×ij",
+      "f äll",
+      "fäll ig",
+      "ĠÑĤÑĢеб ÑĥеÑĤÑģÑı",
+      "Ġcar á",
+      "Ġcará cter",
+      "Ġprinc ÃŃpio",
+      "ĠÅĤ az",
+      "ĠÅĤaz ien",
+      "ĠÅĤazien k",
+      "Ġgi ãn",
+      "ÑģÑĤÑĢа ива",
+      "Ùħس اب",
+      "Ùħساب ÙĤØ©",
+      "à¹Ģà¸Ħรืà¹Īà¸Ńà¸ĩ à¸Ķืà¹Īม",
+      "ترÙĥ ÙĬب",
+      "vol ução",
+      "ĠÐŁ оÑĩ",
+      "ĠÐŁÐ¾Ñĩ ем",
+      "ĠÐŁÐ¾Ñĩем Ñĥ",
+      "казал оÑģÑĮ",
+      "ĠпÑĢимен ениÑı",
+      "à¹Ģà¸Ĺ ียม",
+      "íĮ Ķ",
+      "à¸Ĥà¹īà¸Ń à¹Ģสà¸Ļà¸Ń",
+      "à¸Ľà¸±à¸į à¸įา",
+      "Ġоб ÑĥÑĩ",
+      "ĠобÑĥÑĩ ениÑı",
+      "ĠÑģеÑĢ и",
+      "ĠÑģеÑĢи ал",
+      "Ġingl és",
+      "ĠÙĦ Ùĥرة",
+      "Ġ×ĺ ׾",
+      "Ġ×ĺ׾ פ×ķף",
+      "Ġìł ij",
+      "Ġìłij ê·¼",
+      "×IJ ×ķ×Ĵ",
+      "×IJ×ķ×Ĵ ×ķס",
+      "×IJ×ķ×Ĵ×ķס ×ĺ",
+      "ĠболÑĮÑĪ ое",
+      "ĠÐļон еÑĩно",
+      "×¢×Ļת ×ķ׳",
+      "×¢×Ļת×ķ׳ ×IJ×Ļ",
+      "Ġкноп к",
+      "Ġз н",
+      "Ġзн аÑĤÑĮ",
+      "ĠÄij á»±",
+      "ĠÄijá»± ng",
+      "вл аж",
+      "влаж н",
+      "×ŀ ×Ļ×ĺ×ij",
+      "ãĤ¬ ãĤ¤",
+      "ãĤ¬ãĤ¤ ãĥī",
+      "........ ..",
+      "Ġà¸ģ ุม",
+      "Ġà¸ģุม à¸łà¸²à¸ŀ",
+      "Ġà¸ģà¸¸à¸¡à¸łà¸²à¸ŀ ัà¸Ļ",
+      "Ġà¸ģà¸¸à¸¡à¸łà¸²à¸ŀัà¸Ļ à¸ĺ",
+      "Ġà¸ģà¸¸à¸¡à¸łà¸²à¸ŀัà¸Ļà¸ĺ à¹Į",
+      "be z",
+      "bez pieczeÅĦst",
+      "bezpieczeÅĦst w",
+      "ãĥijãĥij æ´»",
+      "ع اط",
+      "عاط Ùģ",
+      "ĠÄij áºŃm",
+      "Ġз ÑĢ",
+      "ĠзÑĢ ениÑı",
+      "Ġbor ç",
+      "Ġнед ел",
+      "Ġнедел Ñİ",
+      "Ġh á»ı",
+      "Ġhá»ı ng",
+      "ìŀ¥ ìķł",
+      "ìŀ¥ìķł ìĿ¸",
+      "ĠاÙĦع ÙĦاÙĤØ©",
+      "Ġíģ ¬",
+      "Ġíģ¬ ê²Į",
+      "à¹Ħร à¹Ī",
+      "à¸ļา à¸Ķ",
+      "à¸ļาà¸Ķ à¹Ģà¸Īà¹ĩà¸ļ",
+      "à¸Ŀ รั",
+      "à¸Ŀรั à¹Īà¸ĩ",
+      "à¸Ŀรัà¹Īà¸ĩ à¹Ģศ",
+      "à¸Ŀรัà¹Īà¸ĩà¹Ģศ ส",
+      "ר ×¢×Ļ",
+      "רע×Ļ ×ķ׳×ķת",
+      "Ġë Į",
+      "ĠëĮ ĵ",
+      "ĠëĮĵ ê¸Ģ",
+      "Ġnaj b",
+      "Ġnajb li",
+      "Ġnajbli ż",
+      "Ġnajbliż sz",
+      "ĠиÑģполÑĮз ÑĥеÑĤÑģÑı",
+      "Ġcient ÃŃf",
+      "ĠcientÃŃf ico",
+      "×¢ ×ŀק",
+      "Ġg ợi",
+      "Ø´ ØŃÙĨ",
+      "ĠÅĽ m",
+      "ĠÅĽm ier",
+      "ĠÅĽmier ci",
+      "à¸Ħาสิà¹Ĥà¸Ļ à¸Ńà¸Ńà¸Ļà¹Ħลà¸Ļà¹Į",
+      "×Ĺש×ij ת×Ļ",
+      "Ġn ingu",
+      "Ġningu ém",
+      "è¾¼ ãĤģ",
+      "ãģ ·",
+      "ĠÑĥ г",
+      "ĠÑĥг ол",
+      "ï½ °",
+      "פת ×Ļ×Ĺ",
+      "פת×Ļ×Ĺ ×ª",
+      "Ġ×Ķר×IJש ×ķ׳×Ļ×Ŀ",
+      "p ósito",
+      "ãĤŃ ãĥ¬ãĤ¤",
+      "ãģ© ãģĵãĤį",
+      "à¹Ģà¸Ĺà¹Īา à¹Ħ",
+      "à¹Ģà¸Ĺà¹Īาà¹Ħ หร",
+      "à¹Ģà¸Ĺà¹Īาà¹Ħหร à¹Ī",
+      "ĠинÑĤеÑĢ ÑĮеÑĢ",
+      "ĠØŃ Ø§Ø¬",
+      "ĠØŃاج Ø©",
+      "สี à¸Ĥาว",
+      "ìĸ ¼",
+      "Ġn á»Ļ",
+      "Ġná»Ļ p",
+      "ĠÃŃ nd",
+      "ĠÃŃnd ice",
+      "สำ รวà¸Ī",
+      "Ġкажд ой",
+      "Ġhot éis",
+      "Ġnast ÄĻ",
+      "ĠnastÄĻ pn",
+      "Ġ×Ķק ×ķ×ĵ",
+      "Ġ×Ķק×ķ×ĵ ×Ŀ",
+      "פ ×ķפ",
+      "פ×ķפ ×ķ׾",
+      "פ×ķפ×ķ׾ ר×Ļ",
+      "вÑĪ ей",
+      "ãĤ·ãĥ³ ãĥĹ",
+      "ãĤ·ãĥ³ãĥĹ ãĥ«",
+      "ĠzdjÄĻ Äĩ",
+      "ĠгÑĢÑĥпп а",
+      "Ġпом еÑī",
+      "ĠпомеÑī ениÑı",
+      "ãģ©ãģĨ ãģĦãģĨ",
+      "ĠиÑģп ÑĭÑĤа",
+      "Ġog ÅĤ",
+      "ĠogÅĤ os",
+      "ĠogÅĤos zen",
+      "ĠogÅĤoszen i",
+      "สรà¹īาà¸ĩ สรร",
+      "สรà¹īาà¸ĩสรร à¸Ħà¹Į",
+      "à¸ŀร รà¸ĵ",
+      "Ġçık Ä±ÅŁ",
+      "ĠÑĩаÑģÑĤ ноÑģÑĤи",
+      "Ġ×ķ ×Ļ×ķתר",
+      "ç¶ļãģį ãĤĴ",
+      "ç¶ļãģįãĤĴ èªŃ",
+      "ç¶ļãģįãĤĴèªŃ ãĤĢ",
+      "à¸ģร ั",
+      "à¸ģรั ม",
+      "г ÑĢаÑĦ",
+      "Ġв лад",
+      "Ġвлад елÑĮ",
+      "ĠвладелÑĮ ÑĨ",
+      "Ġistedi ÄŁ",
+      "ĠistediÄŁ iniz",
+      "×ij׾ ×¢",
+      "×ij×ľ×¢ ×ĵ×Ļ",
+      "ÙħÙĪ اÙģ",
+      "ÙħÙĪاÙģ ÙĤØ©",
+      "Ġ×Ļ ×ķר",
+      "Ġ×Ļ×ķר ק",
+      "ãĤ«ãĥ¼ãĥī ãĥŃãĥ¼ãĥ³",
+      "ĠاÙĦÙħØ´ ÙĥÙĦ",
+      "ĠاÙĦÙħØ´ÙĥÙĦ Ø©",
+      "ĠêµŃ íļĮ",
+      "ס פ×ĺ",
+      "ספ×ĺ ×ŀ",
+      "ספ×ĺ×ŀ ×ijר",
+      "Ġìĸ´ ëłµ",
+      "Ùĥ اÙħ",
+      "ÙĥاÙħ ÙĬرا",
+      "sch lü",
+      "schlü sse",
+      "ĠØ« ÙĨ",
+      "ĠØ«ÙĨ ائÙĬ",
+      "ìī ½",
+      "ĠÐŀ Ñģоб",
+      "ĠÐŀÑģоб енно",
+      "Ġин веÑģÑĤи",
+      "ĠинвеÑģÑĤи ÑĨи",
+      "اØŃ ØªÙħ",
+      "اØŃتÙħ اÙĦ",
+      "E Äŀ",
+      "EÄŀ Ä°",
+      "íķĺ ê²łëĭ¤",
+      "Ġ×IJ ×ijר×Ķ",
+      "Ġ×IJ×ijר×Ķ ×Ŀ",
+      "Ġ×ij×Ĺ ×Ļ׳×Ŀ",
+      "Ø£ ÙĪض",
+      "Ø£ÙĪض اع",
+      "Ġdé l",
+      "Ġdél ai",
+      "Ġ×IJ×ķ×Ķ ×ij×Ļ×Ŀ",
+      "ĠÑģо Ñħ",
+      "ĠÑģоÑħ ÑĢ",
+      "ĠÑģоÑħÑĢ ани",
+      "ĠдоÑģÑĤ иж",
+      "ĠдоÑģÑĤиж ени",
+      "สิà¹Īà¸ĩ à¹ģ",
+      "สิà¹Īà¸ĩà¹ģ วà¸Ķ",
+      "สิà¹Īà¸ĩà¹ģวà¸Ķ ล",
+      "สิà¹Īà¸ĩà¹ģวà¸Ķล à¹īà¸Ńม",
+      "ĠاÙĦÙħ باشر",
+      "ĠÑĦ иг",
+      "ĠÑĦиг ÑĥÑĢ",
+      "мож ем",
+      "׾×ŀ×Ļ×ĵ ×Ķ",
+      "Ġcin é",
+      "Ġciné ma",
+      "Ġb ada",
+      "Ġbada ÅĦ",
+      "جب ÙĩØ©",
+      "Ġд еп",
+      "Ġдеп ÑĥÑĤ",
+      "ĠдепÑĥÑĤ аÑĤ",
+      "Ġdist ância",
+      "ĠاÙĦÙħ عار",
+      "ĠاÙĦÙħعار ضة",
+      "thè se",
+      "ü nc",
+      "ünc ü",
+      "Ġдан ного",
+      "ĠBel gi",
+      "ĠBelgi ë",
+      "Ġ×ij ×ijק",
+      "Ġ×ij×ijק ש×Ķ",
+      "ย à¹Īาà¸Ļ",
+      "Ġsol ução",
+      "Ġ×Ķצ ×ĺר",
+      "Ġ×Ķצ×ĺר פ×ķ",
+      "ĠØ£ÙĨ ØŃ",
+      "ĠØ£ÙĨØŃ Ø§Ø¡",
+      "Ġد ÙħØ´",
+      "ĠدÙħØ´ ÙĤ",
+      "มั à¹ī",
+      "มัà¹ī ย",
+      "Ùħ غرب",
+      "است عÙħاÙĦ",
+      "ĠS ÅĤow",
+      "ĠëıĻ ìĭľ",
+      "ĠëıĻìĭľ ìĹIJ",
+      "ĠÑģ оÑģ",
+      "ĠÑģоÑģ ед",
+      "ì²Ń ìĨĮ",
+      "ì²ŃìĨĮ ëħĦ",
+      "Ġг ÑĢаÑĦ",
+      "ĠгÑĢаÑĦ ик",
+      "Ġìŀij ìĿĢ",
+      "Ġyet i",
+      "Ġyeti ÅŁtir",
+      "ĠìĿ´ê²ĥ ìĿ´",
+      "ห à¹Īาà¸ĩ",
+      "Ø¥ ÙħÙĥاÙĨ",
+      "Ø¥ÙħÙĥاÙĨ ÙĬØ©",
+      "است عراض",
+      "ÙħØ® در",
+      "ĠÑĩ ÑĥÑĤÑĮ",
+      "Ùħ دÙĬر",
+      "ÙħدÙĬر ÙĬØ©",
+      "Ġà¹Ģม ษ",
+      "Ġà¹Ģมษ ายà¸Ļ",
+      "Ġм еÑħ",
+      "ĠмеÑħ аниз",
+      "ĠмеÑħаниз м",
+      "ĠÑģ Ñĥм",
+      "ĠÑģÑĥм мÑĥ",
+      "Ġv ö",
+      "Ġvö ll",
+      "Ġvöll ig",
+      "Ġд ÑĢÑĥз",
+      "ĠдÑĢÑĥз ÑĮÑı",
+      "ãĤĴåĪ©çĶ¨ ãģĹãģ¦",
+      "à¸ļรร à¸Īุ",
+      "po życz",
+      "×ŀש ׼",
+      "×ŀש׼ ×ł×ª",
+      "×ŀ×©×Ľ×ł×ª ×IJ",
+      "Ġeuropé en",
+      "Ġpropri é",
+      "Ġproprié taire",
+      "Ġkh ấu",
+      "ãģĦãģŁãģł ãģijãĤĭ",
+      "Ġtec rü",
+      "Ġtecrü be",
+      "×Ķ ×ij",
+      "×Ķ×ij ׳×Ķ",
+      "Ġcu Ì",
+      "ĠcuÌ ī",
+      "ĠcuÌī a",
+      "×IJ ×ķ×ķ",
+      "×IJ×ķ×ķ ×Ļר×Ķ",
+      "Ġ׼×ķ׾ ×ķ",
+      "U lus",
+      "Ulus lararası",
+      "Ġ׳ ×ķת",
+      "Ġ׳×ķת ף",
+      "ãģ« åIJij",
+      "ãģ«åIJij ãģijãģ¦",
+      "ë¹ Ľ",
+      "à¸Ĺ ัà¸ģษ",
+      "à¸Ĺัà¸ģษ ะ",
+      "س ÙĤÙĪ",
+      "سÙĤÙĪ Ø·",
+      "Ġв н",
+      "Ġвн еÑĪ",
+      "ĠвнеÑĪ не",
+      "Ġur z",
+      "Ġurz ÄĻd",
+      "Ġá mb",
+      "Ġámb ito",
+      "à¸Ń à¸ĺิ",
+      "à¸Ńà¸ĺิ à¸ļาย",
+      "Ġ ÅĤad",
+      "ĠÅĤad n",
+      "ê±´ ì¶ķ",
+      "wód zt",
+      "wództ w",
+      "Ġquest ões",
+      "Ġש ק",
+      "Ġשק ×Ļ×ij׾",
+      "Ġmiejsc owoÅĽci",
+      "Ġв ал",
+      "Ġвал ÑİÑĤ",
+      "hä user",
+      "หà¸Ļ à¸Ńà¸ĩ",
+      "ãģ¨ åħ±",
+      "ãģ¨åħ± ãģ«",
+      "ãĥı ãĥ¼ãĥī",
+      "Ġê°ľ ìµľ",
+      "ĠоÑģнов ном",
+      "Ġм ÑıÑģ",
+      "اع ت",
+      "اعت ÙĤاÙĦ",
+      "สà¸ĸ ิ",
+      "สà¸ĸิ à¸ķิ",
+      "N gu",
+      "Ngu á»ĵn",
+      "ĠÙħ جÙĦ",
+      "ĠÙħجÙĦ Ø©",
+      "à¹ģà¸Ĥ à¸Ļ",
+      "ĠاÙĦÙĦÙĬ بÙĬ",
+      "פע×Ļ׾ ×ķ×Ļ×ķת",
+      "Ġ×Ķר פ×ķ×IJ×Ļ",
+      "פר ×ķפ",
+      "פר×ķפ ×Ļ׾",
+      "ק ׾×IJ",
+      "ק׾×IJ ס×Ļ",
+      "Ùĥت Ø´Ùģ",
+      "ãģ«ãģª ãģ£ãģ¦ãģĹãģ¾ãģĨ",
+      "à¹Ģà¸Ħล à¹ĩà¸Ķ",
+      "à¹Ģà¸Ħลà¹ĩà¸Ķ ลัà¸ļ",
+      "Ġì» ´",
+      "Ġì»´ íĵ¨",
+      "Ġì»´íĵ¨ íĦ°",
+      "Ġ×Ĺ×Ļ ×ķ×ij×Ļ",
+      "Ġnä m",
+      "Ġnäm lich",
+      "åij¼ ãģ°",
+      "åij¼ãģ° ãĤĮ",
+      "ĠÑĢ ол",
+      "ĠÑĢол и",
+      "Ġspécial isé",
+      "à¸Ļ วัà¸ķ",
+      "à¸Ļวัà¸ķ à¸ģรรม",
+      "ÙĨص ÙĪص",
+      "пеÑĢ ед",
+      "пеÑĢед аÑĩ",
+      "thè que",
+      "Ġר×IJ ×Ļת×Ļ",
+      "ãĥĢ ãĤ¦ãĥ³",
+      "ãĤı ãģĭ",
+      "ãĤıãģĭ ãģ£ãģ¦",
+      "беÑĢ еж",
+      "ĠÑģ ек",
+      "ĠÑģек ÑĢ",
+      "ĠÑģекÑĢ еÑĤ",
+      "ĠпоÑģÑĤоÑıн н",
+      "à¸Ĥà¸Ļ สà¹Īà¸ĩ",
+      "Ġm ük",
+      "Ġmük em",
+      "Ġmükem mel",
+      "еÑĤ еÑģÑĮ",
+      "ĠاÙĦسÙĨ ÙĪات",
+      "ĠìłĦ íĺĢ",
+      "Ġ×Ķ×ŀק ×ķר×Ļ",
+      "Ġmü d",
+      "Ġmüd ah",
+      "Ġmüdah ale",
+      "Ġwy b",
+      "Ġwyb ór",
+      "Ġtend ência",
+      "إ دار",
+      "إدار ÙĬØ©",
+      "Ġunterstüt zen",
+      "ת ×ijר",
+      "ת×ijר ר",
+      "Ġdi á",
+      "Ġdiá logo",
+      "ĠÃĸ nce",
+      "ĠÃĸnce ki",
+      "ãĤ¹ãĥĿ ãĥĥãĥĪ",
+      "ëĦ £",
+      "ĠG eli",
+      "ĠGeli ÅŁ",
+      "ãĤĴ éĢļ",
+      "ãĤĴéĢļ ãģĹãģ¦",
+      "ĠFuÃŁ ball",
+      "Ġsal ari",
+      "Ġsalari é",
+      "ĠпÑĢодÑĥк ÑĤов",
+      "صÙģ ÙĤØ©",
+      "รว à¸ļ",
+      "รวà¸ļ รวม",
+      "à¹ĥà¸Ļ à¸IJาà¸Ļ",
+      "à¹ĥà¸Ļà¸IJาà¸Ļ ะ",
+      "Ġkay na",
+      "Ġkayna ģı",
+      "Ġìŀij íĴĪ",
+      "ĠвÑĭ ÑĢаж",
+      "ĠвÑĭÑĢаж ен",
+      "ĠÑģÑĤ еп",
+      "ĠÑģÑĤеп ени",
+      "ĠاÙĦÙħ ÙĪجÙĪد",
+      "ĠاÙĦÙħÙĪجÙĪد Ø©",
+      "ล à¹īม",
+      "Ġnaj czÄĻ",
+      "ĠnajczÄĻ ÅĽcie",
+      "ĠnajczÄĻÅĽcie j",
+      "Ġz wy",
+      "Ġzwy k",
+      "Ġzwyk ÅĤ",
+      "Ġê·¸ëłĩ ì§Ģ",
+      "à¸ģระ à¸Ī",
+      "à¸ģระà¸Ī าย",
+      "Ġëĭ µ",
+      "Ġëĭµ ë³Ģ",
+      "ĠÑĢе ак",
+      "ĠÑĢеак ÑĨи",
+      "ĠÅĽwie ż",
+      "ĠÑģÑĤоим оÑģÑĤи",
+      "ÙħÙĨ اÙĤ",
+      "ÙħÙĨاÙĤ Ø´",
+      "ÙħÙĨاÙĤØ´ Ø©",
+      "ĠÑħоÑĩ Ñĥ",
+      "ãĥľ ãĥ¼ãĥī",
+      "Ġróż nic",
+      "Ġк ÑĢÑĭ",
+      "ĠкÑĢÑĭ ÑĪ",
+      "âľ ĵ",
+      "ãĤ³ãĥ³ ãĥĨãĥ³",
+      "ãĤ³ãĥ³ãĥĨãĥ³ ãĥĦ",
+      "ĠпÑĢед поÑĩ",
+      "×ŀר ×ij×Ļת",
+      "ĠØ´ Ùĥ",
+      "ĠØ´Ùĥ را",
+      "Ġд ал",
+      "Ġдал ек",
+      "Ġдалек о",
+      "بر ÙĬØ·",
+      "برÙĬØ· اÙĨÙĬا",
+      "ع ÙĨا",
+      "عÙĨا ÙĬØ©",
+      "ĠÑĢаÑģÑģ каз",
+      "ĠÑĢаÑģÑģказ Ñĭва",
+      "Ø£ ÙĦÙĪ",
+      "Ø£ÙĦÙĪ اÙĨ",
+      "æĮģ ãģ£ãģ¦",
+      "æĮģãģ£ãģ¦ ãģĦ",
+      "Ùħباد ئ",
+      "×Ķ ×¢×ijר",
+      "×Ķ×¢×ijר ת",
+      "Ġyay ı",
+      "Ġyayı ml",
+      "Ġyayıml a",
+      "m át",
+      "mát icos",
+      "à¸ģ ัà¸ĩ",
+      "à¸ģัà¸ĩ วล",
+      "Ġ׾ פת",
+      "Ġ×ľ×¤×ª ×ķ×Ĺ",
+      "à¸ŀฤ à¸ķิ",
+      "à¸ŀฤà¸ķิ à¸ģรรม",
+      "í Ĥ¬",
+      "Ġок ÑĢÑĥг",
+      "Ġ×ŀצ ×ķ×ķ×Ķ",
+      "ÐĽ ени",
+      "ÐĽÐµÐ½Ð¸ н",
+      "ĠTri á»ģu",
+      "ãĤ³ãĥŁ ãĥ¥",
+      "ãĤ³ãĥŁãĥ¥ ãĥĭ",
+      "ãĤ³ãĥŁãĥ¥ãĥĭ ãĤ±",
+      "ãĤ³ãĥŁãĥ¥ãĥĭãĤ± ãĥ¼ãĤ·ãĥ§ãĥ³",
+      "Ùĥ ÙĨÙĬ",
+      "ÙĥÙĨÙĬ سة",
+      "ãĤĴ ä¸Ńå¿ĥ",
+      "ãĤĴä¸Ńå¿ĥ ãģ«",
+      "ĠmiÄĻd z",
+      "ĠmiÄĻdz yn",
+      "ĠmiÄĻdzyn ar",
+      "ĠmiÄĻdzynar od",
+      "ĠmiÄĻdzynarod ow",
+      "ÙĦ ÙĨ",
+      "ÙĦÙĨ دا",
+      "بر ش",
+      "برش ÙĦÙĪÙĨ",
+      "برشÙĦÙĪÙĨ Ø©",
+      "à¸ģระ à¸ķุ",
+      "à¸ģระà¸ķุ à¹īà¸Ļ",
+      "Ġg ı",
+      "Ġgı da",
+      "à¸Ľà¸£à¸° à¸Ĺัà¸ļ",
+      "à¸Ľà¸£à¸°à¸Ĺัà¸ļ à¹ĥà¸Ī",
+      "Ġë¶Ī 구",
+      "Ġë¶Ī구 íķĺê³ł",
+      "ĠÙĨ Ø·",
+      "ĠÙĨØ· اÙĤ",
+      "ĠÐľ ожеÑĤ",
+      "Pr äs",
+      "Präs ident",
+      "ĠÑģк оÑĢ",
+      "ĠÑģкоÑĢ оÑģÑĤÑĮ",
+      "Ġ×Ķ×ij ×ķקר",
+      "еÑħ аÑĤÑĮ",
+      "Ġg ạo",
+      "Ġש×IJ ×Ļ׳×Ŀ",
+      "Ġ×ij׳ ×ķ×Ĵ",
+      "Ġ×ij׳×ķ×Ĵ ×¢",
+      "Ġо пиÑģание",
+      "Ġucz ni",
+      "Ġuczni ów",
+      "à¹Ģà¸Ń à¹ĩà¸Ļ",
+      "Ġت Ø´",
+      "Ġتش رÙĬÙĨ",
+      "Ġnh ãn",
+      "ë¹ ¨",
+      "Ġcaract ère",
+      "×¢ ׾×Ļ",
+      "×¢×ľ×Ļ ×Ļ×Ķ",
+      "楽ãģĹ ãĤģãĤĭ",
+      "ĠÑģ аÑħ",
+      "ĠÑģаÑħ аÑĢ",
+      "дÑĥм аÑĤÑĮ",
+      "ĠÐĴоз можно",
+      "ص ÙĬاÙĨ",
+      "صÙĬاÙĨ Ø©",
+      "öm ür",
+      "ส ล",
+      "สล à¹ĩ",
+      "สลà¹ĩ à¸Ń",
+      "สลà¹ĩà¸Ń à¸ķ",
+      "ë¡ ¯",
+      "Ġth ói",
+      "gr Ã¶ÃŁe",
+      "Ġksi ÄĻ",
+      "ĠksiÄĻ g",
+      "ĠÑĢ ом",
+      "ĠÑĢом ан",
+      "ÙĤ اسÙħ",
+      "×ŀ×ij ×ķ×Ĵ",
+      "×ŀ×ij×ķ×Ĵ ר×Ļ×Ŀ",
+      "bes ch",
+      "besch äft",
+      "beschäft ig",
+      "×Ķצע ×Ķ",
+      "ĠÃģ rea",
+      "ĠзаÑıв к",
+      "Ä ¹",
+      "ĠлÑİб ого",
+      "Ġ ม",
+      "Ġม à¸ģร",
+      "Ġมà¸ģร าà¸Ħม",
+      "ÑĦ из",
+      "ÑĦиз иÑĩеÑģк",
+      "ин ÑĦ",
+      "инÑĦ ек",
+      "инÑĦек ÑĨи",
+      "اÙĦ Ø·",
+      "اÙĦØ· ائÙģ",
+      "Ġкол л",
+      "Ġколл екÑĤив",
+      "ез жа",
+      "Ġس بØŃ",
+      "ĠسبØŃ Ø§ÙĨ",
+      "ĠسبØŃاÙĨ Ùĩ",
+      "sch lä",
+      "schlä ge",
+      "Ġд и",
+      "Ġди аг",
+      "Ġдиаг ноÑģÑĤ",
+      "ĠоÑĤмеÑĤ иÑĤÑĮ",
+      "Т Ь",
+      "ĠاÙĦ در",
+      "ĠاÙĦدر اسÙĬ",
+      "עצ ×ŀ",
+      "עצ×ŀ ×IJ×ķת",
+      "Ġdém arch",
+      "Ġdémarch e",
+      "Ġ×ĺ ×ķ×¢",
+      "Ġ×ĺ×ķ×¢ ף",
+      "Ġfuncion ários",
+      "á» µ",
+      "׾ ׼×IJ",
+      "׾׼×IJ ×ķר×Ķ",
+      "à¸ĭ à¹Ī",
+      "à¸ĭà¹Ī à¸Ńม",
+      "ĠÑĩ Ñĥв",
+      "ĠÑĩÑĥв ÑģÑĤво",
+      "âĸ ¼",
+      "п ÑĥÑī",
+      "пÑĥÑī ен",
+      "Ġм еÑĢ",
+      "ĠмеÑĢ оп",
+      "ĠмеÑĢоп ÑĢи",
+      "ĠмеÑĢопÑĢи ÑıÑĤиÑı",
+      "Ġu çu",
+      "Ġuçu ÅŁ",
+      "ãĤĴåĪ©çĶ¨ ãģĻãĤĭ",
+      "a ÄŁ",
+      "aģ lı",
+      "ìĺĪ ìĪł",
+      "à¹ģ ยà¹Ī",
+      "ĠاÙĦÙĥ Ùħ",
+      "ĠاÙĦÙĥÙħ بÙĬ",
+      "ĠاÙĦÙĥÙħبÙĬ ÙĪتر",
+      "ت ÙĪÙĬ",
+      "تÙĪÙĬ تر",
+      "à¹Ģà¸Ĭ ีà¹Īยว",
+      "à¹Ģà¸Ĭีà¹Īยว à¸Ĭา",
+      "à¹Ģà¸Ĭีà¹Īยวà¸Ĭา à¸į",
+      "á» Ķ",
+      "Ġhi ếm",
+      "ذا Ùĥرة",
+      "Ġ×Ķ×ŀ×Ļ ×ķ×Ĺ×ĵ",
+      "ĠìĪ ľ",
+      "ĠìĪľ ê°Ħ",
+      "ĠK ı",
+      "ĠKı sa",
+      "Ġgele ceÄŁi",
+      "пÑĢо ÑĦеÑģÑģиона",
+      "пÑĢоÑĦеÑģÑģиона л",
+      "Ġog ó",
+      "Ġogó le",
+      "ĠgÅĤ ów",
+      "ĠgÅĤów ne",
+      "ĠÑģÑĤ илÑĮ",
+      "×IJ פ׾",
+      "×IJפ׾ ×Ļק",
+      "×IJפ׾×Ļק צ×Ļ×Ķ",
+      "สม ารà¹Į",
+      "สมารà¹Į à¸Ĺ",
+      "สมารà¹Įà¸Ĺ à¹Ĥà¸Ł",
+      "สมารà¹Įà¸Ĺà¹Ĥà¸Ł à¸Ļ",
+      "Ġth ánh",
+      "ÐŁ од",
+      "ÐŁÐ¾Ð´ ÑĢоб",
+      "ÐŁÐ¾Ð´ÑĢоб нее",
+      "ĠاÙĦت ÙĪÙĨ",
+      "ĠاÙĦتÙĪÙĨ سÙĬ",
+      "Ġbah çe",
+      "à¹ģà¸ģà¹ī à¸Ľà¸±à¸įหา",
+      "é ducation",
+      "eu rop",
+      "europ ä",
+      "europä ische",
+      "ĠK si",
+      "ĠKsi ÄĻ",
+      "ĠëĦ ĺ",
+      "ĠëĦĺ ìĸ´",
+      "Ġv üc",
+      "Ġvüc ud",
+      "Ġyay g",
+      "Ġyayg ın",
+      "Ġnie kt",
+      "Ġniekt óry",
+      "Ġniektóry ch",
+      "ãģŃ ãģĩ",
+      "Ġк аж",
+      "Ġкаж еÑĤÑģÑı",
+      "к аж",
+      "каж еÑĤ",
+      "ĠاÙĦ دÙĬÙħÙĤرا",
+      "ĠاÙĦدÙĬÙħÙĤرا Ø·",
+      "ĠاÙĦدÙĬÙħÙĤراط ÙĬØ©",
+      "æŃ ©",
+      "æŃ© ãģĦãģ¦",
+      "Ġv az",
+      "Ġvaz ge",
+      "Ġvazge ç",
+      "Ġмин ималÑĮ",
+      "ĠминималÑĮ н",
+      "ãĥij ãĤ¿",
+      "ãĥijãĤ¿ ãĥ¼ãĥ³",
+      "Ġë Ĭ",
+      "ĠëĬ IJ",
+      "ĠëĬIJ ëĤĮ",
+      "ãģ¡ ãĤĩãģĨ",
+      "ãģ¡ãĤĩãģĨ ãģ©",
+      "Ġ à¸ģร",
+      "Ġà¸ģร à¸ģà¸İ",
+      "Ġà¸ģรà¸ģà¸İ าà¸Ħม",
+      "تج دÙĬد",
+      "ĠØ´ اÙħÙĦ",
+      "หลัà¸ģ à¸IJาà¸Ļ",
+      "ĠмаÑĢ ÑĪ",
+      "ĠмаÑĢÑĪ ÑĢÑĥÑĤ",
+      "Ġv ÃŃt",
+      "ĠvÃŃt ima",
+      "Ġquiz á",
+      "ay gı",
+      "×ĵ×ijר ×Ļ×ķ",
+      "Ġиз д",
+      "Ġизд ели",
+      "Ġиздели Ñı",
+      "п ла",
+      "пла Ñĩ",
+      "плаÑĩ ива",
+      "ä»» ãģĽ",
+      "Ġéquip é",
+      "ä¹ħ ãģĹãģ",
+      "ä¹ħãģĹãģ ¶",
+      "ä¹ħãģĹãģ¶ ãĤĬ",
+      "Ġк аÑĤ",
+      "ĠкаÑĤ ал",
+      "ĠкаÑĤал ог",
+      "ส à¹īม",
+      "ĠÑĢ ей",
+      "ĠÑĢей ÑĤ",
+      "ĠÑĢейÑĤ инг",
+      "Ġth uyá»ģn",
+      "ĠاÙĦÙħ ÙĤدس",
+      "esp ère",
+      "ãģ«åħ¥ ãģ£ãģŁ",
+      "หมาย à¹Ģลà¸Ĥ",
+      "ת×Ĺ×ķש ת",
+      "à¸Ļ à¹Īะ",
+      "Ġpe ÅĤ",
+      "ĠpeÅĤ ne",
+      "Ġpé rd",
+      "Ġpérd ida",
+      "หม วà¸Ķ",
+      "หมวà¸Ķ หมูà¹Ī",
+      "иÑĩеÑģк ÑĥÑİ",
+      "çµĤ ãĤı",
+      "çµĤãĤı ãģ£ãģŁ",
+      "Ġ×Ĵ ×ķ×Ĵ׾",
+      "à¸Ĺำ à¸Ħวาม",
+      "à¸Ĺำà¸Ħวาม สะà¸Ńาà¸Ķ",
+      "Hot éis",
+      "Ġз аÑĢ",
+      "ĠзаÑĢ егиÑģÑĤ",
+      "ĠзаÑĢегиÑģÑĤ ÑĢи",
+      "ĠзаÑĢегиÑģÑĤÑĢи ÑĢова",
+      "ĠÑģ обÑĭÑĤи",
+      "ĠÑģобÑĭÑĤи Ñı",
+      "Ġ×ĸ ׼×IJ",
+      "ÙħÙĨظ ÙĪÙħØ©",
+      "Ġ×Ķ×ŀ צ",
+      "Ġ×Ķ×ŀצ ×Ļ×IJ×ķת",
+      "Ùħ ÙĥÙĪÙĨ",
+      "ÙħÙĥÙĪÙĨ ات",
+      "ä¸ĬãģĮ ãĤĭ",
+      "Ġm ÄĻ",
+      "ĠmÄĻ sk",
+      "หรืà¸Ń à¹Ģà¸Ľà¸¥à¹Īา",
+      "ëĤ ®",
+      "Ġnok tas",
+      "Ġnoktas ı",
+      "ĠболÑĮÑĪ им",
+      "ĠлÑĥÑĩ ÑĪиÑħ",
+      "Ø´Ùĩ ÙĬد",
+      "à¸Ńำ à¸Ļ",
+      "à¸Ńำà¸Ļ วย",
+      "à¸Ńำà¸Ļวย à¸Ħวาม",
+      "à¸Ńำà¸Ļวยà¸Ħวาม สะà¸Ķวà¸ģ",
+      "Ġе в",
+      "Ġев ÑĢ",
+      "ĠевÑĢ оп",
+      "ĠевÑĢоп ей",
+      "à¸ī าย",
+      "ìĦ Ń",
+      "Ùħ Ùģا",
+      "ÙħÙģا ÙĪض",
+      "ÙħÙģاÙĪض ات",
+      "ë¹ Į",
+      "赤 ãģ¡ãĤĥãĤĵ",
+      "ĠÑĥдал оÑģÑĮ",
+      "ĠÐ¥ оÑĤ",
+      "ĠХоÑĤ Ñı",
+      "przedsiÄĻbior c",
+      "ĠH ôm",
+      "íķĺìĺĢ ìĬµëĭĪëĭ¤",
+      "Ġн аг",
+      "Ġнаг ÑĢÑĥз",
+      "ĠнагÑĢÑĥз к",
+      "Ġ×ij×Ļ׳ ׾×IJ×ķ×ŀ×Ļ",
+      "Ġê°ĢëĬ¥ íķľ",
+      "ĠH ữu",
+      "à¸Ń ุà¸Ķ",
+      "à¸Ńุà¸Ķ ม",
+      "ת ×ķפ",
+      "ת×ķפ ×¢×Ķ",
+      "Ġmi ÅĤo",
+      "ĠmiÅĤo ÅĽci",
+      "ksi Äħż",
+      "ksiÄħż ka",
+      "ĠاÙĦÙĦ عبة",
+      "à¸ī าà¸ģ",
+      "สะ สม",
+      "×ŀ תר",
+      "×ŀתר ×Ĺש",
+      "Ġlég ère",
+      "Ġ׾צ פ",
+      "Ġ׾צפ ×Ļ×Ķ",
+      "ĠиÑģÑĤоÑĢ иÑı",
+      "Ġ ãĥĪãĥ©",
+      "ĠãĥĪãĥ© ãĥĥãĤ¯",
+      "ĠãĥĪãĥ©ãĥĥãĤ¯ ãĥIJãĥĥãĤ¯",
+      "Ġк а",
+      "Ġка ÑĦе",
+      "×ŀס×ŀ ×ļ",
+      "Ġc üm",
+      "Ġcüm le",
+      "à¹Ģà¸Ħลืà¹Īà¸Ńà¸Ļ à¹Ħหว",
+      "ãģĬ ãģĿ",
+      "ãģĬãģĿ ãĤīãģı",
+      "ìŀIJ ëıĻ",
+      "ìŀIJëıĻ ì°¨",
+      "à¸Ńั à¸ķ",
+      "à¸Ńัà¸ķ à¹Ĥà¸Ļ",
+      "à¸Ńัà¸ķà¹Ĥà¸Ļ มั",
+      "à¸Ńัà¸ķà¹Ĥà¸Ļมั à¸ķิ",
+      "ĠÅŁ ik",
+      "ĠÅŁik ay",
+      "ĠÅŁikay et",
+      "extr ême",
+      "kr ä",
+      "krä fte",
+      "ëĤ Ļ",
+      "íķ ij",
+      "ì² Ļ",
+      "íĺ Ī",
+      "ì° į",
+      "âĻ ¡",
+      "ìŀ Ķ",
+      "ë¢ °",
+      "íĿ Ķ",
+      "íĿ IJ",
+      "âĩ Ĵ",
+      "ë§ Ľ",
+      "ìĬ Ī",
+      "á» Ĵ",
+      "ìĺ µ",
+      "âĹ İ",
+      "í Ĥ¨",
+      "ê¿ Ī",
+      "ìĪ ¨",
+      "ìĽ ¨",
+      "ë§ ¥",
+      "ï½ Ģ",
+      "ï¼ ª",
+      "Ạ¨",
+      "ãħ İ",
+      "Ñ Ĺ",
+      "ìĦ ¬",
+      "ì¹ ¼",
+      "ï¼ ¶",
+      "ìĽ ł",
+      "ëŁ ´",
+      "Å ĥ",
+      "ëĤ ¼",
+      "ëĭ IJ",
+      "âĢ ¹",
+      "ë¦ Ń",
+      "ì§ IJ",
+      "âĢ ¤",
+      "Ã ħ",
+      "ëľ ¨",
+      "íĦ ¸",
+      "íľ ĺ",
+      "ê² ģ",
+      "ë´ ħ",
+      "Ã ĺ",
+      "ëŃ Ķ",
+      "ëĺ ij",
+      "âĹ ĩ",
+      "ìĹ ĺ",
+      "ï» ´",
+      "ë§ ¹",
+      "ï¾ Ŀ",
+      "ìĬ ·",
+      "íĥ ķ",
+      "ï¼ ł",
+      "ì» ´",
+      "ëł Į",
+      "ì½ ľ",
+      "ï» ¹",
+      "ãħ ł",
+      "ì¡ ¸",
+      "ëħ ¹",
+      "âĤ º",
+      "âĸ ¶",
+      "íĥ IJ",
+      "êµ ´",
+      "íij ¸",
+      "Ñ Ķ",
+      "íĶ ½",
+      "Ð ħ",
+      "ë° ¤",
+      "Ô ģ",
+      "ì² ¨",
+      "ì¶ ĺ",
+      "ë² Ĺ",
+      "ë© ¸",
+      "ï¼ »",
+      "ï¼ ½",
+      "ï¼ ·",
+      "ì° Į",
+      "Ã Ĵ",
+      "íı ´",
+      "ìĵ ¸",
+      "ì´ Į",
+      "ëģ Ķ",
+      "ëĶ ©",
+      "ëĩ Į",
+      "ë© Ģ",
+      "ë² ¨",
+      "ï¼ µ",
+      "ë§ ¡",
+      "ëĭ «",
+      "ภ¿",
+      "ãģ ±",
+      "ìĩ ¼",
+      "ìº ł",
+      "ë® ¤",
+      "ê± ±",
+      "ì» ¬",
+      "âĦ ĥ",
+      "ëĶ ±",
+      "ëĥ Ī",
+      "ìĭ ±",
+      "íĻ Ī",
+      "ëŀ IJ",
+      "ìħ Ģ",
+      "ìł ł",
+      "Ð Ĩ",
+      "ëł ī",
+      "ï½ ħ",
+      "ï½ ı",
+      "íĻ Ģ",
+      "ëĽ °",
+      "á» ®",
+      "í Ĥ¹",
+      "ê½ ĥ",
+      "ï» ¤",
+      "ïº Ķ",
+      "êº ¼",
+      "ìķ ī",
+      "âĻ ¦",
+      "ï½ ģ",
+      "ìĵ ´",
+      "ãĢ ī",
+      "ì° ®",
+      "ì¤ ĺ",
+      "á» ª",
+      "ëģ Ħ",
+      "ëIJ ¨",
+      "ìķ Į",
+      "íĿ ĺ",
+      "íħ IJ",
+      "ãĢ Ī",
+      "ê² ª",
+      "ëĭ ¥",
+      "ê² ¼",
+      "á» Į",
+      "ë§ ¨",
+      "ëģ Ĭ",
+      "ë² ¤",
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+      "ãģ ī",
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+      "Õ ´",
+      "ï¬ Ģ",
+      "âľ ´",
+      "ðŁ¤ Ń",
+      "ðŁij Ĩ",
+      "⼠Ķ",
+      "ê· ĵ",
+      "ìĮ Į",
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+      "Û Ķ",
+      "ðŁ§ ¡",
+      "ðŁĺ ĵ",
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+      "âı °",
+      "ê² ľ",
+      "ëĭ ³",
+      "ëİ ħ",
+      "ë° Ī",
+      "ï® IJ",
+      "ðŁı ¡",
+      "âĨ ª",
+      "âĵ Ķ",
+      "âľ Ĭ",
+      "Ï ²",
+      "Ü IJ",
+      "ðŁĩ ³",
+      "Ö Ĥ",
+      "âľ ı",
+      "ìĸ Ĺ",
+      "ì« Ļ",
+      "ðŁĺ ²",
+      "Ä Ń",
+      "âĻ Ń",
+      "âĶ ı",
+      "âĹ Į",
+      "ðŁĺ ¯",
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+      "Ê ģ",
+      "ठŁ",
+      "á¹ ģ",
+      "á¼ °",
+      "á¿ Ĩ",
+      "â «",
+      "â« ¸",
+      "ëį «",
+      "ì³ ĩ",
+      "ì¼ ¤",
+      "íĽ ¨",
+      "ðŁĴ Ł",
+      "Ê Ģ",
+      "Ê ³",
+      "ëĵ IJ",
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+      "âĿ ĩ",
+      "Ç Ģ",
+      "Ç Ķ",
+      "É ´",
+      "âĺ ļ",
+      "âĺ ľ",
+      "ê¶ Ĥ",
+      "ì« Ĵ",
+      "ì± Ī",
+      "ðŁĩ ¨",
+      "ðŁİ ¥",
+      "ðŁĵ Ŀ",
+      "Ä §",
+      "ðĿ ijIJ",
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+      "ï¹ ı",
+      "Ë ĭ",
+      "ðŁ¥ º",
+      "âĸ ¨",
+      "íĻ ĭ",
+      "âĪ ħ",
+      "ëģ Ļ",
+      "ëŀ ł",
+      "ìĨ ¥",
+      "âĢ ĸ",
+      "ðŁ¤ ĺ",
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+      "áµ ķ",
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+      "ïº ļ",
+      "ï» Ĥ",
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+      "ìĪ ¯",
+      "ëĨ ĭ",
+      "âľ ¯",
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+      "Ú ¨",
+      "âľ Ń",
+      "ê² ħ",
+      "íĮ °",
+      "íľ Ļ",
+      "ðŁĮ Ĭ",
+      "ðŁİ ĵ",
+      "ðŁĺ Ļ",
+      "Ë ĥ",
+      "ðŁĴ ģ",
+      "ðŁij İ",
+      "âĺ ¹",
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+      "ðŁĴ »",
+      "ëĤ µ",
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+      "ï» ¯",
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+      "Ï ķ",
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+      "ïº Ĩ",
+      "Ê º",
+      "Ó §",
+      "âĨ ł",
+      "ëĥ ĩ",
+      "ìİ Ī",
+      "ìŁ ¤",
+      "ï± ¢",
+      "âķ ¬",
+      "âĺ ł",
+      "ðŁİ Ĭ",
+      "ãį į",
+      "ãİ İ",
+      "âĺ °",
+      "âľ ĥ",
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+      "ë¯ Ī",
+      "ë¹ ¤",
+      "ìı Ń",
+      "ðĿij ¢",
+      "ðŁIJ ¾",
+      "Å ĭ",
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+      "áĥ ¡",
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+      "Å Ĩ",
+      "Ñ IJ",
+      "ìĥ Ľ",
+      "ìĺ Į",
+      "ì± ¤",
+      "íħ ģ",
+      "íļ ĥ",
+      "ï³ Ĭ",
+      "ðĿij Ķ",
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+      "âĭ °",
+      "ðŁĺ ¨",
+      "âĤ ©",
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+      "Ḡį",
+      "á» ´",
+      "âĨ ĺ",
+      "âĺ ¯",
+      "ãħ ı",
+      "ìł ¬",
+      "âĻ Ķ",
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+      "ðŁĺ ł",
+      "ðŁĻ Ĭ",
+      "à® ľ",
+      "á¹ ħ",
+      "âĹ IJ",
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+      "ìĥ ħ",
+      "ðĿij ł",
+      "Æ ¢",
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+      "ðŁĴ Ń",
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+      "ðŁIJ °",
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+      "Ü ĵ",
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+      "ðĿij Ŀ",
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+      "ठĹ",
+      "áIJ ī",
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+      "ì¶ §",
+      "ï³ ī",
+      "ï» ħ",
+      "ðĿIJ ŀ",
+      "ठ¶",
+      "ðŁĵ ¢",
+      "ðŁį ĭ",
+      "ðŁĴ ħ",
+      "ï¾ ķ",
+      "⬠Ĩ",
+      "âĪ µ",
+      "ðŁ¤ ij",
+      "áĥ £",
+      "Æ Ħ",
+      "Ñ ¹",
+      "á¼ Ķ",
+      "ê° ł",
+      "ê´ Į",
+      "ê· IJ",
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+      "ì± ĺ",
+      "ï® Ń",
+      "ïº ¹",
+      "ïº ¾",
+      "âľ Ĺ",
+      "âĿ ¦",
+      "ðŁij ¦",
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+      "Ù ²",
+      "á½ ´",
+      "âĪ ı",
+      "âľ ®",
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+      "ïº ŀ",
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+      "ðŁĩ Ń",
+      "Ë Ĥ",
+      "ðŁį ij",
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+      "ðĿij ļ",
+      "ðŁĵ ¦",
+      "ðŁĶ İ",
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+      "ëĢ Ŀ",
+      "ðŁį Ĭ",
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+      "ì« Ģ",
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+      "ðĿIJ ¢",
+      "ðŁļ ¨",
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+      "Õ ¯",
+      "âı ©",
+      "ðĿij £",
+      "ðŁĴ £",
+      "Å ĺ",
+      "ॠIJ",
+      "âģ ĥ",
+      "âĮ ĺ",
+      "ê» Į",
+      "ìĮ Ķ",
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+      "ठľ",
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+      "ìIJ Ī",
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+      "ðŁĺ ¤",
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+      "ठ¡",
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+      "ìķ ´",
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+      "âĹ ¼",
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+      "ðŁĽ į",
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+      "â ĵĺ",
+      "ðŁ ĴĮ",
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+      "ïŃ ĭ",
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+      "Ï ³",
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+      "áŀ Ł",
+      "ðŁį º",
+      "áŀ ļ",
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+      "ðŁIJ ·",
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+      "ëĪ Ĺ",
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+      "íį ħ",
+      "ï· ²",
+      "ðŁĮ ı",
+      "ðŁį «",
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+      "ðŁİ °",
+      "ðŁij °",
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+      "âĹ ł",
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+      "á ´Ģ",
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+      "ðŁı ¥",
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+      "âĹ ½",
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+      "ðŁĴ ®",
+      "ຠ°",
+      "ðŁĶ ľ",
+      "ðŁį Ħ",
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+      "Ê ¾",
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+      "âĹ ħ",
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+      "ê¿ ©",
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+      "ðŁı ģ",
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+      "ìĹ ·",
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+      "íĹ ¹",
+      "íľ ¨",
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+      "ðŁı µ",
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+      "âķ ¥",
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+      "ठ¥",
+      "áī µ",
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+      "âĿ ±",
+      "ëī ł",
+      "ëİ ł",
+      "ëı Ľ",
+      "ë¿ ħ",
+      "ìĶ ¸",
+      "íij ¯",
+      "íŀ ī",
+      "íŀ Ľ",
+      "ï§ Ħ",
+      "ïŃ ĺ",
+      "ïº ¦",
+      "ï» ¸",
+      "ðĿij Ĥ",
+      "ðĿij ı",
+      "Ï ij",
+      "Ú ł",
+      "áĢ Ķ",
+      "áŀ Ķ",
+      "á¹ ¢",
+      "ëĦ ¸",
+      "ðĿIJ ¨",
+      "ðŁĩ ´",
+      "Õ °",
+      "ðŁij ł",
+      "ðŁį Ĩ",
+      "ðŁı Ģ",
+      "ðŁ ijIJ",
+      "ðŁį ĩ",
+      "ðŁIJ £",
+      "áĪ Ń",
+      "Ü ª",
+      "ðŁ ĮĢ",
+      "áŀ ĺ",
+      "âĩ Ħ",
+      "ðĿIJ Ģ",
+      "Ê Ļ",
+      "âĶ ¼",
+      "ðŁı ¿",
+      "Æ ·",
+      "È ł",
+      "Ñ ½",
+      "âĤ ¨",
+      "ê´ Ń",
+      "ê¹ »",
+      "ëĶ ¨",
+      "ìĪ Ģ",
+      "ì¾ °",
+      "íĨ Ī",
+      "ï® §",
+      "ï¯ ½",
+      "ðŁĶ ħ",
+      "ðŁĶ ®",
+      "Å ¢",
+      "Ê °",
+      "Ñ ¸",
+      "ठ£",
+      "âĬ Ĺ",
+      "ëª Ħ",
+      "ï¹ ·",
+      "ïº ħ",
+      "ðĿIJ µ",
+      "ðŁĮ ¶",
+      "ðŁĵ °",
+      "ðŁĶ ·",
+      "ðŁĸ Ĵ",
+      "ðŁ¤ ²",
+      "ëī ©",
+      "ðŁİ Ĩ",
+      "ðŁ§ IJ",
+      "ðŁį ®",
+      "âĨ º",
+      "âĿ ¢",
+      "ðŁij ª",
+      "ðŁij ±",
+      "âĨ ¡",
+      "áŀ ı",
+      "Ú ķ",
+      "ðŁį ¹",
+      "ðŁĴ Ģ",
+      "Ë ®",
+      "Ó ¨",
+      "Ö ħ",
+      "ठĩ",
+      "âĤ ¡",
+      "âĪ ķ",
+      "âĺ ī",
+      "ê¹ ¼",
+      "ê¼ IJ",
+      "ì½ ¸",
+      "ðĿIJ ¬",
+      "ðŁı ħ",
+      "ðŁij Ļ",
+      "ðŁĴ ī",
+      "ðŁ¤ Ļ",
+      "È ĺ",
+      "É ³",
+      "É ¹",
+      "Ù º",
+      "áĢ Ħ",
+      "á¿ ³",
+      "âļ ĺ",
+      "âĿ Ĩ",
+      "ëĨ ī",
+      "ìĸ į",
+      "ìĺ ĩ",
+      "ì¥ ĺ",
+      "íĸ ħ",
+      "íĻ ij",
+      "ï® Ĭ",
+      "ï¿ Ń",
+      "ðĿĴ IJ",
+      "ðĿĹ ¢",
+      "ðŁĶ ĸ",
+      "ðŁĶ ¨",
+      "ðŁļ ij",
+      "ðŁļ ²",
+      "Æ ¸",
+      "âĹ ¥",
+      "ðĿIJ Ń",
+      "ðŁį ½",
+      "âĹ ij",
+      "âĵ ĩ",
+      "ðŁĶ ±",
+      "âľ ¼",
+      "ï¹ ĥ",
+      "âķ ±",
+      "ãĢ Ĺ",
+      "ðŁı ĭ",
+      "ðŁļ ´",
+      "ðĿIJ ®",
+      "Ä ļ",
+      "Õ ı",
+      "Ä ¶",
+      "áĥ ij",
+      "á¹ ¬",
+      "Ä Ī",
+      "Ä Ĵ",
+      "Ò °",
+      "Ó ķ",
+      "â IJ",
+      "âIJ £",
+      "âĹ ¢",
+      "âļ Ļ",
+      "ãħ Ĺ",
+      "ê° ¬",
+      "ê³ ª",
+      "ê» Ģ",
+      "ëĦ ´",
+      "ëİ ģ",
+      "ëĿ Ķ",
+      "ë¬ ½",
+      "ëŃ į",
+      "ìĩ ³",
+      "ì° ¹",
+      "íĮ ¹",
+      "íŀ Ŀ",
+      "ï® ĭ",
+      "ï ¶Ī",
+      "ðĿĴ Ĥ",
+      "ðŁ¥ Ģ",
+      "ðŁ¦ ħ",
+      "Ê ĺ",
+      "á¼ ij",
+      "âģ İ",
+      "ðŁį ŀ",
+      "âĨ ĸ",
+      "âĨ Ļ",
+      "ðŁİ ĥ",
+      "âĦ ¡",
+      "âĭ ±",
+      "ðŁĶ į",
+      "ಠ¨",
+      "áµ ĥ",
+      "âĶ «",
+      "⦠¿",
+      "ðŁĩ »",
+      "Æ ¤",
+      "Ò ı",
+      "Ò ·",
+      "Û ī",
+      "à® ķ",
+      "Ḡ³",
+      "ï¬ ±",
+      "ðŁĨ Ķ",
+      "Ú Ń",
+      "Û ¦",
+      "áħ ¡",
+      "âĦ ¹",
+      "ê¿ İ",
+      "ëķ Ķ",
+      "ë¼ ī",
+      "ìļ §",
+      "ì² µ",
+      "ì´ ¨",
+      "íĬ Ī",
+      "íĸ IJ",
+      "ðĿĹ ĺ",
+      "ðŁĩ ¿",
+      "ðŁİ ĸ",
+      "ðŁij ħ",
+      "ðŁ ĵĺ",
+      "ðŁļ Ļ",
+      "ðŁĽ µ",
+      "ච½",
+      "⼠µ",
+      "ðĿIJ ³",
+      "ðĿIJ ¸",
+      "âļ Ķ",
+      "ðŁij Ń",
+      "Ó ij",
+      "âĶ ¯",
+      "ðŁħ ¿",
+      "ðŁĺ ¹",
+      "ï¿ «",
+      "â¼ ¤",
+      "ðŁĴ ĩ",
+      "ðŁĵ İ",
+      "ðŁĸ ĭ",
+      "ঠ¸",
+      "ðĿIJ į",
+      "Ä ²",
+      "Ï ĭ",
+      "Ñ ¬",
+      "Ú ¬",
+      "Ü Ĵ",
+      "á´ ¬",
+      "ï¨ Ħ",
+      "É £",
+      "Ë ij",
+      "Ï µ",
+      "Ò Ŀ",
+      "Û ¥",
+      "Ü ł",
+      "๠Ľ",
+      "áĥ ķ",
+      "áĬ ķ",
+      "á¾ ¶",
+      "âĤ ·",
+      "âĩ ¾",
+      "âķ ©",
+      "âĸ IJ",
+      "âĺ ª",
+      "âĺ ®",
+      "âĿ ļ",
+      "âĿ Ń",
+      "âŀ ±",
+      "âµ İ",
+      "ãı Ĭ",
+      "ë© ĵ",
+      "ìĹ ¾",
+      "ìª Ħ",
+      "íĵ Į",
+      "íķ ¼",
+      "ïŃ ¬",
+      "ðĿij Ĩ",
+      "ðĿij ŀ",
+      "ðĿĸ Ĭ",
+      "ðŁİ ¸",
+      "ðŁı Ħ",
+      "ðŁij µ",
+      "ðŁĴ ł",
+      "ðŁĶ ĺ",
+      "ðŁ¥ Ĥ",
+      "Å ª",
+      "à· ĥ",
+      "á´ ¼",
+      "âĬ °",
+      "ë³ ı",
+      "ë´ £",
+      "ï¥ ľ",
+      "ðŁĵ Ī",
+      "ðŁķ ¯",
+      "ðŁ§ Ģ",
+      "âĻ IJ",
+      "ðŁĨ Ĺ",
+      "ðŁĵ ķ",
+      "ðŁ§ ģ",
+      "Ü «",
+      "âĿ IJ",
+      "Õ ķ",
+      "འķ",
+      "âŀ Ŀ",
+      "ঠķ",
+      "ðĿIJ ¶",
+      "É ¢",
+      "Î Ħ",
+      "áĨ ¢",
+      "âĤ ±",
+      "Õ į",
+      "à¡ ķ",
+      "á´ °",
+      "Ḡ©",
+      "⼠·",
+      "âĿ ®",
+      "ê¡ ĵ",
+      "ëı ¤",
+      "ëĹ IJ",
+      "ëµ Į",
+      "ìij Ī",
+      "íı ¿",
+      "íĹ µ",
+      "ðĿIJ İ",
+      "ðŁĨ ĺ",
+      "ðŁı Ł",
+      "É ¥",
+      "Õ »",
+      "à¡ Ķ",
+      "ठĸ",
+      "á´ ¸",
+      "âİ Ļ",
+      "âİ ¥",
+      "âı ³",
+      "ëģ ķ",
+      "ëĬ ī",
+      "ì¡ į",
+      "ì¹ ¡",
+      "ï¦ ¶",
+      "ï¬ Ł",
+      "ï® «",
+      "ï® ¯",
+      "ï± ĥ",
+      "ï ·»",
+      "ïº µ",
+      "ðĿĹ Ķ",
+      "ðĿĹ ¡",
+      "ðŁİ ¨",
+      "ðŁĶ Ĵ",
+      "Ú Ľ",
+      "ठ§",
+      "âŀ ¹",
+      "áĢ Ģ",
+      "ðŁį ħ",
+      "âĹ ¤",
+      "ठł",
+      "ðŁIJ ¥",
+      "áĥ Ĵ",
+      "ðŁı Ŀ",
+      "ðŁį ¼",
+      "ãĮ §",
+      "âĿ Ľ",
+      "ðŁIJ Ī",
+      "ঠ¯",
+      "áĢ ŀ",
+      "ãĢ ĸ",
+      "áŀ Ļ",
+      "ঠª",
+      "Õ Ĩ",
+      "âĬ Ĩ",
+      "âľ ¾",
+      "ðŁIJ Ĺ",
+      "ï¹ ¿",
+      "Ä ¦",
+      "Ü Ł",
+      "ಠł",
+      "ಠ¥",
+      "áŀ ī",
+      "á´ ¥",
+      "á´ ©",
+      "á½ Ģ",
+      "á½ ¡",
+      "âĨ ķ",
+      "âŀ ¯",
+      "ê¡ ij",
+      "ëij £",
+      "ë± Į",
+      "ìĪ ij",
+      "ìľ Ķ",
+      "ìŀ ½",
+      "ì¨ į",
+      "ðĿij Ģ",
+      "ðŁĮ Į",
+      "ðŁį ¦",
+      "ðŁį ©",
+      "ðŁIJ ļ",
+      "ðŁĵ Ĵ",
+      "ðŁĵ ¹",
+      "ðŁ¥ ij",
+      "Ä ĭ",
+      "Ë Ĺ",
+      "Ñ «",
+      "Õ ¢",
+      "Ú °",
+      "â ĮĢ",
+      "âĹ Ĥ",
+      "âĹ £",
+      "âľ Ľ",
+      "âĿ Ĵ",
+      "âĿ ĺ",
+      "âŀ Ļ",
+      "âŀ ²",
+      "ãİ į",
+      "ê¡ IJ",
+      "ëŀ ĸ",
+      "ìĬ Ŀ",
+      "ìĽ ¤",
+      "ì¡ ĭ",
+      "ì¨ °",
+      "íĹ Ļ",
+      "ï¥ ¸",
+      "ï³ į",
+      "ï» İ",
+      "ðĿij ĵ",
+      "ðŁĵ Ĭ",
+      "ðŁļ ¼",
+      "ï¦ ģ",
+      "ðĿķ Ĵ",
+      "ðŁ ijľ",
+      "ðŁij ¿",
+      "ðŁĩ ½",
+      "à· Ħ",
+      "âĸ ´",
+      "ãį ī",
+      "âĬ ĩ",
+      "ðŁ§ ¸",
+      "Ú ¡",
+      "â¾ ĥ",
+      "ðŁĹ »",
+      "âĵ ij",
+      "ðŁ¤ ¸",
+      "ðŁ¤ ¯",
+      "êĴ °",
+      "ðĿIJ ĵ",
+      "âĶ ´",
+      "êĴ ±",
+      "áĢ ĺ",
+      "â ĽĦ",
+      "ï¹ ¹",
+      "Ó Ķ",
+      "áĥ ±",
+      "Ü ¡",
+      "ß ŀ",
+      "âĻ ı",
+      "âľ ¸",
+      "ìij ¨",
+      "ðĿIJ Ŀ",
+      "ðĿIJ ¥",
+      "ðŁį ī",
+      "ðŁij ¼",
+      "ðŁ¥ Ŀ",
+      "Æ Ķ",
+      "Ý ¬",
+      "ठ«",
+      "ຠļ",
+      "á´ ´",
+      "á½ ĸ",
+      "âĤ ¶",
+      "âİ ¢",
+      "âĿ ħ",
+      "⣠«",
+      "ãİ Ľ",
+      "ë® ¨",
+      "ëº Į",
+      "ë¼ ĺ",
+      "ìĨ Ŀ",
+      "ìľ ³",
+      "ìŀ Į",
+      "ì£ Ĺ",
+      "ìª ĺ",
+      "ì» ¹",
+      "ï· ¼",
+      "ïº Ĥ",
+      "ðĿIJ ´",
+      "ðĿIJ ¼",
+      "ðŁĮ ļ",
+      "ðŁı «",
+      "ðŁĴ ¤",
+      "ðŁĴ ¶",
+      "ðŁĴ ¼",
+      "Ê ķ",
+      "Ê ½",
+      "â² Ł",
+      "ãī ł",
+      "ê¡ Ĵ",
+      "ëľ Ģ",
+      "ìĥ ¾",
+      "ì¸ ¤",
+      "ï¥ ģ",
+      "ðĿļ Ĭ",
+      "ðŁļ ĥ",
+      "âŀ Ľ",
+      "ìħ ´",
+      "áĦ ĭ",
+      "âĩ Ĺ",
+      "ï§ ·",
+      "âĺ ĸ",
+      "ðŁIJ ¦",
+      "⸠ľ",
+      "ðŁĴ ´",
+      "ðŁ¤ ļ",
+      "ãĬ Ĺ",
+      "âĮ Ľ",
+      "áĪ Ľ",
+      "༠º",
+      "â½ ī",
+      "ðŁı ¢",
+      "âĵ ŀ",
+      "âĺ ½",
+      "ãĢ Ļ",
+      "ðŁ¤ ®",
+      "Å IJ",
+      "áĥ ¬",
+      "ðĿĹ »",
+      "ðŁį ĸ",
+      "Æ Ĭ",
+      "Ê Ł",
+      "ß ĭ",
+      "ठĭ",
+      "áµ Ķ",
+      "á¿ ĥ",
+      "âĦ ī",
+      "âĮ ĭ",
+      "âı ²",
+      "âĵ Ī",
+      "âĵ ¢",
+      "âķ Ķ",
+      "âļ ij",
+      "âĿ ĭ",
+      "âĿ İ",
+      "â µľ",
+      "âµ £",
+      "ëĴ Ī",
+      "ëľ ģ",
+      "ë¶ ĩ",
+      "ìį »",
+      "ìĺ Ń",
+      "ì§ ¢",
+      "íĹ Ģ",
+      "ï§ Ĭ",
+      "ï ¬¸",
+      "ï± ¡",
+      "ðĿIJ º",
+      "ðĿij §",
+      "ðĿĺ ¦",
+      "ðŁĵ ¥",
+      "ðŁĺ Ł",
+      "ðŁ¥ IJ",
+      "Ä ĸ",
+      "É ¨",
+      "áĢ IJ",
+      "áĥ ĵ",
+      "Ạĵ",
+      "á¼ ¶",
+      "á½ Ħ",
+      "âĤ ¤",
+      "âĮ ľ",
+      "âĮ Ł",
+      "âİ ł",
+      "⼠¸",
+      "âµ į",
+      "âµ ı",
+      "âµ ĵ",
+      "ãĢ ĺ",
+      "ë ·¸",
+      "íħ ¼",
+      "ï¦ Į",
+      "ïŃ Ħ",
+      "ïŃ İ",
+      "ðĿĻ ļ",
+      "ðĿļ ĺ",
+      "༠ĵ",
+      "ëŃ ħ",
+      "áIJ Ľ",
+      "ãİ ¾",
+      "ï¨ Ģ",
+      "ðŁĹ ½",
+      "âĻ ŀ",
+      "Ë ĸ",
+      "âĹ ŀ",
+      "ðŁ¤ «",
+      "ðŁĺ Ĺ",
+      "ï½ ¦",
+      "ðŁ¤ ¢",
+      "âģ ĩ",
+      "ãĢ µ",
+      "ðŁį Ķ",
+      "áĬ ł",
+      "ðŁĺ ¼",
+      "ðĿĹ ®",
+      "ðŁIJ ³",
+      "ðĿIJ ĭ",
+      "ðŁĨ ļ",
+      "ðŁĶ Ľ",
+      "Ñ »",
+      "Ü ¨",
+      "à® ²",
+      "âľ ŀ",
+      "âµ Ļ",
+      "êµ £",
+      "ì¸ ¨",
+      "ðĿ IJľ",
+      "ðĿĺ °",
+      "ðŁĶ ½",
+      "Ç »",
+      "Ç ¿",
+      "Ê ĩ",
+      "Î IJ",
+      "Ð Ģ",
+      "Ñ ¡",
+      "Ñ ²",
+      "Ò Ĵ",
+      "Ù ¶",
+      "ß ķ",
+      "ච±",
+      "áIJ ģ",
+      "âģ ŀ",
+      "âĸ §",
+      "⼠Ī",
+      "âľ ľ",
+      "âľ ¹",
+      "⣠¹",
+      "⤠ĩ",
+      "ê² Ĭ",
+      "ê¾ ľ",
+      "ë¯ IJ",
+      "ë³ IJ",
+      "ìħ ©",
+      "ìIJ ¬",
+      "ìij ¹",
+      "ï¤ Ķ",
+      "ï¦ ļ",
+      "ï¬ ł",
+      "ïŃ Ķ",
+      "ïº ¶",
+      "ðĿĴ ı",
+      "ðĿĸ Ĩ",
+      "ðĿĹ ¶",
+      "ðŁı Ĥ",
+      "ðŁIJ ½",
+      "ðŁĴ ©",
+      "ðŁĵ ½",
+      "ðŁĹ ¨",
+      "ðŁĹ º",
+      "ðŁĺ ¸",
+      "ðŁ¥ §",
+      "Å Ĺ",
+      "Ê İ",
+      "Ò Ļ",
+      "× ²",
+      "ठĪ",
+      "á¼ ´",
+      "á¿ ij",
+      "âµ ī",
+      "ãħ ĵ",
+      "ì½ ´",
+      "ðĿĸ ĵ",
+      "ðŁĵ Ĺ",
+      "ðŁĶ ª",
+      "ðŁĸ į",
+      "Ï Ĵ",
+      "ðŁij ¬",
+      "áĥ Ļ",
+      "âĨ ¬",
+      "âĶ ¤",
+      "⼠¹",
+      "âĻ Ł",
+      "ðŁļ ¶",
+      "ðŁij ¾",
+      "âĪ ĭ",
+      "ðŁIJ ¯",
+      "༠İ",
+      "âľ ·",
+      "ï¨ Ļ",
+      "âĶ »",
+      "ðŁij ¹",
+      "áĦ ī",
+      "ຠª",
+      "â¾ ı",
+      "â½ ħ",
+      "ãİ ĸ",
+      "Ñ ´",
+      "Õ ®",
+      "Ú ¼",
+      "áĢ ķ",
+      "áĨ ¼",
+      "ëŃ ı",
+      "ðŁIJ ¸",
+      "ðŁļ £",
+      "Æ Ŀ",
+      "Ô »",
+      "áĥ ¢",
+      "ðŁį ¯",
+      "É ¦",
+      "Õ ¦",
+      "âĻ ĭ",
+      "ï¬ «",
+      "ðĿĹ ¦",
+      "Ç ļ",
+      "É ±",
+      "ठī",
+      "á´ Ħ",
+      "âĻ ĵ",
+      "⼠°",
+      "⣠ª",
+      "ëĥ ĺ",
+      "ë¢ ¸",
+      "ìĤ ij",
+      "ï® Ķ",
+      "ðĿķ ĸ",
+      "ðĿĹ §",
+      "ðŁĩ ¼",
+      "ðŁĵ ĭ",
+      "ðŁļ ľ",
+      "ðŁ¥ ¤",
+      "Ä ®",
+      "Å ·",
+      "ß Ĭ",
+      "ॠ¥",
+      "à® ª",
+      "áŀ Ħ",
+      "áµ Ģ",
+      "Ḡħ",
+      "á¼ ¢",
+      "âĪ Ŀ",
+      "âĬ ¹",
+      "âĴ ¶",
+      "âķ ´",
+      "⼠±",
+      "⼠³",
+      "⼠º",
+      "âŀ Ł",
+      "ãı Ħ",
+      "ê¸ Ķ",
+      "ê¹ Ł",
+      "ëĩ °",
+      "ë¹ »",
+      "ìĤ ¥",
+      "ìĽ »",
+      "ì° Ł",
+      "íĥ °",
+      "íĨ º",
+      "íļ ½",
+      "ï¤ ´",
+      "ï¥ ¾",
+      "ï³ Ŀ",
+      "ðĿIJ ¦",
+      "ðĿĴ ľ",
+      "ðĿĴ Ł",
+      "ðĿļ Ĺ",
+      "ðŁİ Ń",
+      "ðŁı ĵ",
+      "ðŁı ³",
+      "ðŁı º",
+      "ðŁIJ į",
+      "ðŁij ĥ",
+      "ðŁĴ ı",
+      "ðŁ¤ ĸ",
+      "ðŁ¤ µ",
+      "Õ ²",
+      "âµ Ķ",
+      "ëĺ ¬",
+      "ï¦ £",
+      "Ê Ĥ",
+      "áĨ «",
+      "áŀ ij",
+      "ðĿĸ İ",
+      "ðĿĹ ĸ",
+      "áĦ ĥ",
+      "âĩ ł",
+      "áĢ ¡",
+      "འĦ",
+      "âŀ ¸",
+      "ï¦ Ļ",
+      "âĩ ļ",
+      "ðŁIJ ¬",
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+      "áĬ ¢",
+      "áŀ IJ",
+      "Ḡ·",
+      "âĦ Ľ",
+      "âĩ Ģ",
+      "âĩ Ĭ",
+      "êĴ ¦",
+      "ê¦ ł",
+      "ï® ¤",
+      "ðŁį Ľ",
+      "ðŁ¤ Ľ",
+      "ᨠ¾",
+      "âŀ º",
+      "áķ ¯",
+      "ἠı",
+      "âĩ Ĥ",
+      "âĶ ¹",
+      "âĻ Ĺ",
+      "ðŁĸ ¨",
+      "ê¦ ı",
+      "ઠ°",
+      "áļ ¨",
+      "ðŁ¤ ¥",
+      "ðŁ§ ¢",
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+      "ãĦ ¥",
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+      "ðĵ Ī",
+      "ðĵĪ Ĵ",
+      "â» Ħ",
+      "ï¨ Ĵ",
+      "âĦ ª",
+      "Ò §",
+      "Ú Į",
+      "âĢ ¶",
+      "⺠ł",
+      "â» ģ",
+      "âĨ ¸",
+      "áĦ IJ",
+      "ãħ IJ",
+      "à» Ħ",
+      "áĹ ª",
+      "âĨ ¼",
+      "âĩ ĭ",
+      "âĩ ĺ",
+      "âĮ ij",
+      "âĸ ©",
+      "ðĿIJ Ĺ",
+      "Ä Ĭ",
+      "ঠī",
+      "ìī ł",
+      "É ¤",
+      "ß į",
+      "ß ı",
+      "áµ Ĺ",
+      "âĤ ¥",
+      "âĵ ī",
+      "âĶ ł",
+      "âĶ ¨",
+      "âķ Ħ",
+      "ä ¤",
+      "ä¤ Ģ",
+      "ê» ¸",
+      "ï® ģ",
+      "ðĵ Ĥ",
+      "ðĵĤ ĥ",
+      "ðŁ¦ ķ",
+      "Æ Ľ",
+      "ঠĩ",
+      "ãı ĺ",
+      "ï® ¼",
+      "Ú ĵ",
+      "Ú Ŀ",
+      "ঠĵ",
+      "ච¯",
+      "á´ ħ",
+      "á½ Ļ",
+      "âģ ¼",
+      "âĸ İ",
+      "â¼ ©",
+      "ä Ķ",
+      "äĶ Ģ",
+      "ë» ¡",
+      "ìĽ ½",
+      "íģ Ħ",
+      "ï¥ ¼",
+      "ï± ī",
+      "ï¹ »",
+      "ðĿĸ ĭ",
+      "ðĿĻ Ī",
+      "ðĿĻ ª",
+      "ðĿ Ļ¶",
+      "ðŁIJ Ħ",
+      "ðŁIJ Ĩ",
+      "áİ ¢",
+      "ḠĮ",
+      "âĿ ´",
+      "ðŁı ¸",
+      "È Ŀ",
+      "É ¸",
+      "Î ħ",
+      "Ï ľ",
+      "Ó ¢",
+      "Õ ¹",
+      "à´ ħ",
+      "ຠĪ",
+      "áĭ °",
+      "áij İ",
+      "áł µ",
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+      "á´ ī",
+      "Ḡµ",
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+      "âĵ £",
+      "âĶ ¶",
+      "â½ ¯",
+      "ê² ¥",
+      "ê¿ ĺ",
+      "ëģ İ",
+      "ëİ Ī",
+      "ëĶ ¯",
+      "ë² °",
+      "ìĺ ¯",
+      "ìĽ ¸",
+      "ìŀ Ĺ",
+      "ì§ ĺ",
+      "ì¬ ¬",
+      "ì· ¬",
+      "íģ ħ",
+      "íĵ Ķ",
+      "íĽ Ŀ",
+      "ï¤ ®",
+      "ï¤ ¹",
+      "ï¥ ²",
+      "ï¯ ĸ",
+      "ðĿĵ ħ",
+      "ðĿĻ Ħ",
+      "ðŁĵ ¶",
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+      "ðŁ¥ Ķ",
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+      "Å ®",
+      "Å ´",
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+      "Ç ģ",
+      "Ç £",
+      "Ç º",
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+      "È ¯",
+      "É ľ",
+      "Ê ¬",
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+      "Ë ¤",
+      "Ë µ",
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+      "Ò ¬",
+      "Ó ı",
+      "Ó Ľ",
+      "Ó ¡",
+      "Ó ³",
+      "Ô Į",
+      "Ô ¬",
+      "Õ ³",
+      "Ù »",
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+      "Ü ľ",
+      "ß ª",
+      "ठĿ",
+      "ঠĽ",
+      "ਠĨ",
+      "ઠķ",
+      "ઠ¡",
+      "à® İ",
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+      "ൠ»",
+      "ൠ¼",
+      "චł",
+      "චŃ",
+      "ච¶",
+      "à· Ĩ",
+      "༠½",
+      "áĢ ļ",
+      "áħ ¢",
+      "áĨ ¸",
+      "áĪ Ģ",
+      "áĪ ķ",
+      "áĪ °",
+      "áī ¡",
+      "áī ¤",
+      "áĬ ¦",
+      "áĬ «",
+      "áĭ ĭ",
+      "áĭ į",
+      "áİ ¯",
+      "áij Ń",
+      "áķ Ĺ",
+      "ᣠĽ",
+      "ᥠĴ",
+      "á© ī",
+      "áŃ º",
+      "á´ ¡",
+      "áµ ĺ",
+      "áµ Ľ",
+      "ᶠł",
+      "Ḡģ",
+      "Ḡĭ",
+      "á¹ Ļ",
+      "á¹ Ŀ",
+      "á¹ ¦",
+      "Ạħ",
+      "á¼ Ĥ",
+      "á½ ĥ",
+      "á½ į",
+      "á½ §",
+      "á¾ ·",
+      "âĢ µ",
+      "âĤ İ",
+      "âĦ Ŀ",
+      "âħ Ģ",
+      "âĨ ŀ",
+      "âĨ §",
+      "âĩ ħ",
+      "âĪ ĥ",
+      "âī ı",
+      "âī ½",
+      "âĬ ŀ",
+      "âĬ ¡",
+      "âĬ §",
+      "â Ĭ¶",
+      "âĭ Ħ",
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+      "âİ ¡",
+      "âİ £",
+      "âİ ª",
+      "âı İ",
+      "âĵ ĥ",
+      "âĵ ĸ",
+      "âĵ ¨",
+      "âķ ĭ",
+      "âķ ĸ",
+      "âķ ¢",
+      "âķ ²",
+      "âĸ Ĩ",
+      "âĸ Ĭ",
+      "âĸ į",
+      "âĸ ®",
+      "âĺ ¡",
+      "âĺ ¦",
+      "âĺ ±",
+      "âĺ ¿",
+      "âĻ ĺ",
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+      "âļ °",
+      "⼠ij",
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+      "⤠Ŀ",
+      "⤠¢",
+      "⤠·",
+      "⧠«",
+      "⨠Ń",
+      "⨠¯",
+      "â± £",
+      "â² İ",
+      "âµ Ľ",
+      "ãħ Ķ",
+      "ãĪ ı",
+      "ãī ²",
+      "ãī ³",
+      "ãĬ ij",
+      "ãĭ Ľ",
+      "ãİ IJ",
+      "ê² ¤",
+      "ê· ¿",
+      "ê¹ ŀ",
+      "ê» ¨",
+      "ê¼ į",
+      "ê¿ ¸",
+      "ëĥ ¬",
+      "ëĩ IJ",
+      "ëĭ ł",
+      "ëį ¯",
+      "ëĹ Į",
+      "ëĹ ij",
+      "ë¥ Ģ",
+      "ëª ĥ",
+      "ëª ¯",
+      "ë± ¡",
+      "ë³ ĵ",
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+      "ë µľ",
+      "ìĤ ³",
+      "ìħ ¥",
+      "ìĩ ½",
+      "ìı ¨",
+      "ìı ¸",
+      "ìķ į",
+      "ìĸ ĸ",
+      "ìŁ ¨",
+      "ì¢ ĥ",
+      "ì¢ į",
+      "ì¥ ij",
+      "ì§ ¼",
+      "ì© ĥ",
+      "ì® ľ",
+      "ì® ¸",
+      "ì³ ij",
+      "ì´ ¥",
+      "ì¾ ĥ",
+      "íħ ¦",
+      "íĪ ¿",
+      "íĵ ½",
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+      "íĸ ı",
+      "íĹ ł",
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+      "ï¥ İ",
+      "ï¥ ¶",
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+      "ï¦ ½",
+      "ï§ ĩ",
+      "ï¬ Ĩ",
+      "ï¬ ³",
+      "ï® ĩ",
+      "ï® Ī",
+      "ï® Ŀ",
+      "ï® ©",
+      "ï® ±",
+      "ï¯ ĺ",
+      "ï¯ Ļ",
+      "ï¯ ¢",
+      "ï¯ £",
+      "ï¯ ¤",
+      "ï¯ ¥",
+      "ï± Ĥ",
+      "ï² Ĩ",
+      "ï² ª",
+      "ï´ ¼",
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+      "ïº Ĭ",
+      "ïº ¥",
+      "ðĿij ¨",
+      "ðĿij ©",
+      "ðĿij ²",
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+      "ðĿĴ ª",
+      "ðĿĴ ®",
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+      "ðĿĵ Ī",
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+      "ðĿĶ ¨",
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+      "ðĿķ Ĩ",
+      "ðĿķ ¦",
+      "ðĿķ §",
+      "ðĿķ «",
+      "ðĿķ ·",
+      "ðĿĹ µ",
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+      "ðĿĺ Ħ",
+      "ðĿĺ Ļ",
+      "ðĿĺ ł",
+      "ðĿĺ ¬",
+      "ðĿĻ į",
+      "ðĿĻ ij",
+      "ðĿĻ ¡",
+      "ðĿ Ļ¨",
+      "ðĿĻ ·",
+      "ðĿļ į",
+      "ðĿĽ ¿",
+      "ðŁ ĥ",
+      "ðŁĥ ı",
+      "ðŁħ ĺ",
+      "ðŁ ī",
+      "ðŁī ij",
+      "ðŁİ ¡",
+      "ðŁİ ª",
+      "ðŁİ ±",
+      "ðŁİ ³",
+      "ðŁİ º",
+      "ðŁı İ",
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+      "ðŁı ļ",
+      "ðŁı ŀ",
+      "ðŁı ¦",
+      "ðŁı §",
+      "ðŁIJ ģ",
+      "ðŁIJ ħ",
+      "ðŁIJ ĵ",
+      "ðŁĴ Ĥ",
+      "ðŁĵ ij",
+      "ðŁĵ ĵ",
+      "ðŁĵ ¨",
+      "ðŁĵ «",
+      "ðŁĶ ĭ",
+      "ðŁĶ Ń",
+      "ðŁĶ ¯",
+      "ðŁķ Ĺ",
+      "ðŁļ Ĥ",
+      "ðŁļ ¢",
+      "ðŁļ ¦",
+      "ðŁļ ¬",
+      "ðŁĽ ĭ",
+      "ðŁĽ Į",
+      "ðŁĽ ¬",
+      "ðŁĽ ¶",
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+      "ðŁ¥ ĺ",
+      "ðŁ¥ Ł",
+      "ðŁ¥ ¦",
+      "ðŁ¦ ĩ",
+      "ðŁ¦ Ī",
+      "ðŁ§ Ĭ",
+      "ðŁ§ Ĺ",
+      "ðŁ§ ¤",
+      "Ê ·",
+      "Ë ¹",
+      "á¹ ļ",
+      "á½ ¥",
+      "âĦ Ł",
+      "ê² ¯",
+      "ê» «",
+      "ë° ·",
+      "ìĥ Ĩ",
+      "ìĽ Ŀ",
+      "ì¨ ī",
+      "ì« ı",
+      "ï¯ ķ",
+      "ðĿľ ĭ",
+      "É ²",
+      "Ò Ń",
+      "Ó Ī",
+      "འĽ",
+      "áĭ ĵ",
+      "áĻ Ń",
+      "áł ©",
+      "á¹ ®",
+      "âĦ Ĵ",
+      "âĨ »",
+      "âµ ĥ",
+      "ëĢ ¨",
+      "ëł §",
+      "ìī ¥",
+      "ìĮ ľ",
+      "ìĹ ¶",
+      "ì¨ Ī",
+      "ìª ¾",
+      "íı ½",
+      "íļ Ķ",
+      "íĽ µ",
+      "ï¤ ¸",
+      "ï¦ IJ",
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+      "ï§ ļ",
+      "ï¬ ¯",
+      "ðĿIJ Ĭ",
+      "ðĿķ Ĺ",
+      "ðĿĹ ļ",
+      "ðĿļ ĸ",
+      "ðŁħ ´",
+      "È ĥ",
+      "É Ŀ",
+      "Ï ±",
+      "Ó Ĺ",
+      "ठ¢",
+      "áħ ł",
+      "áī ¦",
+      "áij Į",
+      "áĴ ¼",
+      "áŀ ¡",
+      "áł ¨",
+      "áł Ń",
+      "ᨠħ",
+      "ᨠĶ",
+      "á´ ĺ",
+      "ᶠ¦",
+      "Ḡİ",
+      "á¼ ħ",
+      "á¼ ¹",
+      "âĨ ¯",
+      "âĵ İ",
+      "ãı Į",
+      "ê ī",
+      "êī Ĥ",
+      "ëĨ §",
+      "ëĿ ±",
+      "ì¢ ¡",
+      "íĪ ½",
+      "ï¤ ĩ",
+      "ï¤ Ľ",
+      "ðĿIJ ķ",
+      "ðĿĵ ¸",
+      "ðĿĵ ¼",
+      "ðĿĹ ķ",
+      "ðĿĺ Ī",
+      "ðŁı £",
+      "ðŁı ¤",
+      "ðŁĹ Ħ",
+      "Ñ ·",
+      "Ò ł",
+      "áµ ĸ",
+      "á¼ ¨",
+      "ë¬ Ħ",
+      "ï° ´",
+      "âĪ ½",
+      "Õ Ń",
+      "Ú ¹",
+      "ॠŁ",
+      "áĢ Ĩ",
+      "áŀ Ĵ",
+      "ãĢ ¶",
+      "ê¦ «",
+      "ï¸ ĵ",
+      "ðĿIJ Ľ",
+      "ðĿĺ Ĺ",
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+      "ðŁ§ ŀ",
+      "འĤ",
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+      "âĵ ģ",
+      "âĶ §",
+      "âķ ģ",
+      "âķ ¤",
+      "ê¦ Ĺ",
+      "ê¦ ¤",
+      "ðŁı Ī",
+      "áŀ ķ",
+      "Ô ½",
+      "ઠĹ",
+      "ଠĨ",
+      "âķ ķ",
+      "ï½ ł",
+      "â¼ ¦",
+      "â¼ ¯",
+      "â¾ ·",
+      "âĶ ĸ",
+      "ଠĵ",
+      "âĺ Ĺ",
+      "âį ĭ",
+      "ï¨ Ŀ",
+      "â¼ ¥",
+      "ï¦ ª",
+      "âĦ Ĭ",
+      "ãĢ ´",
+      "âį ¢",
+      "ð¡ Ī",
+      "ð¡Ī ½",
+      "ï© ¨",
+      "ãĢ »",
+      "ãı ĥ",
+      "ï¦ ¡",
+      "ï¨ ĺ",
+      "ðŁIJ ĥ",
+      "ðŁĨ ĸ",
+      "ðŁĹ ¾",
+      "ãĦ ĩ",
+      "Þ ĭ",
+      "â¼ ¼",
+      "ï¨ Ń",
+      "Þ Ģ",
+      "Þ Ħ",
+      "Þ Ī",
+      "Þ IJ",
+      "âĮ Ħ",
+      "â» ĺ",
+      "ãŁ ¢",
+      "á ħ§",
+      "ðIJĮ ¿",
+      "Ë »",
+      "ಠĹ",
+      "áĢ ĩ",
+      "áŀ Ĭ",
+      "âķ ĩ",
+      "ãĩ ¼",
+      "ãİ °",
+      "Õ Ĵ",
+      "Ü Ī",
+      "ß ¥",
+      "à¿ IJ",
+      "áĢ Ł",
+      "âĨ ¥",
+      "âķ Į",
+      "â½ Ģ",
+      "â½ °",
+      "â¾ Ĭ",
+      "ä Ħ",
+      "äĦ Ģ",
+      "ðĵ IJ",
+      "ðĵIJ į",
+      "ðŁİ ¦",
+      "âĤ ¯",
+      "âĬ ĺ",
+      "âĦ į",
+      "Ê µ",
+      "Ñ ¶",
+      "Ú ĥ",
+      "ঠĶ",
+      "à´ ¦",
+      "áİ ¶",
+      "áĵ ķ",
+      "á¹ ¨",
+      "âĤ ł",
+      "âĩ °",
+      "âĹ Ĵ",
+      "â¿ Ĭ",
+      "ê· ±",
+      "ì¹ ķ",
+      "íĪ ©",
+      "ïŃ Ģ",
+      "ðĿĴ ¸",
+      "ðĿĵ Ĭ",
+      "ðĿĺ ©",
+      "Ç ¦",
+      "É «",
+      "áĬ ¨",
+      "È ¹",
+      "Ê ¯",
+      "Î ª",
+      "Ú Ģ",
+      "áĮ ¸",
+      "áİ »",
+      "áı ķ",
+      "áı ´",
+      "á² Ĥ",
+      "á½ ¨",
+      "âı Ŀ",
+      "âĺ Ļ",
+      "ëĥ ¨",
+      "ëĦ ¼",
+      "ëĪ Ļ",
+      "ë£ ħ",
+      "ìĶ ¼",
+      "ìķ Ŀ",
+      "ìļ ¬",
+      "ìľ ±",
+      "ï¥ Ĥ",
+      "ï¦ ¹",
+      "ï¬ ¹",
+      "ïŃ ģ",
+      "ï³ Ī",
+      "ðĿĶ ħ",
+      "ðĿĺ ¤",
+      "ðĿĻ ı",
+      "ðĿĻ Ļ",
+      "ðŁķ ī",
+      "ðŁ§ Ļ",
+      "Ḡij",
+      "ê´ ¼",
+      "ëģ į",
+      "ëĹ ´",
+      "ëĿ ³",
+      "ë° ŀ",
+      "ë° ¢",
+      "ëµ ĺ",
+      "ìĤ Ķ",
+      "ìĦ Ħ",
+      "ì¼ ļ",
+      "íĢ ł",
+      "íĬ ±",
+      "íĮ ĸ",
+      "ï¤ ij",
+      "ï¦ ´",
+      "ï¦ ¸",
+      "ï´ į",
+      "ðĿĺ ·",
+      "Ä ¬",
+      "Å ¬",
+      "Æ Ģ",
+      "Æ ĭ",
+      "Æ ľ",
+      "Ç ij",
+      "Ç ĺ",
+      "Ç ŀ",
+      "Ç ¥",
+      "Ç ®",
+      "É °",
+      "É ¶",
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+      "É ½",
+      "Ê Ī",
+      "Ê IJ",
+      "Ë İ",
+      "Ë Ł",
+      "Ë ¦",
+      "Ë ¯",
+      "Ï IJ",
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+      "Ï ¢",
+      "Ï ¤",
+      "Ï ª",
+      "Ï Ń",
+      "Ï ®",
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+      "Ò ¨",
+      "Ó Ŀ",
+      "Ô ¡",
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+      "Õ ĵ",
+      "Õ ĸ",
+      "Õ ļ",
+      "Õ Ŀ",
+      "Ö İ",
+      "Ø ¿",
+      "Ú ħ",
+      "Ú į",
+      "Ú Ķ",
+      "Û Ĭ",
+      "Û ¾",
+      "Ü Ļ",
+      "Ý Ĵ",
+      "Ý ĺ",
+      "ß Ĵ",
+      "ß ĸ",
+      "ठĬ",
+      "ठIJ",
+      "ঠı",
+      "ঠĸ",
+      "ৠŁ",
+      "ઠ®",
+      "ઠ¹",
+      "à® ħ",
+      "à® Ĩ",
+      "à° ¡",
+      "à° °",
+      "ಠļ",
+      "ಠ®",
+      "ಠ¯",
+      "à´ Ł",
+      "à´ ·",
+      "ൠ¾",
+      "චij",
+      "චŀ",
+      "༠¼",
+      "འĵ",
+      "áĢ ĵ",
+      "áĤ ¦",
+      "áĥ ĸ",
+      "áĥ Ń",
+      "áĥ ¯",
+      "áħ ¨",
+      "áħ ª",
+      "áĨ °",
+      "áĪ ģ",
+      "áĪ İ",
+      "áĪ ĵ",
+      "áĪ ¥",
+      "áĪ ²",
+      "áĪ ´",
+      "áĪ »",
+      "áī ł",
+      "áī ²",
+      "áī ¶",
+      "áĬ £",
+      "áĬ ¥",
+      "áĬ ª",
+      "áĭ ĺ",
+      "áĭ ²",
+      "áĭ ¶",
+      "áĮ £",
+      "áį ¡",
+      "áį £",
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+      "áµ İ",
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+      "áµ ¤",
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+      "È ¨",
+      "È µ",
+      "È º",
+      "È »",
+      "É Į",
+      "É ®",
+      "Ê ħ",
+      "Ê ¥",
+      "Ê ¨",
+      "Ë ĵ",
+      "Ë Ķ",
+      "Ë ł",
+      "Ë £",
+      "Ë ¸",
+      "Í ´",
+      "Ï Ĺ",
+      "Ï ĺ",
+      "Ï Ļ",
+      "Ï ļ",
+      "Ï Ŀ",
+      "Ï ¨",
+      "Ï ¬",
+      "Ï ¾",
+      "Ï ¿",
+      "Ñ ª",
+      "Ò Ģ",
+      "Ò ľ",
+      "Ò ¼",
+      "Ò ½",
+      "Ó Ĥ",
+      "Ó ħ",
+      "Ó ĩ",
+      "Ó į",
+      "Ó ĸ",
+      "Ó Ł",
+      "Ó «",
+      "Ó ±",
+      "Ô Ĩ",
+      "Ô ĩ",
+      "Ô º",
+      "Õ ĭ",
+      "Ö ī",
+      "Ø Ī",
+      "Ø Ĭ",
+      "Ø ½",
+      "Ø ¾",
+      "Ù ·",
+      "Ú Ĥ",
+      "Ú Ĭ",
+      "Ú ĸ",
+      "Ú Ĺ",
+      "Ú £",
+      "Ú «",
+      "Ú ¸",
+      "Û Ģ",
+      "Û į",
+      "Û ½",
+      "Ü ī",
+      "Ü ¤",
+      "Ý §",
+      "Ý ´",
+      "Þ ĥ",
+      "Þ ¤",
+      "Þ ¥",
+      "ß ļ",
+      "ß Ľ",
+      "ß ¤",
+      "àł į",
+      "àł ĵ",
+      "àł ³",
+      "à¡ ¢",
+      "ॠł",
+      "ৠł",
+      "ৠº",
+      "ਠĬ",
+      "ਠIJ",
+      "ਠ®",
+      "ਠ¯",
+      "ਠ°",
+      "ਠ¸",
+      "ઠĨ",
+      "ઠ³",
+      "ઠµ",
+      "ઠ½",
+      "ଠĮ",
+      "ଠĺ",
+      "ଠ½",
+      "à® ĥ",
+      "à® ¸",
+      "à° Ĩ",
+      "à° ķ",
+      "à° ¦",
+      "ಠĨ",
+      "ಠĬ",
+      "ಠĮ",
+      "ಠIJ",
+      "ಠĽ",
+      "ಠ¤",
+      "ಠ¦",
+      "ಠª",
+      "ಠ²",
+      "ಠ¹",
+      "à´ Ĩ",
+      "à´ ı",
+      "à´ Ĺ",
+      "à´ «",
+      "à´ ¹",
+      "ൠº",
+      "ൠ½",
+      "චħ",
+      "චĬ",
+      "චĶ",
+      "ච§",
+      "ච«",
+      "ච°",
+      "༠Ħ",
+      "༠ħ",
+      "༠Ĭ",
+      "འĻ",
+      "འ¡",
+      "འ§",
+      "à¿ Ģ",
+      "à¿ Ļ",
+      "áĢ Ŀ",
+      "áĢ §",
+      "áĢ ©",
+      "áĢ ¿",
+      "áģ µ",
+      "áĤ ģ",
+      "áĤ ½",
+      "áĥ Ĥ",
+      "áĥ ª",
+      "áĦ Ĭ",
+      "áĦ ¢",
+      "áħ ¦",
+      "áħ Ń",
+      "áĨ ®",
+      "áĨ ±",
+      "áĨ »",
+      "á ĩ",
+      "áĩ Ĥ",
+      "áĪ ħ",
+      "áĪ ī",
+      "áĪ Į",
+      "áĪ IJ",
+      "áĪ Ĵ",
+      "áĪ Ļ",
+      "áĪ ļ",
+      "áĪ ľ",
+      "áĪ ŀ",
+      "áĪ ©",
+      "áĪ ³",
+      "áĪ º",
+      "áĪ ½",
+      "áī ħ",
+      "áī ¢",
+      "áī ±",
+      "áī ´",
+      "áĬ ĥ",
+      "áĬ į",
+      "áĬ ĸ",
+      "áĬ ®",
+      "áĬ ¸",
+      "áĭ Ľ",
+      "áĭ Ŀ",
+      "áĭ ³",
+      "áĮ ģ",
+      "áĮ ħ",
+      "áĮ ¥",
+      "áĮ ¦",
+      "á Į¨",
+      "áį Ĭ",
+      "áį į",
+      "áį ķ",
+      "áį ĸ",
+      "áį ¢",
+      "áį ¤",
+      "áİ Ĵ",
+      "áİ ª",
+      "áı ģ",
+      "áı IJ",
+      "áı Ł",
+      "áIJ Ĥ",
+      "áIJ ĸ",
+      "áIJ Ŀ",
+      "áIJ ŀ",
+      "áIJ Ł",
+      "áIJ ł",
+      "áij ĸ",
+      "áĴ ĭ",
+      "áĴ į",
+      "áĴ ¡",
+      "áĵ «",
+      "áĶ ķ",
+      "áķ ĭ",
+      "áķ ij",
+      "áķ Ļ",
+      "áķ ļ",
+      "áķ Ľ",
+      "áķ ¤",
+      "áķ ¦",
+      "áķ ®",
+      "áķ ¼",
+      "áĸ ĵ",
+      "áĹ Ĺ",
+      "áĹ ¢",
+      "áĹ ¯",
+      "áĹ ·",
+      "áĺ Ħ",
+      "áĺ ij",
+      "ἠĤ",
+      "ἠĻ",
+      "áŀ į",
+      "áł Ĩ",
+      "áł ¡",
+      "áł ¦",
+      "áł ®",
+      "áł ¯",
+      "áł ²",
+      "áł ·",
+      "á¡ į",
+      "á¡ ŀ",
+      "á¡ ¤",
+      "á ¡´",
+      "á¡ µ",
+      "ᤠĵ",
+      "ᥠĸ",
+      "ᥠ°",
+      "ᨠ¦",
+      "ᨠ§",
+      "ᨠ¨",
+      "ᨠª",
+      "ᨠ¬",
+      "ᨠ¯",
+      "ᨠ³",
+      "ᨠµ",
+      "á© ĥ",
+      "ᬠķ",
+      "áŃ £",
+      "á ±",
+      "á± ļ",
+      "á² ł",
+      "á´ ĵ",
+      "á´ ¶",
+      "áµ Ĥ",
+      "áµ Į",
+      "áµ ¥",
+      "áµ ´",
+      "ᶠĩ",
+      "ḠĪ",
+      "Ḡł",
+      "Ḡ§",
+      "Ḡ´",
+      "Ḡ¾",
+      "á¹ Ģ",
+      "á¹ ĸ",
+      "á¹ Ł",
+      "á¹ ł",
+      "á¹ «",
+      "á¹ ±",
+      "á¹ ·",
+      "á¹ ¿",
+      "ẠĦ",
+      "Ạį",
+      "Ạij",
+      "ẠĹ",
+      "á¼ ī",
+      "á¼ ĵ",
+      "á¼ Ń",
+      "á½ ĭ",
+      "á½ Ĵ",
+      "á½ ł",
+      "á½ £",
+      "á¾ Ħ",
+      "á¾ ı",
+      "á¾ ij",
+      "á¾ Ĺ",
+      "á¾ ¦",
+      "á¾ §",
+      "á¾ ¾",
+      "á¿ Ħ",
+      "á¿ ĵ",
+      "á¿ ¡",
+      "á¿ ¬",
+      "âģ ļ",
+      "âĤ Į",
+      "âĦ ģ",
+      "âĦ Ķ",
+      "âĦ £",
+      "âĦ §",
+      "âĦ ¯",
+      "âĦ °",
+      "âĦ ´",
+      "âħ ħ",
+      "âĨ ľ",
+      "âĨ «",
+      "âĨ Ń",
+      "âĨ ±",
+      "âĨ ¹",
+      "âĨ ½",
+      "âĩ ĩ",
+      "âĩ ľ",
+      "âĩ µ",
+      "âĪ ī",
+      "âĪ Ĭ",
+      "âĪ ĸ",
+      "âĪ ľ",
+      "âĪ ¾",
+      "âī Ģ",
+      "âī ĭ",
+      "âī Į",
+      "âī ĵ",
+      "âī ľ",
+      "âī ´",
+      "âī ¿",
+      "âĬ Ĭ",
+      "âĬ ĭ",
+      "âĬ Ķ",
+      "âĬ ĸ",
+      "âĬ £",
+      "âĬ ¦",
+      "âĭ İ",
+      "âĭ ª",
+      "âĭ ²",
+      "âĮ ¦",
+      "âĮ §",
+      "âį º",
+      "âİ Ī",
+      "âİ ¨",
+      "âİ ¬",
+      "âİ ³",
+      "âİ ¼",
+      "âİ ¾",
+      "âı Į",
+      "âı ļ",
+      "âı «",
+      "âı ¯",
+      "âı µ",
+      "âĴ ľ",
+      "âĴ Ŀ",
+      "âĴ «",
+      "âĵ Ħ",
+      "âĵ Ĭ",
+      "âĵ Ļ",
+      "âĵ ©",
+      "âĶ ij",
+      "âĶ Ļ",
+      "âĶ ļ",
+      "âĶ ¥",
+      "âķ ħ",
+      "âķ ī",
+      "âķ į",
+      "âķ ı",
+      "âķ ŀ",
+      "âĸ ļ",
+      "âĸ ¯",
+      "âĹ ĥ",
+      "âĹ ļ",
+      "âĹ ¬",
+      "âĹ ´",
+      "âĺ Ī",
+      "âĺ ¤",
+      "âĺ ¥",
+      "âĺ §",
+      "âĺ ¬",
+      "âĻ ģ",
+      "âĻ ±",
+      "âļ ĥ",
+      "âļ Ħ",
+      "âļ ħ",
+      "âļ ı",
+      "âļ ļ",
+      "âļ ŀ",
+      "âļ Ł",
+      "âļ ±",
+      "âļ ²",
+      "âľ Ģ",
+      "âľ Ł",
+      "âľ ¢",
+      "âĿ µ",
+      "⣠¡",
+      "⣠¦",
+      "⣠§",
+      "⣠³",
+      "⣠¾",
+      "⣠¿",
+      "âł ĩ",
+      "⤠Ħ",
+      "⤠º",
+      "⥠Ĥ",
+      "⥠¹",
+      "⧠ī",
+      "⧠¼",
+      "⧠½",
+      "⨠į",
+      "⬠Ĭ",
+      "⬠Ł",
+      "âŃ ŀ",
+      "â® ŀ",
+      "â® ³",
+      "⯠Ī",
+      "⯠ij",
+      "â± ł",
+      "â± ±",
+      "â² Ń",
+      "â´ ¹",
+      "âµ ķ",
+      "⸠¾",
+      "â º«",
+      "â¼ Ĩ",
+      "â¼ ł",
+      "â½ Ł",
+      "â½ ¼",
+      "â¾ Ľ",
+      "â¾ §",
+      "â¿ ĥ",
+      "â¿ »",
+      "ãĤ ķ",
+      "ãĤ Ł",
+      "ãĦ Ľ",
+      "ãĦ ¡",
+      "ãĦ ¶",
+      "ãĦ º",
+      "ãħ Ĵ",
+      "ãħ Ł",
+      "ãĨ Ģ",
+      "ãĩ »",
+      "ãĪ ij",
+      "ãĪ Ń",
+      "ãĪ ®",
+      "ãĪ ³",
+      "ãĪ ¹",
+      "ãī ¥",
+      "ãī ¦",
+      "ãī ¹",
+      "ãī ¿",
+      "ãĬ ŀ",
+      "ãĬ ¨",
+      "ãĭ ij",
+      "ãĭ ¥",
+      "ãĭ ´",
+      "ãĭ º",
+      "ãİ Ħ",
+      "ãİ ķ",
+      "ãİ ¯",
+      "ãı Ĥ",
+      "ãı Ī",
+      "ãı ĵ",
+      "ãı ĸ",
+      "ãı ±",
+      "ãIJ ±",
+      "ãŁ ģ",
+      "ã ¢",
+      "㢠¨",
+      "ã ¨",
+      "㨠³",
+      "ã« ª",
+      "ã« ´",
+      "㶠³",
+      "㺠¾",
+      "ä Ģ",
+      "äĢ Ģ",
+      "ä ĭ",
+      "äĭ Į",
+      "ä ĮĢ",
+      "äIJ Ģ",
+      "ä łĢ",
+      "ä ł",
+      "äł ¼",
+      "ä §",
+      "ä§ ŀ",
+      "ä¨ °",
+      "ä¨ º",
+      "ä ´Ģ",
+      "ä ·",
+      "ä· ħ",
+      "ä ·¸",
+      "ê Ĥ",
+      "êĤ «",
+      "ê Į",
+      "êĮ ¼",
+      "ê į",
+      "êį ²",
+      "êĴ µ",
+      "ê ĵ",
+      "êĵ ½",
+      "êĻ Ń",
+      "êĿ Ľ",
+      "êĿ ¥",
+      "ê ŀ",
+      "êŀ Ĭ",
+      "ê¦ Ĩ",
+      "ê¦ ĩ",
+      "ê¦ Ł",
+      "ê¦ ¨",
+      "ê§ Ī",
+      "ê ©",
+      "ê© Ł",
+      "êª ĭ",
+      "êª ij",
+      "êª ķ",
+      "êª Ĺ",
+      "êª ľ",
+      "êª ®",
+      "êª ±",
+      "êª »",
+      "êª ¼",
+      "ê« Ģ",
+      "ê« Ŀ",
+      "ê° ĥ",
+      "ê° ĺ",
+      "ê± ľ",
+      "ê² ĵ",
+      "ê² ļ",
+      "ê³ Ļ",
+      "ê³ ¾",
+      "ê´ Ĺ",
+      "ê´ Ļ",
+      "êµ Ľ",
+      "ê¶ ĥ",
+      "ê¶ ķ",
+      "ê¶ ¨",
+      "ê¸ ©",
+      "ê¸ ¿",
+      "ê ¹Ħ",
+      "ê¹ Ĩ",
+      "ê¹ ī",
+      "ê¹ ĵ",
+      "ê¹ ¢",
+      "ê¹ £",
+      "ê¹ ¸",
+      "êº ³",
+      "ê¿ ı",
+      "ê¿ ķ",
+      "ê¿ §",
+      "ëĢ ©",
+      "ëģ ħ",
+      "ëĥ µ",
+      "ëĦ ĸ",
+      "ëĦ Ĺ",
+      "ëĦ ¢",
+      "ëħ Ĥ",
+      "ëĨ IJ",
+      "ëĩ ľ",
+      "ëĪ ĭ",
+      "ëĪ ļ",
+      "ëī į",
+      "ëī ¨",
+      "ëĬ ļ",
+      "ëĬ ¡",
+      "ëĭ ľ",
+      "ëĭ ª",
+      "ëĮ ĺ",
+      "ëĮ ¤",
+      "ëĮ ¸",
+      "ëİ Ł",
+      "ëı ¨",
+      "ëIJ Ħ",
+      "ëIJ ı",
+      "ëIJ ´",
+      "ëIJ ¸",
+      "ëij ģ",
+      "ëij ¿",
+      "ëĴ ¨",
+      "ëĵ ·",
+      "ëĶ ®",
+      "ëĶ ²",
+      "ëķ §",
+      "ëĸ Ķ",
+      "ëĸ ª",
+      "ëĺ Ń",
+      "ëļ Ģ",
+      "ëļ ł",
+      "ëĽ Ķ",
+      "ëĽ ©",
+      "ëľ ħ",
+      "ëŀ ķ",
+      "ëŀ °",
+      "ëŁ IJ",
+      "ëł ¡",
+      "ë¡ ŀ",
+      "ë¡ £",
+      "ë¡ µ",
+      "ë£ Ħ",
+      "ë£ į",
+      "ë¤ ³",
+      "ë¦ į",
+      "ë¦ ı",
+      "ë¦ ³",
+      "ë§ Ħ",
+      "ë§ Ĩ",
+      "ë§ į",
+      "ë§ ľ",
+      "ë§ «",
+      "ë§ »",
+      "ë¨ ®",
+      "ë© Ĥ",
+      "ë© Ń",
+      "ëª ´",
+      "ë¬ ľ",
+      "ë¬ ł",
+      "ë¬ «",
+      "ë¬ ¾",
+      "ëŃ ¬",
+      "ë® ĺ",
+      "ë® ¹",
+      "ë¯ ķ",
+      "ë¯ ľ",
+      "ë° ¨",
+      "ë° ª",
+      "ë± Ķ",
+      "ë² ĺ",
+      "ë² Ľ",
+      "ë² ±",
+      "ë² ´",
+      "ë´ ½",
+      "ëµ ¤",
+      "ëµ ¨",
+      "ë· Ĺ",
+      "ë· ĺ",
+      "ë¸ ĵ",
+      "ë¸ ľ",
+      "ë¹ ª",
+      "ëº ĥ",
+      "ëº ĺ",
+      "ëº µ",
+      "ë» ´",
+      "ë¼ IJ",
+      "ë¾ Ķ",
+      "ìģ Ń",
+      "ìĤ ł",
+      "ìĤ ®",
+      "ìĥ ı",
+      "ìĥ Ļ",
+      "ìĦ º",
+      "ìħ ¢",
+      "ìĨ Ģ",
+      "ìĨ ħ",
+      "ìĨ ¤",
+      "ìĨ ¦",
+      "ìĨ ¬",
+      "ìĩ ±",
+      "ìĪ µ",
+      "ìĭ ¨",
+      "ìĭ ´",
+      "ìĮ °",
+      "ìį ľ",
+      "ìİ Ĺ",
+      "ìİ ĺ",
+      "ìİ ¼",
+      "ìij ī",
+      "ìij Ŀ",
+      "ìij »",
+      "ìĴ Ķ",
+      "ìĴ ¯",
+      "ìĵ ©",
+      "ìķ IJ",
+      "ìķ ĸ",
+      "ìĸ ł",
+      "ìĸ ¾",
+      "ìĹ ĥ",
+      "ìĹ Ĺ",
+      "ìĹ ľ",
+      "ìĹ ¨",
+      "ìĺ Ĥ",
+      "ìĺ Ħ",
+      "ìĺ ı",
+      "ìĺ ¾",
+      "ìĺ ¿",
+      "ìľ §",
+      "ìĿ IJ",
+      "ìĿ ĸ",
+      "ìĿ ·",
+      "ìŀ į",
+      "ìŀ ı",
+      "ìŀ ¨",
+      "ìŀ ª",
+      "ìŀ ³",
+      "ìł ¡",
+      "ìł ´",
+      "ìł ¹",
+      "ì¡ Ģ",
+      "ì¡ ª",
+      "ì¡ µ",
+      "ì¢ IJ",
+      "ì¢ ¨",
+      "ì£ Į",
+      "ì£ Ļ",
+      "ì£ ³",
+      "ì¦ ij",
+      "ì§ ¥",
+      "ì§ ´",
+      "ì§ ¾",
+      "ì¨ ĵ",
+      "ì¨ ķ",
+      "ì© °",
+      "ì© »",
+      "ì© ¼",
+      "ìª Ĺ",
+      "ì¬ Ķ",
+      "ì¬ ĺ",
+      "ì® ®",
+      "ì¯ ķ",
+      "ì¯ ĺ",
+      "ì° İ",
+      "ì° ¯",
+      "ì± ĥ",
+      "ì± µ",
+      "ì² §",
+      "ì² ®",
+      "ì² ¯",
+      "ì³ ¬",
+      "ì´ ĭ",
+      "ì´ ¢",
+      "ìµ ¥",
+      "ì¶ £",
+      "ì¸ Ī",
+      "ì¸ Ļ",
+      "ìº ¤",
+      "ìº Ń",
+      "ì» ½",
+      "ì¼ Ļ",
+      "ì½ ¬",
+      "ì¾ Ģ",
+      "ì¿ ħ",
+      "ì¿ ½",
+      "íĢ ħ",
+      "íģ ¦",
+      "íĤ ħ",
+      "íĥ ¶",
+      "íĥ ¹",
+      "íĦ Ķ",
+      "íħ £",
+      "íĨ Ħ",
+      "íĨ §",
+      "íĨ ¹",
+      "íĩ ¼",
+      "íī ¤",
+      "íĬ ½",
+      "íĭ Ĥ",
+      "íĭ ij",
+      "íį Ī",
+      "íį Ļ",
+      "íį ¿",
+      "íİ ¶",
+      "íIJ Ŀ",
+      "íĴ ľ",
+      "íĵ Ŀ",
+      "íĵ ª",
+      "íĵ ±",
+      "íĵ ·",
+      "íĵ ¼",
+      "íĶ Ļ",
+      "íĶ ł",
+      "íķ ļ",
+      "íķ Ľ",
+      "íķ ŀ",
+      "íķ Ł",
+      "íķ §",
+      "íķ ¶",
+      "íĸ Ĭ",
+      "íĸ ĭ",
+      "íĸ į",
+      "íĸ Ķ",
+      "íĸ ĺ",
+      "íĸ ¡",
+      "íĸ ¬",
+      "íĹ £",
+      "íĹ ¿",
+      "íĺ ĸ",
+      "íĺ Ń",
+      "íļ °",
+      "íĽ į",
+      "íĽ ½",
+      "íĿ Ł",
+      "íĿ Ń",
+      "íĿ ´",
+      "íŀ ľ",
+      "ï¤ ī",
+      "ï¤ Ń",
+      "ï¤ ²",
+      "ï¤ µ",
+      "ï¤ ¼",
+      "ï¥ Ģ",
+      "ï¥ ij",
+      "ï¥ Ĵ",
+      "ï¥ ķ",
+      "ï¥ ĺ",
+      "ï¥ Ļ",
+      "ï¥ «",
+      "ï¥ ¬",
+      "ï¥ °",
+      "ï ¥¿",
+      "ï¦ ĭ",
+      "ï¦ ı",
+      "ï¦ Ķ",
+      "ï¦ ĸ",
+      "ï¦ ĺ",
+      "ï¦ Ľ",
+      "ï¦ ł",
+      "ï¦ ®",
+      "ï¦ ¯",
+      "ï¦ º",
+      "ï¦ »",
+      "ï¦ ¾",
+      "ï§ Ĩ",
+      "ï§ ĸ",
+      "ï§ Ľ",
+      "ï§ ŀ",
+      "ï§ Ł",
+      "ï§ §",
+      "ï§ ³",
+      "ï§ º",
+      "ï§ ½",
+      "ï¨ ĥ",
+      "ï¨ ļ",
+      "ï¨ ¢",
+      "ï© Ł",
+      "ï¬ ¤",
+      "ï¬ ¬",
+      "ï¬ ¼",
+      "ïŃ Ĵ",
+      "ïŃ ķ",
+      "ïŃ Ľ",
+      "ïŃ Ŀ",
+      "ïŃ ŀ",
+      "ïŃ Ł",
+      "ïŃ ¤",
+      "ïŃ §",
+      "ïŃ ¨",
+      "ïŃ ®",
+      "ïŃ °",
+      "ïŃ ±",
+      "ïŃ ·",
+      "ïŃ ¹",
+      "ïŃ »",
+      "ï® Ģ",
+      "ï® ĥ",
+      "ï® Ħ",
+      "ï® ħ",
+      "ï® į",
+      "ï® Ĵ",
+      "ï® ĵ",
+      "ï® ķ",
+      "ï® ¦",
+      "ï® ®",
+      "ï® °",
+      "ï¯ ĵ",
+      "ï¯ ľ",
+      "ï¯ ©",
+      "ï¯ ª",
+      "ï¯ ¬",
+      "ï¯ Ń",
+      "ï¯ ®",
+      "ï¯ ·",
+      "ï¯ ¹",
+      "ï¯ »",
+      "ï¯ ¼",
+      "ï° ĥ",
+      "ï° Į",
+      "ï° IJ",
+      "ï° ĺ",
+      "ï° Ļ",
+      "ï° ľ",
+      "ï° ŀ",
+      "ï° ¢",
+      "ï° ®",
+      "ï° °",
+      "ï° ¼",
+      "ï° ¿",
+      "ï± Ģ",
+      "ï± ģ",
+      "ï± Ī",
+      "ï± ĭ",
+      "ï± ı",
+      "ï± Ń",
+      "ï² Ģ",
+      "ï² ĩ",
+      "ï² Ī",
+      "ï² ĭ",
+      "ï² İ",
+      "ï² Ĵ",
+      "ï² ľ",
+      "ï² ł",
+      "ï² ¬",
+      "ï² »",
+      "ï³ ĩ",
+      "ï³ Ķ",
+      "ï³ £",
+      "ï³ «",
+      "ï´ ĺ",
+      "ï´ °",
+      "ï´ ½",
+      "ï ¶",
+      "ï¶ °",
+      "ï¸ ĸ",
+      "ï¸ ´",
+      "ï¸ ¹",
+      "ï¹ į",
+      "ï¹ Ĺ",
+      "ï¹ ¢",
+      "ï¹ ¤",
+      "ï¹ ©",
+      "ï¹ ±",
+      "ï¾ °",
+      "ï¿ Ĥ",
+      "ï¿ ®",
+      "ðIJĮ °",
+      "ðIJĮ ¹",
+      "ðIJĮ º",
+      "ðIJĮ ½",
+      "ðIJį Ĥ",
+      "ðIJį ĥ",
+      "ðIJį Ħ",
+      "ðIJ İ",
+      "ðIJİ ¹",
+      "ðIJ¤ Ĥ",
+      "ðIJ¤ į",
+      "ðIJ¤ ı",
+      "ðIJ¤ ĵ",
+      "ðIJŃ ī",
+      "ðIJŃ į",
+      "ðIJ° ĩ",
+      "ðIJ° °",
+      "ðij Ĥ",
+      "ðijĤ Ħ",
+      "ðij ĺ",
+      "ðijĺ ģ",
+      "ðĴ Ģ",
+      "ðĴĢ ¸",
+      "ðĴ ģ",
+      "ðĴģ º",
+      "ðĴ Ħ",
+      "ðĴĦ ·",
+      "ðĴ Ĭ",
+      "ðĴĬ ij",
+      "ðĴ ĭ",
+      "ðĴĭ Ĺ",
+      "ð ĴĮ",
+      "ðĴĮ ¨",
+      "ðĵĥ ¢",
+      "ðĵĥ °",
+      "ðĸ ł",
+      "ðĸł ļ",
+      "ðĿĦ ĥ",
+      "ðĿĦ ħ",
+      "ðĿĦ ķ",
+      "ðĿĦ Ļ",
+      "ðĿĦ ±",
+      "ðĿĦ ´",
+      "ðĿĦ ¹",
+      "ðĿħ İ",
+      "ðĿħ ª",
+      "ðĿĨ £",
+      "ðĿĨ ³",
+      "ðĿĨ ¹",
+      "ðĿĩ Ĭ",
+      "ðĿĩ Ĺ",
+      "ðĿĩ ļ",
+      "ðĿĩ ľ",
+      "ðĿĩ ł",
+      "ðĿIJ ī",
+      "ðĿIJ ĸ",
+      "ðĿIJ ĺ",
+      "ðĿIJ £",
+      "ðĿIJ ±",
+      "ðĿij Ĭ",
+      "ðĿij Ń",
+      "ðĿij ¼",
+      "ðĿij ½",
+      "ðĿĴ °",
+      "ðĿĴ ·",
+      "ðĿĴ ¿",
+      "ðĿĵ ģ",
+      "ðĿĵ ĭ",
+      "ðĿĵ İ",
+      "ðĿĵ Ĵ",
+      "ðĿ ĵĺ",
+      "ðĿĵ ¢",
+      "ðĿĵ ¦",
+      "ðĿĵ «",
+      "ðĿĵ ¿",
+      "ðĿĶ İ",
+      "ðĿĶ ±",
+      "ðĿĶ ´",
+      "ðĿĶ ·",
+      "ðĿĶ ¸",
+      "ðĿĶ ½",
+      "ðĿķ Ĥ",
+      "ðĿķ ĥ",
+      "ðĿķ ĭ",
+      "ðĿķ ı",
+      "ðĿķ IJ",
+      "ðĿķ ¥",
+      "ðĿķ ´",
+      "ðĿķ º",
+      "ðĿĸ IJ",
+      "ðĿĸ Ľ",
+      "ðĿĸ Ŀ",
+      "ðĿĸ ŀ",
+      "ðĿĹ ©",
+      "ðĿĹ ³",
+      "ðĿĹ ½",
+      "ðĿĺ Ĭ",
+      "ðĿĺ ĭ",
+      "ðĿĺ Ķ",
+      "ðĿĺ ±",
+      "ðĿĺ ´",
+      "ðĿĺ ¿",
+      "ðĿĻ Ĵ",
+      "ðĿĻ Ŀ",
+      "ðĿĻ Ł",
+      "ðĿĻ ¬",
+      "ðĿĻ Ń",
+      "ðĿĻ »",
+      "ðĿĻ ¾",
+      "ðĿļ Ī",
+      "ðĿļ ĭ",
+      "ðĿļ ij",
+      "ðĿļ Ł",
+      "ðĿļ ł",
+      "ðĿļ £",
+      "ðĿĽ ½",
+      "ðĿľ Ĥ",
+      "ðĿľ Ķ",
+      "ðĿľ Ļ",
+      "ðŁ Ģ",
+      "ðŁĢ Ħ",
+      "ðŁĦ ²",
+      "ðŁĦ ¶",
+      "ðŁħ IJ",
+      "ðŁħ ĸ",
+      "ðŁħ ļ",
+      "ðŁħ Ľ",
+      "ðŁħ ¦",
+      "ðŁħ ¶",
+      "ðŁħ »",
+      "ðŁħ ¼",
+      "ðŁĨ ĥ",
+      "ðŁĨ Ĩ",
+      "ðŁĨ İ",
+      "ðŁĪ ¯",
+      "ðŁĪ ²",
+      "ðŁĪ ¹",
+      "ðŁĮ ĩ",
+      "ðŁĮ ĵ",
+      "ðŁį ĺ",
+      "ðŁİ ij",
+      "ðŁİ ¿",
+      "ðŁı ı",
+      "ðŁı Ĵ",
+      "ðŁı ©",
+      "ðŁı ¯",
+      "ðŁIJ Ģ",
+      "ðŁij Ŀ",
+      "ðŁĴ ¹",
+      "ðŁĴ º",
+      "ðŁĵ Ł",
+      "ðŁĵ ª",
+      "ðŁĵ ¼",
+      "ðŁĶ Ģ",
+      "ðŁĶ Ĥ",
+      "ðŁĶ ĥ",
+      "ðŁĶ ĩ",
+      "ðŁĶ ĵ",
+      "ðŁĶ ¢",
+      "ðŁĶ ¤",
+      "ðŁĶ ©",
+      "ðŁķ ĸ",
+      "ðŁķ ļ",
+      "ðŁķ ľ",
+      "ðŁķ Ŀ",
+      "ðŁķ ŀ",
+      "ðŁķ ł",
+      "ðŁķ ¢",
+      "ðŁķ ³",
+      "ðŁĸ ĩ",
+      "ðŁĸ ij",
+      "ðŁĸ ¶",
+      "ðŁĹ ģ",
+      "Ñ ¨",
+      "Ú İ",
+      "á¡ Į",
+      "Ḡ°",
+      "ẠĢ",
+      "á¼ ®",
+      "á½ Ŀ",
+      "âĦ ¬",
+      "âļ §",
+      "⼠¤",
+      "ã³ ¬",
+      "êĻ ĭ",
+      "ê¸ ij",
+      "ëĶ ī",
+      "ëĹ į",
+      "ë¡ ij",
+      "ë¯ ij",
+      "ë» ħ",
+      "ë¼ Ŀ",
+      "ìĦ IJ",
+      "ìī ¡",
+      "ìĭ ²",
+      "ìı ±",
+      "ìĹ ¤",
+      "ìĿ ©",
+      "ìĿ ¿",
+      "ìŁ Ļ",
+      "ìł °",
+      "ì¥ ī",
+      "íĬ Ń",
+      "íķ ®",
+      "ï® ı",
+      "ðŁħ ±",
+      "ðŁĨ Ĵ",
+      "ðŁķ ĭ",
+      "É ĺ",
+      "Ê ĵ",
+      "Õ ĥ",
+      "à´ ´",
+      "འħ",
+      "áĨ º",
+      "áĪ Ĭ",
+      "áĪ ¨",
+      "áĪ ¾",
+      "áī IJ",
+      "áĮ ĥ",
+      "áĮ ½",
+      "áĶ Ń",
+      "áł Ĥ",
+      "áł ¬",
+      "ᨠ¸",
+      "á© ĭ",
+      "ᶠı",
+      "á¾ Ķ",
+      "á¿ IJ",
+      "á¿ ļ",
+      "âĻ Ļ",
+      "âļ Ĥ",
+      "âļ Ĺ",
+      "â¡ ¢",
+      "⤠¦",
+      "ëĸ °",
+      "ë¤ Ĥ",
+      "ë§ ł",
+      "ë± ĭ",
+      "ë± IJ",
+      "ìĽ ¢",
+      "ìľ ¾",
+      "ì³ ħ",
+      "ì» ģ",
+      "íģ »",
+      "íĥ Ļ",
+      "íĵ ĸ",
+      "íĵ Ń",
+      "íķ ±",
+      "íĽ ľ",
+      "ï¤ ħ",
+      "ï¤ Ĩ",
+      "ï¦ ĥ",
+      "ï§ ©",
+      "ï¨ Ĥ",
+      "ðIJ¤ Ķ",
+      "ðIJŃ ĵ",
+      "ðIJ° ¼",
+      "ðĿĵ ŀ",
+      "ðĿĵ °",
+      "ðĿĻ ľ",
+      "ðĿļ ģ",
+      "ðŁħ ¢",
+      "ðŁı ĩ",
+      "È ²",
+      "Ê ¶",
+      "Ô Ī",
+      "Ô ij",
+      "Ý ĵ",
+      "Ý ¥",
+      "ठij",
+      "ॠ±",
+      "ଠī",
+      "à° ³",
+      "à° µ",
+      "ಠŁ",
+      "áĢ ı",
+      "áģ ¼",
+      "áī ¨",
+      "áĬ Ĵ",
+      "áĭ ©",
+      "áĮ Ħ",
+      "áĮ Ķ",
+      "áIJ §",
+      "á ĴĮ",
+      "áĶ ħ",
+      "áĶ Ĭ",
+      "áł Ħ",
+      "ᨠģ",
+      "Ḡĥ",
+      "Ḡ»",
+      "âĶ ŀ",
+      "âĺ µ",
+      "âļ £",
+      "â² ¢",
+      "ãĪ ª",
+      "ä¶ µ",
+      "ê² Ļ",
+      "ê² ´",
+      "ê³ Ĥ",
+      "ë¡ ¼",
+      "ìĨ Ĭ",
+      "ì¼ ĩ",
+      "íĭ į",
+      "íĵ ¬",
+      "íĵ ®",
+      "íĵ ¶",
+      "íĵ »",
+      "ï¤ ¦",
+      "ï¥ ł",
+      "ï¥ ±",
+      "ïŃ ²",
+      "ðIJŃ Ĭ",
+      "ðIJ ±ħ",
+      "ðĸ ¥",
+      "ðĸ¥ ¨",
+      "ðĿij ³",
+      "ðĿĵ ķ",
+      "ðĿĵ ¬",
+      "ðĿĵ ¹",
+      "ðĿĵ ¾",
+      "ðĿĶ ĵ",
+      "ðĿķ į",
+      "ðĿķ ¡",
+      "ðĿķ ±",
+      "ðĿĸ ĸ",
+      "ðĿĺ ı",
+      "ðĿĺ IJ",
+      "ðĿĺ ļ",
+      "ðĿĻ ®",
+      "ðĿĻ °",
+      "ðĿĻ ¸",
+      "ðĿĻ º",
+      "ðĿĻ ¼",
+      "ðĿĻ ½",
+      "ðĿĻ ¿",
+      "ðĿļ Ħ",
+      "ðĿļ ı",
+      "ðŁħ ħ",
+      "ðŁħ ĵ",
+      "Æ Ī",
+      "àł Į",
+      "áĻ ³",
+      "á ļĮ",
+      "ἠħ",
+      "ἠIJ",
+      "ᤠĬ",
+      "ḠĬ",
+      "âĶ ½",
+      "âķ Ĭ",
+      "⼠ĩ",
+      "⼠ı",
+      "âĿ ª",
+      "âĿ «",
+      "⣠°",
+      "ãĦ į",
+      "ãĦ ĵ",
+      "ãĦ §",
+      "ãħ ĸ",
+      "ãī «",
+      "ê¦ Ķ",
+      "ï± Ĭ",
+      "ຠĤ",
+      "áħ £",
+      "ᥠĶ",
+      "ᥠ¤",
+      "âĨ ¤",
+      "âĨ ·",
+      "âĩ ŀ",
+      "âĸ ¤",
+      "âŀ ¶",
+      "ãĪ ¼",
+      "ï¨ ·",
+      "ðĵı §",
+      "âĶ ²",
+      "âĢ ´",
+      "âĴ Ł",
+      "âĴ ¡",
+      "â° Ĥ",
+      "â° į",
+      "â° İ",
+      "â° IJ",
+      "â° ij",
+      "â° Ł",
+      "â° ł",
+      "â° ¡",
+      "â¼ Ń",
+      "ãĬ ¥",
+      "âĴ ł",
+      "â½ º",
+      "ãĩ º",
+      "ãĩ ½",
+      "ï¨ Ĭ",
+      "áķ ·",
+      "âį ¨",
+      "⺠Ł",
+      "â½ Ĺ"
+    ]
+  }
+}
\ No newline at end of file
diff --git a/audio/tokenizer_config.json b/audio/tokenizer_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..ed3cd6a8402e69e6a4d8b4c3f381d55e7bdbeb03
--- /dev/null
+++ b/audio/tokenizer_config.json
@@ -0,0 +1,29610 @@
+{
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151646": {
+      "content": "<|AUDIO|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151647": {
+      "content": "<|audio_bos|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151648": {
+      "content": "<|audio_eos|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151649": {
+      "content": "<|sil|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151650": {
+      "content": "<|0.00|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151651": {
+      "content": "<|0.01|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151652": {
+      "content": "<|0.02|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151653": {
+      "content": "<|0.03|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151654": {
+      "content": "<|0.04|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151655": {
+      "content": "<|0.05|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151656": {
+      "content": "<|0.06|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151657": {
+      "content": "<|0.07|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151658": {
+      "content": "<|0.08|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151659": {
+      "content": "<|0.09|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151660": {
+      "content": "<|0.10|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151661": {
+      "content": "<|0.11|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151662": {
+      "content": "<|0.12|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151663": {
+      "content": "<|0.13|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151664": {
+      "content": "<|0.14|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151665": {
+      "content": "<|0.15|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151666": {
+      "content": "<|0.16|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151667": {
+      "content": "<|0.17|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151668": {
+      "content": "<|0.18|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151669": {
+      "content": "<|0.19|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151670": {
+      "content": "<|0.20|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151671": {
+      "content": "<|0.21|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151672": {
+      "content": "<|0.22|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151673": {
+      "content": "<|0.23|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151674": {
+      "content": "<|0.24|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151675": {
+      "content": "<|0.25|>",
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diff --git a/base/IXC2d5_clip_l_560/config.json b/base/IXC2d5_clip_l_560/config.json
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+{
+  "_name_or_path": "/mnt/petrelfs/dongxiaoyi/gittest/IXC/output/clip_l_560_pro7b/",
+  "architectures": [
+    "CLIPVisionModel"
+  ],
+  "attention_dropout": 0.0,
+  "dropout": 0.0,
+  "hidden_act": "quick_gelu",
+  "hidden_size": 1024,
+  "image_size": 560,
+  "initializer_factor": 1.0,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "layer_norm_eps": 1e-05,
+  "model_type": "clip_vision_model",
+  "num_attention_heads": 16,
+  "num_channels": 3,
+  "num_hidden_layers": 24,
+  "patch_size": 14,
+  "projection_dim": 768,
+  "torch_dtype": "float32",
+  "transformers_version": "4.33.1"
+}
diff --git a/base/IXC2d5_clip_l_560/preprocessor_config.json b/base/IXC2d5_clip_l_560/preprocessor_config.json
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+{
+  "crop_size": 560,
+  "do_center_crop": true,
+  "do_normalize": true,
+  "do_resize": true,
+  "feature_extractor_type": "CLIPFeatureExtractor",
+  "image_mean": [
+    0.48145466,
+    0.4578275,
+    0.40821073
+  ],
+  "image_std": [
+    0.26862954,
+    0.26130258,
+    0.27577711
+  ],
+  "resample": 3,
+  "size": 560
+}
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+version https://git-lfs.github.com/spec/v1
+oid sha256:f2345623c2fe3bd46d9251d7dfdbfc8d55cea5411a1e42940ee15cde730d45c4
+size 1218353513
diff --git a/base/README.md b/base/README.md
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index 0000000000000000000000000000000000000000..ebadfeb8ef796b561dc6cb8fb20047ca64bb2685
--- /dev/null
+++ b/base/README.md
@@ -0,0 +1,290 @@
+---
+license: other
+pipeline_tag: visual-question-answering
+---
+
+
+<p align="center">
+    <img src="logo_en.png" width="600"/>
+<p>
+
+<p align="center">
+    <b><font size="6">InternLM-XComposer-2.5</font></b> 
+<p>
+
+<div align="center">
+
+[💻Github Repo](https://github.com/InternLM/InternLM-XComposer)
+
+[Online Demo](https://huggingface.co/spaces/Willow123/InternLM-XComposer)
+
+[Paper](https://huggingface.co/papers/2407.03320)
+
+</div>
+
+**InternLM-XComposer2.5** excels in various text-image comprehension and composition applications, achieving GPT-4V level capabilities with merely 7B LLM backend. IXC2.5 is trained with 24K interleaved image-text contexts, it can seamlessly extend to 96K long contexts via RoPE extrapolation. This long-context capability allows IXC-2.5 to excel in tasks requiring extensive input and output contexts. 
+
+
+### Import from Transformers
+To load the InternLM-XComposer2-4KHD model using Transformers, use the following code:
+```python
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+ckpt_path = "internlm/internlm-xcomposer2d5-7b"
+tokenizer = AutoTokenizer.from_pretrained(ckpt_path, trust_remote_code=True).cuda()
+# Set `torch_dtype=torch.floatb16` to load model in bfloat16, otherwise it will be loaded as float32 and might cause OOM Error.
+model = AutoModelForCausalLM.from_pretrained(ckpt_path, torch_dtype=torch.bfloat16, trust_remote_code=True).cuda()
+model = model.eval()
+```
+
+## Quickstart
+
+We provide a simple example to show how to use InternLM-XComposer2.5 with 🤗 Transformers. 
+
+<details>
+  <summary>
+    <b>Video Understanding</b>
+  </summary>
+
+```python
+import torch
+from transformers import AutoModel, AutoTokenizer
+
+torch.set_grad_enabled(False)
+
+# init model and tokenizer
+model = AutoModel.from_pretrained('internlm/internlm-xcomposer2d5-7b', torch_dtype=torch.bfloat16, trust_remote_code=True).cuda().eval()
+tokenizer = AutoTokenizer.from_pretrained('internlm/internlm-xcomposer2d5-7b', trust_remote_code=True)
+model.tokenizer = tokenizer
+
+query = 'Here are some frames of a video. Describe this video in detail'
+image = ['./examples/liuxiang.mp4',]
+with torch.autocast(device_type='cuda', dtype=torch.float16):
+    response, his = model.chat(tokenizer, query, image, do_sample=False, num_beams=3, use_meta=True)
+print(response)
+#The video opens with a shot of an athlete, dressed in a red and yellow uniform with the word "CHINA" emblazoned across the front, preparing for a race. 
+#The athlete, Liu Xiang, is seen in a crouched position, focused and ready, with the Olympic rings visible in the background, indicating the prestigious setting of the Olympic Games. As the race commences, the athletes are seen sprinting towards the hurdles, their determination evident in their powerful strides. 
+#The camera captures the intensity of the competition, with the athletes' numbers and times displayed on the screen, providing a real-time update on their performance. The race reaches a climax as Liu Xiang, still in his red and yellow uniform, triumphantly crosses the finish line, his arms raised in victory. 
+#The crowd in the stands erupts into cheers, their excitement palpable as they witness the athlete's success. The video concludes with a close-up shot of Liu Xiang, still basking in the glory of his victory, as the Olympic rings continue to symbolize the significance of the event.
+
+query = 'tell me the athlete code of Liu Xiang'
+image = ['./examples/liuxiang.mp4',]
+with torch.autocast(device_type='cuda', dtype=torch.float16):
+    response, _ = model.chat(tokenizer, query, image, history=his, do_sample=False, num_beams=3, use_meta=True)
+print(response)
+#The athlete code of Liu Xiang, as displayed on his uniform in the video, is "1363".
+```
+
+</details>
+
+<details>
+  <summary>
+    <b>Multi-Image Mutli-Tune Dialog</b>
+  </summary>
+
+```python
+import torch
+from transformers import AutoModel, AutoTokenizer
+
+torch.set_grad_enabled(False)
+
+# init model and tokenizer
+model = AutoModel.from_pretrained('internlm/internlm-xcomposer2d5-7b', torch_dtype=torch.bfloat16, trust_remote_code=True).cuda().eval()
+tokenizer = AutoTokenizer.from_pretrained('internlm/internlm-xcomposer2d5-7b', trust_remote_code=True)
+model.tokenizer = tokenizer
+
+query = 'Image1 <ImageHere>; Image2 <ImageHere>; Image3 <ImageHere>; I want to buy a car from the three given cars, analyze their advantages and weaknesses one by one'
+image = ['./examples/cars1.jpg',
+        './examples/cars2.jpg',
+        './examples/cars3.jpg',]
+with torch.autocast(device_type='cuda', dtype=torch.float16):
+    response, his = model.chat(tokenizer, query, image, do_sample=False, num_beams=3, use_meta=True)
+print(response)
+#To analyze the advantages and disadvantages of each car, we need to consider factors such as brand reputation, performance, design, cost, and maintenance. 
+#1. Mercedes-Benz: - Advantages: Known for its luxury and reliability, the Mercedes-Benz brand offers a high level of comfort, advanced technology, and superior craftsmanship. The vehicle in the image appears to be an SUV, which is versatile for both city driving and off-road conditions. - Disadvantages: Typically, Mercedes-Benz vehicles are more expensive compared to other brands, and they may require more frequent maintenance due to their luxury status. 
+#2. Bugatti: - Advantages: Bugatti is renowned for producing some of the fastest and most powerful cars in the world. The vehicle in the image is a sports car, likely offering an exhilarating driving experience with its high-performance engine and advanced aerodynamics. - Disadvantages: Bugatti cars are extremely expensive, making them less accessible to the average consumer. They also require specialized knowledge for maintenance and may not be suitable for everyday driving due to their high-performance nature. 
+#3. BMW: - Advantages: BMW is a well-respected manufacturer known for its innovative engineering and design. The car in the image appears to be an electric vehicle (EV), which offers advantages such as lower emissions, reduced noise pollution, and potentially lower operating costs. - Disadvantages: EVs like the one in the image may have a shorter range compared to traditional gasoline-powered vehicles, limiting their suitability for long-distance travel. 
+#Additionally, the initial cost of purchasing an EV can be higher than that of a conventional car. In conclusion, each car has its own set of advantages and disadvantages. The Mercedes-Benz offers luxury and versatility, the Bugatti provides high performance and exclusivity, and the BMW represents innovation in electric vehicle technology. The choice ultimately depends on the buyer's priorities, such as comfort, performance, environmental impact, and budget.
+
+query = 'Image4 <ImageHere>; How about the car in Image4'
+image.append('./examples/cars4.jpg')        
+with torch.autocast(device_type='cuda', dtype=torch.float16):
+    response, _ = model.chat(tokenizer, query, image, do_sample=False, num_beams=3, history= his, use_meta=True)
+print(response)
+#The car in Image4 is a red sports car, which appears to be a Ferrari. Ferrari is a renowned Italian manufacturer known for producing some of the most iconic and high-performance sports cars in the world. - Advantages: Ferrari vehicles are synonymous with speed, luxury, and engineering excellence. 
+#The car in the image likely offers an exhilarating driving experience with its powerful engine, advanced aerodynamics, and high-quality craftsmanship. The red color adds to the car's aesthetic appeal, making it stand out on the road. - Disadvantages: Ferrari cars are extremely expensive, making them less accessible to the average consumer. 
+#They also require specialized knowledge for maintenance and may not be suitable for everyday driving due to their high-performance nature. In conclusion, the Ferrari in Image4 represents a pinnacle of automotive engineering and design, offering unmatched performance and luxury. 
+#However, its high cost and specialized maintenance requirements make it less practical for everyday use compared to the other vehicles in the images.
+```
+
+
+</details>
+
+<details>
+  <summary>
+    <b>High Resolution Image Understanding</b>
+  </summary>
+
+```python
+import torch
+from transformers import AutoModel, AutoTokenizer
+
+torch.set_grad_enabled(False)
+
+# init model and tokenizer
+model = AutoModel.from_pretrained('internlm/internlm-xcomposer2d5-7b', torch_dtype=torch.bfloat16, trust_remote_code=True).cuda().eval()
+tokenizer = AutoTokenizer.from_pretrained('internlm/internlm-xcomposer2d5-7b', trust_remote_code=True)
+model.tokenizer = tokenizer
+
+query = 'Analyze the given image in a detail manner'
+image = ['./examples/dubai.png']
+with torch.autocast(device_type='cuda', dtype=torch.float16):
+    response, _ = model.chat(tokenizer, query, image, do_sample=False, num_beams=3, use_meta=True)
+print(response)
+#The infographic is a visual representation of various facts about Dubai. It begins with a statement about Palm Jumeirah, highlighting it as the largest artificial island visible from space. It then provides a historical context, noting that in 1968, there were only a few cars in Dubai, contrasting this with the current figure of more than 1.5 million vehicles. 
+#The infographic also points out that Dubai has the world's largest Gold Chain, with 7 of the top 10 tallest hotels located there. Additionally, it mentions that the crime rate is near 0%, and the income tax rate is also 0%, with 20% of the world's total cranes operating in Dubai. Furthermore, it states that 17% of the population is Emirati, and 83% are immigrants.
+#The Dubai Mall is highlighted as the largest shopping mall in the world, with 1200 stores. The infographic also notes that Dubai has no standard address system, with no zip codes, area codes, or postal services. It mentions that the Burj Khalifa is so tall that its residents on top floors need to wait longer to break fast during Ramadan. 
+#The infographic also includes information about Dubai's climate-controlled City, with the Royal Suite at Burj Al Arab costing $24,000 per night. Lastly, it notes that the net worth of the four listed billionaires is roughly equal to the GDP of Honduras.
+
+```
+
+</details>
+
+
+<details>
+  <summary>
+    <b>Instruction to Webpage</b>
+  </summary>
+
+```python
+import torch
+from transformers import AutoModel, AutoTokenizer
+
+torch.set_grad_enabled(False)
+
+# init model and tokenizer
+model = AutoModel.from_pretrained('internlm/internlm-xcomposer2d5-7b', torch_dtype=torch.bfloat16, trust_remote_code=True).cuda().eval()
+tokenizer = AutoTokenizer.from_pretrained('internlm/internlm-xcomposer2d5-7b', trust_remote_code=True)
+model.tokenizer = tokenizer
+
+query = 'A website for Research institutions. The name is Shanghai AI lab. Top Navigation Bar is blue.Below left, an image shows the logo of the lab. In the right, there is a passage of text below that describes the mission of the laboratory.There are several images to show the research projects of Shanghai AI lab.'
+with torch.autocast(device_type='cuda', dtype=torch.float16):
+    response = model.write_webpage(query, seed=202, task='Instruction-aware Webpage Generation', repetition_penalty=3.0)
+print(response)
+# see the Instruction-aware Webpage Generation.html 
+```
+ 
+See the [Instruction to Webpage](https://github.com/InternLM/InternLM-XComposer/blob/main/examples/Instruction-aware_Webpage_Generation.html) results here.
+</details>
+
+<details>
+  <summary>
+    <b>Resume to Webpage</b>
+  </summary>
+
+```python
+import torch
+from transformers import AutoModel, AutoTokenizer
+
+torch.set_grad_enabled(False)
+
+# init model and tokenizer
+model = AutoModel.from_pretrained('internlm/internlm-xcomposer2d5-7b', torch_dtype=torch.bfloat16, trust_remote_code=True).cuda().eval()
+tokenizer = AutoTokenizer.from_pretrained('internlm/internlm-xcomposer2d5-7b', trust_remote_code=True)
+model.tokenizer = tokenizer
+
+## the input should be a resume in markdown format
+query = './examples/resume.md'
+with torch.autocast(device_type='cuda', dtype=torch.float16):
+    response = model.resume_2_webpage(query, seed=202, repetition_penalty=3.0)
+print(response)
+```
+See the [Resume to Webpage](https://github.com/InternLM/InternLM-XComposer/blob/main/examples/Resume-to-Personal_Page.html) results here.
+
+
+</details>
+
+
+<details>
+  <summary>
+    <b>Screenshot to Webpage</b>
+  </summary>
+
+```python
+import torch
+from transformers import AutoModel, AutoTokenizer
+
+torch.set_grad_enabled(False)
+
+# init model and tokenizer
+model = AutoModel.from_pretrained('internlm/internlm-xcomposer2d5-7b', torch_dtype=torch.bfloat16, trust_remote_code=True).cuda().eval()
+tokenizer = AutoTokenizer.from_pretrained('internlm/internlm-xcomposer2d5-7b', trust_remote_code=True)
+model.tokenizer = tokenizer
+
+query = 'Generate the HTML code of this web image with Tailwind CSS.'
+image = ['./examples/screenshot.jpg']
+with torch.autocast(device_type='cuda', dtype=torch.float16):
+    response = model.screen_2_webpage(query, image, seed=202, repetition_penalty=3.0)
+print(response)
+```
+See the [Screenshot to Webpage](https://github.com/InternLM/InternLM-XComposer/blob/main/examples/Screenshot-to-Webpage.html) results here.
+
+</details>
+
+
+
+<details>
+  <summary>
+    <b>Write Article</b>
+  </summary>
+
+```python
+import torch
+from transformers import AutoModel, AutoTokenizer
+
+torch.set_grad_enabled(False)
+
+# init model and tokenizer
+model = AutoModel.from_pretrained('internlm/internlm-xcomposer2d5-7b', torch_dtype=torch.bfloat16, trust_remote_code=True).cuda().eval()
+tokenizer = AutoTokenizer.from_pretrained('internlm/internlm-xcomposer2d5-7b', trust_remote_code=True)
+model.tokenizer = tokenizer
+
+query = '阅读下面的材料，根据要求写作。 电影《长安三万里》的出现让人感慨，影片并未将重点全落在大唐风华上，也展现了恢弘气象的阴暗面，即旧门阀的资源垄断、朝政的日益衰败与青年才俊的壮志难酬。高适仕进无门，只能回乡>沉潜修行。李白虽得玉真公主举荐，擢入翰林，但他只是成为唐玄宗的御用文人，不能真正实现有益于朝政的志意。然而，片中高潮部分《将进酒》一节，人至中年、挂着肚腩的李白引众人乘仙鹤上天，一路从水面、瀑布飞升至银河进入仙>宫，李白狂奔着与仙人们碰杯，最后大家纵身飞向漩涡般的九重天。肉身的微贱、世路的“天生我材必有用，坎坷，拘不住精神的高蹈。“天生我材必有用，千金散尽还复来。” 古往今来，身处闲顿、遭受挫折、被病痛折磨，很多人都曾经历>了人生的“失意”，却反而成就了他们“诗意”的人生。对正在追求人生价值的当代青年来说，如何对待人生中的缺憾和困顿?诗意人生中又有怎样的自我坚守和自我认同?请结合“失意”与“诗意”这两个关键词写一篇文章。 要求:选准角度，确定>立意，明确文体，自拟标题;不要套作，不得抄袭;不得泄露个人信息;不少于 800 字。'
+with torch.autocast(device_type='cuda', dtype=torch.float16):
+    response = model.write_artical(query, seed=8192)
+print(response)
+#诗意人生，贵在坚守
+#《菜根谭》有云:“闲时要有吃紧的心思,忙里要留吃闲工夫。”人生在世,总有失意之时,当面对缺憾和困顿,诗意地生活着才能为人生增添一抹亮色。何谓诗意地生活? 所谓诗意地生活，便是在于坚守本心、直面遗憾、超越自我,在失意中寻找人生价值。
+#诗意地生活,需坚守本心,淡然处之。
+#陶渊明曾执意辞去彭泽县令,归隐田园,“采菊东篱下,悠然见南山”,在山水间寄情自娱；王维面对仕途失意,终日沉醉于诗酒之中,“兴来每独往,胜事空自知”,在诗酒中闲逸自如;李白仕途不顺,被赐金放还,但他依旧豪气干云,“天生我才必有用,千金散尽还复来”,在失意中坦然豁达。坚守本心，便能在遭遇失意之时守住自己的精神家园,让生活充满诗意。反之,若不能坚守本心,而只是一味迎合世俗以求得升迁,那纵使身居高位,亦会丧失生活的乐趣。
+#诗意地生活,需直面遗憾,超越自我。
+#“西塞山前白鹭飞,桃花流水鳜鱼肥。青箬笠,绿柳枝,半斤酒,一纶丝。五湖四海皆如此,何妨到此处归。”白居易的《渔歌子》写出了多少人的愿望:没有权势纷扰,没有贫困凄凉,只有青山绿水、白鹭鸥鸟作伴,如此自由自在的生活令人神往。然而,白居易却并没有因此真的归隐山林,而是直面人生,超越自我,写下了一首首诗意而富有现实关怀的作品。如果白居易只顾逃避人生,那又怎会拥有“大弦嘈嘈如急雨,小弦切切如私语”的绝美比喻呢?如果白居易只顾归隐山林,那又怎会写出“此曲只应天上有,人间哪得配白居易”这样的诗句呢?
+#诗意地生活,需直面遗憾,坚守本心。
+#李文波患有渐冻症,医生说他活不过五年,但他没有因此放弃对音乐的热爱,而是与病魔作斗争,演奏出美妙的乐曲;孙家林自幼患有脑瘫,但他不甘于命运的捉弄,终成全国最美教师;史铁生饱受疾病折磨,但他仍能发出“我常常在我的心头清点,我有什么?”的叩问,并由此走上文学道路,为后世留下丰厚的文化遗产。这些人没有逃避,而是选择直面人生的缺憾,在坚守本心的同时超越自我,最终实现了自己的价值。
+#诗意地生活,是于失意中坚守本心,于缺憾中超越自我。当面对人生的缺憾与挫折,坚守本心、超越自我的同时,也必将书写属于自己的辉煌篇章。
+#愿你我都能诗意地生活着!
+
+query = 'Please write a blog based on the title: French Pastries: A Sweet Indulgence'
+with torch.autocast(device_type='cuda', dtype=torch.float16):
+    response = model.write_artical(query, seed=8192)
+print(response)
+#French Pastries: A Sweet Indulgence
+#The French are well known for their love of pastries, and it’s a love that is passed down through generations. When one visits France, they are treated to an assortment of baked goods that can range from the delicate macaron to the rich and decadent chocolate mousse. While there are many delicious types of pastries found in France, five stand out as being the most iconic. Each of these pastries has its own unique qualities that make it special.
+#1. Croissant
+#One of the most famous pastries from France is the croissant. It is a buttery, flaky pastry that is best enjoyed fresh from the bakery. The dough is laminated with butter, giving it its signature layers. Croissants are typically eaten for breakfast or brunch, often accompanied by coffee or hot chocolate.
+#2. Macaron
+#The macaron is a small, delicate French confection made from almond flour, powdered sugar, and egg whites. The macaron itself is sandwiched with a ganache or jam filling. They come in a variety of colors and flavors, making them a popular choice for both casual snacking and upscale desserts.
+#3. Madeleine
+#The madeleine is a small shell-shaped cake that is light and sponge-like. It is often flavored with lemon or orange zest and sometimes dipped in chocolate. Madeleines are perfect for an afternoon snack with tea or coffee.
+#4. Éclair
+#The éclair is a long, thin pastry filled with cream and topped with chocolate glaze. It is a classic French treat that is both sweet and satisfying. Éclairs can be found in bakeries all over France and are often enjoyed with a cup of hot chocolate.
+#5. Tarte Tatin
+#The tarte Tatin is an apple tart that is known for its caramelized apples and puff pastry crust. It is named after the Tatin sisters who created the recipe in the late 19th century. Tarte Tatin is best served warm with a scoop of vanilla ice cream.
+#These pastries are just a few of the many delicious treats that France has to offer. Whether you are a seasoned traveler or a first-time visitor, indulging in French pastries is a must-do activity. So go ahead, treat yourself—you deserve it!
+```
+
+</details>
+
+
+### Open Source License
+The code is licensed under Apache-2.0, while model weights are fully open for academic research and also allow free commercial usage. To apply for a commercial license, please fill in the application form (English)/申请表（中文）. For other questions or collaborations, please contact internlm@pjlab.org.cn.
\ No newline at end of file
diff --git a/base/SimHei.ttf b/base/SimHei.ttf
new file mode 100644
index 0000000000000000000000000000000000000000..94794236612d827dfc6800269b43c6e3ad1fc513
--- /dev/null
+++ b/base/SimHei.ttf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:336a838f4a78e150826be608dae69de59d50948c3d2b71760e096ae764154bdc
+size 9751960
diff --git a/base/__pycache__/build_mlp.cpython-39.pyc b/base/__pycache__/build_mlp.cpython-39.pyc
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diff --git a/base/added_tokens.json b/base/added_tokens.json
new file mode 100644
index 0000000000000000000000000000000000000000..39090265148ac44e5d5ce46e69594ac3ad34b1e5
--- /dev/null
+++ b/base/added_tokens.json
@@ -0,0 +1,8 @@
+{
+  "<|action_end|>": 92547,
+  "<|action_start|>": 92546,
+  "<|im_end|>": 92545,
+  "<|im_start|>": 92544,
+  "<|interpreter|>": 92548,
+  "<|plugin|>": 92549
+}
diff --git a/base/build_mlp.py b/base/build_mlp.py
new file mode 100644
index 0000000000000000000000000000000000000000..461a201af27a1b2907b6ee272b4ebf982d01e730
--- /dev/null
+++ b/base/build_mlp.py
@@ -0,0 +1,230 @@
+import torch
+import torch.nn as nn
+import re
+import math
+from transformers import CLIPVisionModel, CLIPImageProcessor, CLIPVisionConfig
+
+
+def build_vision_tower():
+    vision_tower = 'internlm-xcomposer2d5-ol-7b/base/IXC2d5_clip_l_560'
+    return CLIPVisionTower(vision_tower)
+
+
+def build_vision_projector(input_dim=4096):
+    projector_type = 'mlp2x_gelu'
+    mm_hidden_size = input_dim
+    mid_hidden_size = 4096
+    hidden_size = 4096
+
+    mlp_gelu_match = re.match(r'^mlp(\d+)x_gelu$', projector_type)
+    if mlp_gelu_match:
+        mlp_depth = int(mlp_gelu_match.group(1))
+        modules = [nn.Linear(mm_hidden_size, mid_hidden_size)]
+        for _ in range(1, mlp_depth):
+            modules.append(nn.GELU())
+            modules.append(nn.Linear(mid_hidden_size, mid_hidden_size))
+
+        return nn.Sequential(*modules)
+
+    if projector_type == 'identity':
+        return IdentityMap()
+
+    raise ValueError(f'Unknown projector type: {projector_type}')
+
+
+class IdentityMap(nn.Module):
+    def __init__(self):
+        super().__init__()
+
+    def forward(self, x, *args, **kwargs):
+        return x
+
+    @property
+    def config(self):
+        return {"mm_projector_type": 'identity'}
+
+
+class CLIPVisionTower(nn.Module):
+    def __init__(self, vision_tower):
+        super().__init__()
+
+        self.is_loaded = False
+
+        self.vision_tower_name = vision_tower
+        # self.conv_dim = 8192
+        # self.conv = torch.nn.Conv2d(1024, self.conv_dim,3,2,1)
+        self.select_layer = -1
+        self.select_feature = 'patch'
+        self.load_model()
+
+    def load_model(self):
+        self.vision_tower = CLIPVisionModel.from_pretrained(self.vision_tower_name)
+        self.vision_tower.requires_grad_(False)
+
+        self.is_loaded = True
+
+    def resize_pos(self):
+        print('Dummy Resized')
+
+    def feature_select(self, image_forward_outs):
+        image_features = image_forward_outs.hidden_states[self.select_layer]
+        if self.select_feature == 'patch':
+            image_features = image_features[:, 1:]
+        elif self.select_feature == 'cls_patch':
+            image_features = image_features
+        else:
+            raise ValueError(f'Unexpected select feature: {self.select_feature}')
+        return image_features
+
+    def forward(self, images, glb_GN, sub_GN):
+        if not self.is_loaded:
+            self.load_model()
+        assert type(images) is list
+        shapes = []
+        input_imgs = []
+        for img in images:
+            _, C, H, W = img.shape
+            shapes.append([H // 560, W // 560])
+            sub_img = img.reshape(1, 3, H // 560, 560, W // 560, 560).permute(0, 2, 4, 1, 3, 5).reshape(-1, 3, 560,
+                                                                                                        560).contiguous()
+            glb_img = torch.nn.functional.interpolate(img.float(), size=(560, 560), mode='bicubic', ).to(sub_img.dtype)
+            input_imgs.append(glb_img)
+            input_imgs.append(sub_img)
+        input_imgs = torch.cat(input_imgs, dim=0)
+        '''
+        if input_imgs.shape[0] > 50:
+            image_f_1 = self.vision_tower(input_imgs[:50].to(device=self.device, dtype=self.dtype), output_hidden_states=True).hidden_states[self.select_layer][:, 1:]
+            with torch.no_grad():
+                image_f_2 = self.vision_tower(input_imgs[50:].to(device=self.device, dtype=self.dtype), output_hidden_states=True).hidden_states[self.select_layer][:, 1:]
+            image_features = torch.cat([image_f_1, image_f_2], dim=0).to(input_imgs.dtype)
+
+        else:
+            image_features = self.vision_tower(input_imgs.to(device=self.device, dtype=self.dtype), output_hidden_states=True).hidden_states[self.select_layer][:, 1:].to(input_imgs.dtype)
+        '''
+        image_features = \
+        self.vision_tower(input_imgs.to(device=self.device, dtype=self.dtype), output_hidden_states=True).hidden_states[
+            self.select_layer][:, 1:].to(input_imgs.dtype)
+        _, N, C = image_features.shape
+        H = int(math.sqrt(N))
+        assert N == 40 ** 2
+
+        output_imgs = []
+        output_len = []
+        for [h, w] in shapes:
+            B_ = h * w
+            glb_img = image_features[:1]  ### 1, N, C
+            glb_img = glb_img.reshape(1, H, H, C).reshape(1, H // 2, 2, H // 2, 2, C).contiguous().permute(0, 1, 3, 2,
+                                                                                                           4,
+                                                                                                           5).reshape(1,
+                                                                                                                      H // 2,
+                                                                                                                      H // 2,
+                                                                                                                      4 * C).contiguous()
+            temp_glb_GN = sub_GN.repeat(1, H // 2, 1, 1)
+            glb_img = torch.cat([glb_img, temp_glb_GN], dim=2).reshape(1, -1, 4 * C)
+
+            sub_img = image_features[1:1 + B_]  ### ?, N, C
+            sub_img = sub_img.reshape(B_, H, H, C).reshape(B_, H // 2, 2, H // 2, 2, C).contiguous().permute(0, 1, 3, 2,
+                                                                                                             4,
+                                                                                                             5).reshape(
+                B_, -1, 4 * C).contiguous()
+            sub_img = sub_img.reshape(1, h, w, 20, 20, -1).permute(0, 1, 3, 2, 4, 5).reshape(1, h * 20, w * 20, 4 * C)
+            temp_sub_GN = sub_GN.repeat(1, h * 20, 1, 1)
+            sub_img = torch.cat([sub_img, temp_sub_GN], dim=2).reshape(1, -1, 4 * C)
+
+            output_imgs.append(torch.cat([glb_img, glb_GN, sub_img], dim=1))
+            temp_len = int((h * w + 1) * 400 + 1 + (h + 1) * 20)
+            assert temp_len == output_imgs[-1].shape[1]
+            output_len.append(temp_len)
+
+            image_features = image_features[1 + h * w:]
+
+        output_imgs = torch.cat(output_imgs, dim=1)
+
+        return output_imgs, output_len
+
+    @property
+    def dummy_feature(self):
+        return torch.zeros(1, self.hidden_size, device=self.device, dtype=self.dtype)
+
+    @property
+    def dtype(self):
+        return self.vision_tower.dtype
+
+    @property
+    def device(self):
+        return self.vision_tower.device
+
+    @property
+    def config(self):
+        if self.is_loaded:
+            return self.vision_tower.config
+        else:
+            return self.cfg_only
+
+    @property
+    def hidden_size(self):
+        return self.config.hidden_size
+
+    @property
+    def num_patches(self):
+        return (self.config.image_size // self.config.patch_size) ** 2
+
+
+class PLoRA(nn.Linear):
+    def __init__(self,
+                 in_features: int,
+                 out_features: int,
+                 bias: bool = True,
+                 device=None,
+                 dtype=None,
+                 lora_r=8,
+                 lora_alpha=16,
+                 lora_dropout=0.05,
+                 lora_len=0,
+                 **kwargs) -> None:
+        super().__init__(in_features, out_features, bias, device, dtype)
+        self.lora_r = lora_r
+        self.lora_alpha = lora_alpha
+        self.lora_len = lora_len
+        if lora_dropout > 0.:
+            self.lora_dropout = nn.Dropout(p=lora_dropout)
+        else:
+            self.lora_dropout = lambda x: x
+        self.lora_scaling = self.lora_alpha / self.lora_r
+
+        self.Plora_A = nn.Linear(in_features,
+                                 self.lora_r,
+                                 bias=False,
+                                 device=device,
+                                 dtype=dtype)
+        self.Plora_B = nn.Linear(self.lora_r,
+                                 out_features,
+                                 bias=False,
+                                 device=device,
+                                 dtype=dtype)
+
+        self.reset_parameters()
+
+    def reset_parameters(self):
+        if hasattr(self, 'lora_A'):
+            # initialize A the same way as the default for nn.Linear and B to zero
+            nn.init.kaiming_uniform_(self.lora_A.weight, a=math.sqrt(5))
+            nn.init.zeros_(self.lora_B.weight)
+            # print ("lora weight init {} {}".format(torch.mean(self.lora_A.weight), torch.mean(self.lora_B.weight)))
+
+    def forward(self, x, im_mask=None):
+        B, N, C = x.shape
+        im_mask = im_mask.view(-1)
+        x = x.reshape(-1, C)
+        res = super().forward(x)
+        if im_mask is not None:
+            if torch.sum(im_mask) > 0:
+                part_x = x[im_mask]
+                res[im_mask] += self.Plora_B(self.Plora_A(
+                    self.lora_dropout(part_x))) * self.lora_scaling
+            else:
+                part_x = x[:1]
+                res[:1] += self.Plora_B(self.Plora_A(
+                    self.lora_dropout(part_x))) * 0
+
+        return res.reshape(B, N, -1)
diff --git a/base/config.json b/base/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..48407a58db4821f15eebed4c740a85764129ea5c
--- /dev/null
+++ b/base/config.json
@@ -0,0 +1,36 @@
+{
+  "architectures": [
+    "InternLMXComposer2ForCausalLM"
+  ],
+  "attn_implementation": "flash_attention_2",
+  "auto_map": {
+    "AutoConfig": "configuration_internlm_xcomposer2.InternLMXcomposer2Config",
+    "AutoModel": "modeling_internlm_xcomposer2.InternLMXComposer2ForCausalLM",
+    "AutoModelForCausalLM": "modeling_internlm_xcomposer2.InternLMXComposer2ForCausalLM"
+  },
+  "bias": false,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_length": 16384,
+  "max_position_embeddings": 24576,
+  "model_type": "internlm2",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pad_token_id": 2,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
+    "type": "dynamic",
+    "factor": 2.0
+  },
+  "rope_theta": 1000000,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.33.1",
+  "use_cache": false,
+  "vocab_size": 92544
+}
diff --git a/base/configuration_internlm_xcomposer2.py b/base/configuration_internlm_xcomposer2.py
new file mode 100644
index 0000000000000000000000000000000000000000..2c367130b869d64c095d7f510b3804ebd61737f3
--- /dev/null
+++ b/base/configuration_internlm_xcomposer2.py
@@ -0,0 +1,150 @@
+# coding=utf-8
+# Copyright (c) The InternLM team and The HuggingFace Inc. team. All rights reserved.
+#
+# This code is based on transformers/src/transformers/models/llama/configuration_llama.py
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+""" InternLM2 model configuration"""
+
+from transformers.configuration_utils import PretrainedConfig
+from transformers.utils import logging
+
+logger = logging.get_logger(__name__)
+
+INTERNLM2_PRETRAINED_CONFIG_ARCHIVE_MAP = {}
+
+
+class InternLMXcomposer2Config(PretrainedConfig):
+    r"""
+    This is the configuration class to store the configuration of a [`InternLM2Model`]. It is used to instantiate
+    an InternLM2 model according to the specified arguments, defining the model architecture. Instantiating a
+    configuration with the defaults will yield a similar configuration to that of the InternLM2-7B.
+
+    Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
+    documentation from [`PretrainedConfig`] for more information.
+
+
+    Args:
+        vocab_size (`int`, *optional*, defaults to 32000):
+            Vocabulary size of the InternLM2 model. Defines the number of different tokens that can be represented by the
+            `inputs_ids` passed when calling [`InternLM2Model`]
+        hidden_size (`int`, *optional*, defaults to 4096):
+            Dimension of the hidden representations.
+        intermediate_size (`int`, *optional*, defaults to 11008):
+            Dimension of the MLP representations.
+        num_hidden_layers (`int`, *optional*, defaults to 32):
+            Number of hidden layers in the Transformer encoder.
+        num_attention_heads (`int`, *optional*, defaults to 32):
+            Number of attention heads for each attention layer in the Transformer encoder.
+        num_key_value_heads (`int`, *optional*):
+            This is the number of key_value heads that should be used to implement Grouped Query Attention. If
+            `num_key_value_heads=num_attention_heads`, the model will use Multi Head Attention (MHA), if
+            `num_key_value_heads=1 the model will use Multi Query Attention (MQA) otherwise GQA is used. When
+            converting a multi-head checkpoint to a GQA checkpoint, each group key and value head should be constructed
+            by meanpooling all the original heads within that group. For more details checkout [this
+            paper](https://arxiv.org/pdf/2305.13245.pdf). If it is not specified, will default to
+            `num_attention_heads`.
+        hidden_act (`str` or `function`, *optional*, defaults to `"silu"`):
+            The non-linear activation function (function or string) in the decoder.
+        max_position_embeddings (`int`, *optional*, defaults to 2048):
+            The maximum sequence length that this model might ever be used with. Typically set this to something large
+            just in case (e.g., 512 or 1024 or 2048).
+        initializer_range (`float`, *optional*, defaults to 0.02):
+            The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
+        rms_norm_eps (`float`, *optional*, defaults to 1e-12):
+            The epsilon used by the rms normalization layers.
+        use_cache (`bool`, *optional*, defaults to `True`):
+            Whether or not the model should return the last key/values attentions (not used by all models). Only
+            relevant if `config.is_decoder=True`.
+        tie_word_embeddings(`bool`, *optional*, defaults to `False`):
+            Whether to tie weight embeddings
+        Example:
+
+    """
+    model_type = "internlm2"
+    _auto_class = "AutoConfig"
+
+    def __init__(  # pylint: disable=W0102
+        self,
+        vocab_size=103168,
+        hidden_size=4096,
+        intermediate_size=11008,
+        num_hidden_layers=32,
+        num_attention_heads=32,
+        num_key_value_heads=None,
+        hidden_act="silu",
+        max_position_embeddings=2048,
+        initializer_range=0.02,
+        rms_norm_eps=1e-6,
+        use_cache=True,
+        pad_token_id=0,
+        bos_token_id=1,
+        eos_token_id=2,
+        tie_word_embeddings=False,
+        bias=True,
+        rope_theta=10000,
+        rope_scaling=None,
+        attn_implementation="flash_attention_2",
+        **kwargs,
+    ):
+        self.vocab_size = vocab_size
+        self.max_position_embeddings = max_position_embeddings
+        self.hidden_size = hidden_size
+        self.intermediate_size = intermediate_size
+        self.num_hidden_layers = num_hidden_layers
+        self.num_attention_heads = num_attention_heads
+        self.bias = bias
+
+        if num_key_value_heads is None:
+            num_key_value_heads = num_attention_heads
+        self.num_key_value_heads = num_key_value_heads
+
+        self.hidden_act = hidden_act
+        self.initializer_range = initializer_range
+        self.rms_norm_eps = rms_norm_eps
+        self.use_cache = use_cache
+        self.rope_theta = rope_theta
+        self.rope_scaling = rope_scaling
+        self._rope_scaling_validation()
+
+        self.attn_implementation = attn_implementation
+        if self.attn_implementation is None:
+            self.attn_implementation = "flash_attention_2"
+        super().__init__(
+            pad_token_id=pad_token_id,
+            bos_token_id=bos_token_id,
+            eos_token_id=eos_token_id,
+            tie_word_embeddings=tie_word_embeddings,
+            **kwargs,
+        )
+
+    def _rope_scaling_validation(self):
+        """
+        Validate the `rope_scaling` configuration.
+        """
+        if self.rope_scaling is None:
+            return
+
+        if not isinstance(self.rope_scaling, dict) or len(self.rope_scaling) != 2:
+            raise ValueError(
+                "`rope_scaling` must be a dictionary with with two fields, `type` and `factor`, "
+                f"got {self.rope_scaling}"
+            )
+        rope_scaling_type = self.rope_scaling.get("type", None)
+        rope_scaling_factor = self.rope_scaling.get("factor", None)
+        if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
+            raise ValueError(
+                f"`rope_scaling`'s type field must be one of ['linear', 'dynamic'], got {rope_scaling_type}"
+            )
+        if rope_scaling_factor is None or not isinstance(rope_scaling_factor, float) or rope_scaling_factor < 1.0:
+            raise ValueError(f"`rope_scaling`'s factor field must be a float >= 1, got {rope_scaling_factor}")
diff --git a/base/examples/cars1.jpg b/base/examples/cars1.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..9169fbc5adbe6a57f2f5b9ed903feb857c283be3
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diff --git a/base/examples/cars2.jpg b/base/examples/cars2.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..2b16e48f26f5811c535a10d05188f2724ee3b0c8
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diff --git a/base/examples/cars3.jpg b/base/examples/cars3.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..a894243c4877ade056db369ef7c9d00c2f2c0c42
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diff --git a/base/examples/cars4.jpg b/base/examples/cars4.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..0f2755a7ab396b1207ff5544a076d45a9c8de8a6
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diff --git a/base/examples/dubai.png b/base/examples/dubai.png
new file mode 100644
index 0000000000000000000000000000000000000000..e632b6966c1e69338db955437a3a0b4e88e4c102
--- /dev/null
+++ b/base/examples/dubai.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d1791fdc7767a6e868da0e35d0158f02eae0c78229a0f4505580d756b4ea3929
+size 2801350
diff --git a/base/examples/liuxiang.mp4 b/base/examples/liuxiang.mp4
new file mode 100644
index 0000000000000000000000000000000000000000..23845cc17ec152df01ce575025cfc01fafb8832b
--- /dev/null
+++ b/base/examples/liuxiang.mp4
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:29e1448fe188d8cca2e85fd81c236c53fd61784063d93bc09e2301d33798937a
+size 26855609
diff --git a/base/examples/resume.md b/base/examples/resume.md
new file mode 100644
index 0000000000000000000000000000000000000000..99ab84af0c5d1fa8c491f6d097aa8cb5299b4865
--- /dev/null
+++ b/base/examples/resume.md
@@ -0,0 +1,51 @@
+# Qidong Huang
+
+Building No.7, USTC West CampusHefei, Anhui, China
+
+Ph.D, University of Science and Technology of China
+
+H (+86) 13085060686
+
+B hqd0037@mail.ustc.edu.cn
+
+# Short Biography
+
+Qidong Huang is a PhD student at University of Science and Technology of China. He has published more than 7 papers at top1-tier conferences and journals, such as CVPR/ICCV/AAAI/TIP/TCSVT. His research interests focus on vision transfer learning (e.g., prompt learning for vision pretrained models) and artificial intelligence security (e.g., adversarial examples and anti-DeepFake). He is the reviewer of many top conferences (including CVPR, ICCV, ECCV) and top journals (TNNLS, PR).
+
+# Education
+
+|09/2020–present|PhD of Cyberspace Security, University of Science and Technology of China, Hefei, China, CAS Key Laboratory of Electromagnetic Space Information. Supervised by Prof. Weiming Zhang.|
+|---|---|
+|09/2016–06/2020|Bachelor of Information Security, School of Information Science and Technology, University of Science and Technology of China, Hefei, China.|
+
+# Skills
+
+- Expertise in vision prompt learning: I have been researching the prompt learning for large-scale vision pretrained models and published one paper on top-tier computer vision conferences, in which I propose DAM-VP, a data diversity-aware method for efficient and adaptive vision prompt learning. This work alleviates the mismatch between vision prompts and downstream data diversity.
+- Expertise in artificial intelligence security: I have been studying artificial intelligence security since 2020, including adversarial attack&defense and anti-DeepFake. For adversarial attack, I propose SI-Adv, a shape-invariant attack for 3D point cloud recognition which great boosts the imperceptibility of adversarial examples. For adversarial defense, I propose a contrastive adversarial training framework for robust point cloud recognition named PointCAT. Besides, our work for improving adversarial robustness of masked autoencoders has been recently accepted by ICCV 2023. For anti-DeepFake, we are the first to propose the concept of “initiative defense” against DeepFakes by proactively protecting users’ facial privacy before the manipulation, unlike previous ex-post countermeasures like DeepFake detection.
+
+# Publications (First Author)
+
+Qidong Huang, Xiaoyi Dong, Dongdong Chen, Yinpeng Chen, Lu Yuan, Gang Hua, Weiming Zhang, Nenghai Yu. Improving Adversarial Robustness of Masked Autoencoders via Test-time Frequency-domain Prompting. International Conference on Computer Vision (ICCV), 2023.
+Qidong Huang, Xiaoyi Dong, Dongdong Chen, Weiming Zhang, Feifei Wang, Gang Hua, Nenghai Yu. Diversity-Aware Meta Visual Prompting. Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
+Qidong Huang, Xiaoyi Dong, Dongdong Chen, Hang Zhou, Weiming Zhang, Nenghai Yu. Shape-invariant 3D Adversarial Point Clouds. Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
+---
+# Publications
+
+Qidong Huang*, Jie Zhang*, Wenbo Zhou, Weiming Zhang, Nenghai Yu. Initiative Defense against Facial Manipulation. AAAI Conference on Artificial Intelligence (AAAI), 2021. (*Qidong Huang and Jie Zhang contribute equally.)
+Qidong Huang, Xiaoyi Dong, Dongdong Chen, Hang Zhou, Weiming Zhang, Kui Zhang, Gang Hua, Nenghai Yu. PointCAT : Contrastive Adversarial Training for Robust Point Cloud Recognition. IEEE Transactions on Image Processing (TIP), Major Revision.
+Kui Zhang, Hang Zhou, Jie Zhang, Qidong Huang, Weiming Zhang, Nenghai Yu. Ada3Diff : Defending against 3D Adversarial Point Clouds via Adaptive Diffusion. Under Review
+Han Fang, Dongdong Chen, Qidong Huang, Jie Zhang, Zehua Ma, Weiming Zhang* and Nenghai Yu. Deep Template-based Watermarking. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2020.
+Jie Zhang, Dongdong Chen, Qidong Huang, Jing Liao, Weiming Zhang, Huamin Feng, Gang Hua, Nenghai Yu. Poison ink : Robust and invisible backdoor attack. IEEE Transactions on Image Processing (TIP), 2022.
+
+# Services
+
+- Reviewer for CVPR 2022, 2023
+- Reviewer for ICCV 2023
+- Reviewer for ECCV 2022
+- Reviewer for ICPR 2022
+- Reviewer for IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
+- Reviewer for Pattern Recognition (PR)
+
+# Awards & Honors
+
+2021 China National Scholarship
\ No newline at end of file
diff --git a/base/examples/screenshot.jpg b/base/examples/screenshot.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..e204630f04b8d4a87c2ee3655140f30f3c4eaf71
Binary files /dev/null and b/base/examples/screenshot.jpg differ
diff --git a/base/examples/test.py b/base/examples/test.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/base/generation_config.json b/base/generation_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..9048ac5345368f583e99250987aa84635df4e0c9
--- /dev/null
+++ b/base/generation_config.json
@@ -0,0 +1,9 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "max_length": 16384,
+  "pad_token_id": 2,
+  "transformers_version": "4.33.1",
+  "use_cache": false
+}
diff --git a/base/ixc_utils.py b/base/ixc_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..a7a3b1464329c1c170ece4390e7ebb5c8b432354
--- /dev/null
+++ b/base/ixc_utils.py
@@ -0,0 +1,145 @@
+import os
+import torch
+import numpy as np
+import torchvision
+from urllib.request import urlopen
+from PIL import Image, ImageDraw, ImageFont
+from torchvision.transforms.functional import InterpolationMode
+import torchvision.transforms as transforms
+from decord import VideoReader
+
+def get_font():
+    truetype_url = 'https://huggingface.co/internlm/internlm-xcomposer2d5-7b/resolve/main/SimHei.ttf?download=true'
+    ff = urlopen(truetype_url)
+    font = ImageFont.truetype(ff, size=40)
+    return font
+
+def padding_336(b, pad=336):
+    width, height = b.size
+    tar = int(np.ceil(height / pad) * pad)
+    top_padding = 0 # int((tar - height)/2)
+    bottom_padding = tar - height - top_padding
+    left_padding = 0
+    right_padding = 0
+    b = transforms.functional.pad(b, [left_padding, top_padding, right_padding, bottom_padding], fill=[255,255,255])
+
+    return b
+
+def Image_transform(img, hd_num=25):
+    width, height = img.size
+    trans = False
+    if width < height:
+        img = img.transpose(Image.TRANSPOSE)
+        trans = True
+        width, height = img.size
+    ratio = (width / height)
+    scale = 1
+    while scale * np.ceil(scale / ratio) <= hd_num:
+        scale += 1
+    scale -= 1
+    scale = min(np.ceil(width / 560), scale)
+    new_w = int(scale * 560)
+    new_h = int(new_w / ratio)
+    #print (scale, f'{height}/{new_h}, {width}/{new_w}')
+
+    img = transforms.functional.resize(img, [new_h, new_w], )
+    img = padding_336(img, 560)
+    width, height = img.size
+    if trans:
+        img = img.transpose(Image.TRANSPOSE)
+
+    return img
+
+
+def Video_transform(img, hd_num=25):
+    width, height = img.size
+    trans = False
+    if width < height:
+        img = img.transpose(Image.TRANSPOSE)
+        trans = True
+        width, height = img.size
+    ratio = (width/ height)
+    scale = 1
+    new_h = int(scale * 560)
+    new_w = int(new_h * ratio)
+    #print (new_h, new_w)
+
+    img = transforms.functional.resize(img, [new_h, new_w],)
+    img = img.transpose(Image.TRANSPOSE)
+    img = padding_336(img, 560)
+    width, height = img.size
+    if not trans:
+        img = img.transpose(Image.TRANSPOSE)
+
+    return img
+
+def frame2img(imgs, font):
+    new_imgs = []
+    for img in imgs:
+        w, h = img.size
+        scale = w/h
+        if w > h:
+            new_w = 560 * 2
+            new_h = int(560 * 2 / scale)
+        else:
+            new_w = int(560 * 2 * scale)
+            new_h = 560 * 2
+        img = transforms.functional.resize(img, [new_h, new_w],)
+        new_imgs.append(img)
+    imgs = new_imgs
+    new_w = 0
+    new_h = 0
+    pad = 40
+    if w > h:
+        for im in imgs:
+            w,h = im.size
+            new_w = max(new_w, w)
+            new_h += h + 10 + pad
+        new_img = Image.new('RGB', (new_w, new_h), 'white')
+        draw = ImageDraw.Draw(new_img)
+        curr_h = 0
+        for idx, im in enumerate(imgs):
+            w,h = im.size
+            new_img.paste(im, (0, pad + curr_h))
+            draw.text((0, curr_h ), f'<IMAGE {idx}>', font=font, fill='black')
+            if idx + 1 < len(imgs):
+                draw.line([(0, pad +curr_h + h +5), (new_w, pad +curr_h + h +5)], fill = 'black', width=2)
+            curr_h += h + 10 + pad
+        #print (new_w, new_h)
+    else:
+        for im in imgs:
+            w,h = im.size
+            new_w += w + 10
+            new_h = max(new_h, h)
+        new_h += pad
+        new_img = Image.new('RGB', (new_w, new_h), 'white')
+        draw = ImageDraw.Draw(new_img)
+        curr_w = 0
+        for idx, im in enumerate(imgs):
+            w,h = im.size
+            new_img.paste(im, (curr_w, pad))
+            draw.text((curr_w, 0), f'<IMAGE {idx}>', font=font, fill='black')
+            if idx + 1 < len(imgs):
+                draw.line([(curr_w + w + 5, 0), (curr_w + w + 5, new_h)], fill = 'black', width=2)
+            curr_w += w + 10
+    return new_img
+
+def load_video(video_path, num_frm=32, start=None, end=None):
+    vid = VideoReader(video_path, num_threads=1)
+    fps = vid.get_avg_fps()
+    t_stride = int(round(float(fps) / int(1)))
+    start_idx = 0 if start is None else start
+    end_idx = len(vid) if end is None else end
+    all_pos = list(range(start_idx, end_idx, t_stride))
+    try:
+        images = [vid[i].numpy() for i in all_pos]
+    except:
+        images = [vid[i].asnumpy() for i in all_pos]
+    if len(images) > num_frm:
+        num_frm = min(num_frm, len(images))
+        step_size = len(images) / (num_frm + 1)
+        indices = [int(i*step_size) for i in range(num_frm)]
+        images = [images[i] for i in indices]
+    images = [Image.fromarray(arr) for arr in images]
+    return images
+
diff --git a/base/logo_en.png b/base/logo_en.png
new file mode 100644
index 0000000000000000000000000000000000000000..2bfa121116ba991a737068cbff6856b6735d61ff
Binary files /dev/null and b/base/logo_en.png differ
diff --git a/base/modeling_internlm2.py b/base/modeling_internlm2.py
new file mode 100644
index 0000000000000000000000000000000000000000..9254fd2d01dd962d51690d340942918de7c4fe34
--- /dev/null
+++ b/base/modeling_internlm2.py
@@ -0,0 +1,991 @@
+# Copyright (c) The InternLM team and The HuggingFace Inc. team. All rights reserved.
+#
+# This code is based on transformers/src/transformers/models/llama/modeling_llama.py
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+""" PyTorch InternLM2 model."""
+import math
+import queue
+import threading
+import warnings
+import copy
+import numpy as np
+from typing import List, Optional, Tuple, Union
+from torchvision import transforms
+from torchvision.transforms.functional import InterpolationMode
+from PIL import Image
+
+import torch
+import torch.nn.functional as F
+import torch.utils.checkpoint
+from einops import rearrange
+from torch import nn
+from transformers.activations import ACT2FN
+from transformers.modeling_outputs import (
+    BaseModelOutputWithPast,
+    CausalLMOutputWithPast,
+    SequenceClassifierOutputWithPast,
+)
+from transformers.modeling_utils import PreTrainedModel
+from transformers.utils import (
+    add_start_docstrings,
+    add_start_docstrings_to_model_forward,
+    logging,
+    replace_return_docstrings,
+)
+
+try:
+    from transformers.generation.streamers import BaseStreamer
+except:  # noqa # pylint: disable=bare-except
+    BaseStreamer = None
+
+from .build_mlp import PLoRA
+from .configuration_internlm_xcomposer2 import InternLMXcomposer2Config as InternLM2Config
+
+logger = logging.get_logger(__name__)
+
+_CONFIG_FOR_DOC = "InternLM2Config"
+
+flash_attn_func, flash_attn_varlen_func = None, None
+pad_input, index_first_axis, unpad_input = None, None, None
+def _import_flash_attn():
+    global flash_attn_func, flash_attn_varlen_func
+    global pad_input, index_first_axis, unpad_input
+    try:
+        from flash_attn import flash_attn_func as _flash_attn_func, flash_attn_varlen_func as _flash_attn_varlen_func
+        from flash_attn.bert_padding import pad_input as _pad_input, index_first_axis as _index_first_axis, unpad_input as _unpad_input
+        flash_attn_func, flash_attn_varlen_func = _flash_attn_func, _flash_attn_varlen_func
+        pad_input, index_first_axis, unpad_input = _pad_input, _index_first_axis, _unpad_input
+    except ImportError:
+        raise ImportError("flash_attn is not installed.")
+
+# Copied from transformers.models.llama.modeling_llama._get_unpad_data
+def _get_unpad_data(attention_mask):
+    seqlens_in_batch = attention_mask.sum(dim=-1, dtype=torch.int32)
+    indices = torch.nonzero(attention_mask.flatten(), as_tuple=False).flatten()
+    max_seqlen_in_batch = seqlens_in_batch.max().item()
+    cu_seqlens = F.pad(torch.cumsum(seqlens_in_batch, dim=0, dtype=torch.torch.int32), (1, 0))
+    return (
+        indices,
+        cu_seqlens,
+        max_seqlen_in_batch,
+    )
+
+
+# Copied from transformers.models.bart.modeling_bart._make_causal_mask
+def _make_causal_mask(
+    input_ids_shape: torch.Size, dtype: torch.dtype, device: torch.device, past_key_values_length: int = 0
+):
+    """
+    Make causal mask used for bi-directional self-attention.
+    """
+    bsz, tgt_len = input_ids_shape
+    mask = torch.full((tgt_len, tgt_len), torch.tensor(torch.finfo(dtype).min, device=device), device=device)
+    mask_cond = torch.arange(mask.size(-1), device=device)
+    mask.masked_fill_(mask_cond < (mask_cond + 1).view(mask.size(-1), 1), 0)
+    mask = mask.to(dtype)
+
+    if past_key_values_length > 0:
+        mask = torch.cat([torch.zeros(tgt_len, past_key_values_length, dtype=dtype, device=device), mask], dim=-1)
+    return mask[None, None, :, :].expand(bsz, 1, tgt_len, tgt_len + past_key_values_length)
+
+
+# Copied from transformers.models.bart.modeling_bart._expand_mask
+def _expand_mask(mask: torch.Tensor, dtype: torch.dtype, tgt_len: Optional[int] = None):
+    """
+    Expands attention_mask from `[bsz, seq_len]` to `[bsz, 1, tgt_seq_len, src_seq_len]`.
+    """
+    bsz, src_len = mask.size()
+    tgt_len = tgt_len if tgt_len is not None else src_len
+
+    expanded_mask = mask[:, None, None, :].expand(bsz, 1, tgt_len, src_len).to(dtype)
+
+    inverted_mask = 1.0 - expanded_mask
+
+    return inverted_mask.masked_fill(inverted_mask.to(torch.bool), torch.finfo(dtype).min)
+
+
+# Copied from transformers.models.llama.modeling_llama.LlamaRMSNorm with Llama->InternLM2
+class InternLM2RMSNorm(nn.Module):
+    def __init__(self, hidden_size, eps=1e-6):
+        """
+        InternLM2RMSNorm is equivalent to T5LayerNorm
+        """
+        super().__init__()
+        self.weight = nn.Parameter(torch.ones(hidden_size))
+        self.variance_epsilon = eps
+
+    def forward(self, hidden_states):
+        input_dtype = hidden_states.dtype
+        hidden_states = hidden_states.to(torch.float32)
+        variance = hidden_states.pow(2).mean(-1, keepdim=True)
+        hidden_states = hidden_states * torch.rsqrt(variance + self.variance_epsilon)
+        return self.weight * hidden_states.to(input_dtype)
+
+
+# Copied from transformers.model.llama.modeling_llama.LlamaRotaryEmbedding with Llama->InternLM2
+class InternLM2RotaryEmbedding(nn.Module):
+    def __init__(self, dim, max_position_embeddings=2048, base=10000, device=None):
+        super().__init__()
+
+        self.dim = dim
+        self.max_position_embeddings = max_position_embeddings
+        self.base = base
+        inv_freq = 1.0 / (self.base ** (torch.arange(0, self.dim, 2).float().to(device) / self.dim))
+        self.register_buffer("inv_freq", inv_freq, persistent=False)
+
+        # Build here to make `torch.jit.trace` work.
+        self._set_cos_sin_cache(
+            seq_len=max_position_embeddings, device=self.inv_freq.device, dtype=torch.get_default_dtype()
+        )
+
+    def _set_cos_sin_cache(self, seq_len, device, dtype):
+        self.max_seq_len_cached = seq_len
+        t = torch.arange(self.max_seq_len_cached, device=device, dtype=self.inv_freq.dtype)
+
+        freqs = torch.einsum("i,j->ij", t, self.inv_freq)
+        # Different from paper, but it uses a different permutation in order to obtain the same calculation
+        emb = torch.cat((freqs, freqs), dim=-1)
+        self.register_buffer("cos_cached", emb.cos().to(dtype), persistent=False)
+        self.register_buffer("sin_cached", emb.sin().to(dtype), persistent=False)
+
+    def forward(self, x, seq_len=None):
+        # x: [bs, num_attention_heads, seq_len, head_size]
+        if seq_len > self.max_seq_len_cached:
+            self._set_cos_sin_cache(seq_len=seq_len, device=x.device, dtype=torch.float32)
+
+        return (
+            self.cos_cached[:seq_len].to(dtype=x.dtype),
+            self.sin_cached[:seq_len].to(dtype=x.dtype),
+        )
+
+
+# Copied from transformers.model.llama.modeling_llama.LlamaLinearScalingRotaryEmbedding with Llama->InternLM2
+class InternLM2LinearScalingRotaryEmbedding(InternLM2RotaryEmbedding):
+    """InternLM2RotaryEmbedding extended with linear scaling. Credits to the Reddit user /u/kaiokendev"""
+
+    def __init__(self, dim, max_position_embeddings=2048, base=10000, device=None, scaling_factor=1.0):
+        self.scaling_factor = scaling_factor
+        super().__init__(dim, max_position_embeddings, base, device)
+
+    def _set_cos_sin_cache(self, seq_len, device, dtype):
+        self.max_seq_len_cached = seq_len
+        t = torch.arange(self.max_seq_len_cached, device=device, dtype=self.inv_freq.dtype)
+        t = t / self.scaling_factor
+
+        freqs = torch.einsum("i,j->ij", t, self.inv_freq)
+        # Different from paper, but it uses a different permutation in order to obtain the same calculation
+        emb = torch.cat((freqs, freqs), dim=-1)
+        self.register_buffer("cos_cached", emb.cos().to(dtype), persistent=False)
+        self.register_buffer("sin_cached", emb.sin().to(dtype), persistent=False)
+
+
+# Copied from transformers.model.llama.modeling_llama.LlamaDynamicNTKScalingRotaryEmbedding with Llama->InternLM2
+class InternLM2DynamicNTKScalingRotaryEmbedding(InternLM2RotaryEmbedding):
+    """InternLM2RotaryEmbedding extended with Dynamic NTK scaling.
+    Credits to the Reddit users /u/bloc97 and /u/emozilla.
+    """
+
+    def __init__(self, dim, max_position_embeddings=2048, base=10000, device=None, scaling_factor=1.0):
+        self.scaling_factor = scaling_factor
+        super().__init__(dim, max_position_embeddings, base, device)
+
+    def _set_cos_sin_cache(self, seq_len, device, dtype):
+        self.max_seq_len_cached = seq_len
+
+        if seq_len > self.max_position_embeddings:
+            base = self.base * (
+                (self.scaling_factor * seq_len / self.max_position_embeddings) - (self.scaling_factor - 1)
+            ) ** (self.dim / (self.dim - 2))
+            inv_freq = 1.0 / (base ** (torch.arange(0, self.dim, 2).float().to(device) / self.dim))
+            self.register_buffer("inv_freq", inv_freq, persistent=False)
+
+        t = torch.arange(self.max_seq_len_cached, device=device, dtype=self.inv_freq.dtype)
+
+        freqs = torch.einsum("i,j->ij", t, self.inv_freq)
+        # Different from paper, but it uses a different permutation in order to obtain the same calculation
+        emb = torch.cat((freqs, freqs), dim=-1)
+        self.register_buffer("cos_cached", emb.cos().to(dtype), persistent=False)
+        self.register_buffer("sin_cached", emb.sin().to(dtype), persistent=False)
+
+
+# Copied from transformers.model.llama.modeling_llama.rotate_half
+def rotate_half(x):
+    """Rotates half the hidden dims of the input."""
+    x1 = x[..., : x.shape[-1] // 2]
+    x2 = x[..., x.shape[-1] // 2 :]
+    return torch.cat((-x2, x1), dim=-1)
+
+
+# Copied from transformers.model.llama.modeling_llama.apply_rotary_pos_emb
+def apply_rotary_pos_emb(q, k, cos, sin, position_ids, unsqueeze_dim=1):
+    """Applies Rotary Position Embedding to the query and key tensors."""
+    cos = cos[position_ids].unsqueeze(unsqueeze_dim)
+    sin = sin[position_ids].unsqueeze(unsqueeze_dim)
+    q_embed = (q * cos) + (rotate_half(q) * sin)
+    k_embed = (k * cos) + (rotate_half(k) * sin)
+    return q_embed, k_embed
+
+
+class InternLM2MLP(nn.Module):
+    def __init__(self, config):
+        super().__init__()
+        self.config = config
+        self.hidden_size = config.hidden_size
+        self.intermediate_size = config.intermediate_size
+        #self.w1 = nn.Linear(self.hidden_size, self.intermediate_size, bias=False)
+        #self.w3 = nn.Linear(self.hidden_size, self.intermediate_size, bias=False)
+        #self.w2 = nn.Linear(self.intermediate_size, self.hidden_size, bias=False)
+        
+        self.w1 = PLoRA(self.hidden_size, self.intermediate_size, bias=False,
+                            lora_r=256, lora_alpha=256, lora_len=1225)
+        self.w3 = PLoRA(self.hidden_size, self.intermediate_size, bias=False,
+                            lora_r=256, lora_alpha=256, lora_len=1225)
+        self.w2 = PLoRA(self.intermediate_size, self.hidden_size, bias=False,
+                            lora_r=256, lora_alpha=256, lora_len=1225)
+
+        self.act_fn = ACT2FN[config.hidden_act]
+
+    def forward(self, x, im_mask):
+        down_proj = self.w2(self.act_fn(self.w1(x, im_mask)) * self.w3(x, im_mask), im_mask)
+
+        return down_proj
+
+
+# Copied from transformers.model.llama.modeling_llama.repeat_kv
+def repeat_kv(hidden_states: torch.Tensor, n_rep: int) -> torch.Tensor:
+    """
+    This is the equivalent of torch.repeat_interleave(x, dim=1, repeats=n_rep). The hidden states go from (batch,
+    num_key_value_heads, seqlen, head_dim) to (batch, num_attention_heads, seqlen, head_dim)
+    """
+    batch, num_key_value_heads, slen, head_dim = hidden_states.shape
+    if n_rep == 1:
+        return hidden_states
+    hidden_states = hidden_states[:, :, None, :, :].expand(batch, num_key_value_heads, n_rep, slen, head_dim)
+    return hidden_states.reshape(batch, num_key_value_heads * n_rep, slen, head_dim)
+
+
+# Modified from transformers.model.llama.modeling_llama.LlamaAttention
+class InternLM2Attention(nn.Module):
+    """Multi-headed attention from 'Attention Is All You Need' paper"""
+
+    def __init__(self, config: InternLM2Config):
+        super().__init__()
+        self.config = config
+        self.hidden_size = config.hidden_size
+        self.num_heads = config.num_attention_heads
+        self.head_dim = self.hidden_size // self.num_heads
+        self.num_key_value_heads = config.num_key_value_heads
+        self.num_key_value_groups = self.num_heads // self.num_key_value_heads
+        self.max_position_embeddings = config.max_position_embeddings
+        self.is_causal = True
+
+        if (self.head_dim * self.num_heads) != self.hidden_size:
+            raise ValueError(
+                f"hidden_size must be divisible by num_heads (got `hidden_size`: {self.hidden_size}"
+                f" and `num_heads`: {self.num_heads})."
+            )
+
+        #self.wqkv = nn.Linear(
+        self.wqkv = PLoRA(
+            self.hidden_size,
+            (self.num_heads + 2 * self.num_key_value_heads) * self.head_dim,
+            bias=config.bias,
+            lora_r=256, lora_alpha=256, lora_len=1225
+        )
+
+        #self.wo = nn.Linear(self.num_heads * self.head_dim, self.hidden_size, bias=config.bias)
+        self.wo = PLoRA(self.num_heads * self.head_dim, self.hidden_size, bias=config.bias,
+                           lora_r=256, lora_alpha=256, lora_len=1225)
+        self._init_rope()
+    
+    def _init_rope(self):
+        if self.config.rope_scaling is None:
+            self.rotary_emb = InternLM2RotaryEmbedding(
+                self.head_dim,
+                max_position_embeddings=self.max_position_embeddings,
+                base=self.config.rope_theta,
+            )
+        else:
+            scaling_type = self.config.rope_scaling["type"]
+            scaling_factor = self.config.rope_scaling["factor"]
+            if scaling_type == "dynamic":
+                self.rotary_emb = InternLM2DynamicNTKScalingRotaryEmbedding(
+                    self.head_dim,
+                    max_position_embeddings=self.max_position_embeddings,
+                    base=self.config.rope_theta,
+                    scaling_factor=scaling_factor,
+                )
+            elif scaling_type == "linear":
+                self.rotary_emb = InternLM2LinearScalingRotaryEmbedding(
+                    self.head_dim,
+                    max_position_embeddings=self.max_position_embeddings,
+                    base=self.config.rope_theta,
+                    scaling_factor=scaling_factor,
+                )
+            else:
+                raise ValueError("Currently we only support rotary embedding's type being 'dynamic' or 'linear'.")
+        return self.rotary_emb
+
+    def _shape(self, tensor: torch.Tensor, seq_len: int, bsz: int):
+        return tensor.view(bsz, seq_len, self.num_heads, self.head_dim).transpose(1, 2).contiguous()
+
+    def forward(
+        self,
+        hidden_states: torch.Tensor,
+        attention_mask: Optional[torch.Tensor] = None,
+        position_ids: Optional[torch.LongTensor] = None,
+        past_key_value: Optional[Tuple[torch.Tensor]] = None,
+        output_attentions: bool = False,
+        use_cache: bool = False,
+        im_mask: Optional[Tuple[torch.Tensor]] = None,
+        **kwargs,
+    ) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[Tuple[torch.Tensor]]]:
+        if "padding_mask" in kwargs:
+            warnings.warn(
+                "Passing `padding_mask` is deprecated and will be removed in v4.37. "
+                "Please make sure use `attention_mask` instead.`"
+            )
+
+        bsz, q_len, _ = hidden_states.size()
+
+        qkv_states = self.wqkv(hidden_states, im_mask)
+
+        qkv_states = rearrange(
+            qkv_states,
+            "b q (h gs d) -> b q h gs d",
+            gs=2 + self.num_key_value_groups,
+            d=self.head_dim,
+        )
+
+        query_states = qkv_states[..., : self.num_key_value_groups, :]
+        query_states = rearrange(query_states, "b q h gs d -> b q (h gs) d")
+        key_states = qkv_states[..., -2, :]
+        value_states = qkv_states[..., -1, :]
+
+        query_states = query_states.transpose(1, 2)
+        key_states = key_states.transpose(1, 2)
+        value_states = value_states.transpose(1, 2)
+
+        kv_seq_len = key_states.shape[-2]
+        if past_key_value is not None:
+            kv_seq_len += past_key_value[0].shape[-2]
+        cos, sin = self.rotary_emb(value_states, seq_len=kv_seq_len)
+        query_states, key_states = apply_rotary_pos_emb(query_states, key_states, cos, sin, position_ids)
+
+        if past_key_value is not None:
+            # reuse k, v, self_attention
+            key_states = torch.cat([past_key_value[0], key_states], dim=2)
+            value_states = torch.cat([past_key_value[1], value_states], dim=2)
+
+        past_key_value = (key_states, value_states) if use_cache else None
+
+        key_states = repeat_kv(key_states, self.num_key_value_groups)
+        value_states = repeat_kv(value_states, self.num_key_value_groups)
+
+        attn_weights = torch.matmul(query_states, key_states.transpose(2, 3)) / math.sqrt(self.head_dim)
+
+        if attn_weights.size() != (bsz, self.num_heads, q_len, kv_seq_len):
+            raise ValueError(
+                f"Attention weights should be of size {(bsz, self.num_heads, q_len, kv_seq_len)}, but is"
+                f" {attn_weights.size()}"
+            )
+
+        if attention_mask is not None:
+            if attention_mask.size() != (bsz, 1, q_len, kv_seq_len):
+                raise ValueError(
+                    f"Attention mask should be of size {(bsz, 1, q_len, kv_seq_len)}, but is {attention_mask.size()}"
+                )
+            attn_weights = attn_weights + attention_mask
+
+        # upcast attention to fp32
+        attn_weights = nn.functional.softmax(attn_weights, dim=-1, dtype=torch.float32).to(query_states.dtype)
+        attn_output = torch.matmul(attn_weights, value_states)
+
+        if attn_output.size() != (bsz, self.num_heads, q_len, self.head_dim):
+            raise ValueError(
+                f"`attn_output` should be of size {(bsz, self.num_heads, q_len, self.head_dim)}, but is"
+                f" {attn_output.size()}"
+            )
+
+        attn_output = attn_output.transpose(1, 2).contiguous()
+        attn_output = attn_output.reshape(bsz, q_len, self.hidden_size)
+
+        attn_output = self.wo(attn_output, im_mask)
+
+        if not output_attentions:
+            attn_weights = None
+
+        return attn_output, attn_weights, past_key_value
+
+
+# Modified from transformers.model.llama.modeling_llama.InternLM2FlashAttention2
+class InternLM2FlashAttention2(InternLM2Attention):
+    """
+    InternLM2 flash attention module. This module inherits from `InternLM2Attention` as the weights of the module stays
+    untouched. The only required change would be on the forward pass where it needs to correctly call the public API of
+    flash attention and deal with padding tokens in case the input contains any of them.
+    """
+
+    def forward(
+        self,
+        hidden_states: torch.Tensor,
+        attention_mask: Optional[torch.LongTensor] = None,
+        position_ids: Optional[torch.LongTensor] = None,
+        past_key_value: Optional[Tuple[torch.Tensor]] = None,
+        output_attentions: bool = False,
+        use_cache: bool = False,
+        im_mask: Optional[Tuple[torch.Tensor]] = None,
+        **kwargs,
+    ) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[Tuple[torch.Tensor]]]:
+        # InternLM2FlashAttention2 attention does not support output_attentions
+        if "padding_mask" in kwargs:
+            warnings.warn(
+                "Passing `padding_mask` is deprecated and will be removed in v4.37. "
+                "Please make sure use `attention_mask` instead.`"
+            )
+
+            # overwrite attention_mask with padding_mask
+            attention_mask = kwargs.pop("padding_mask")
+
+        output_attentions = False
+
+        bsz, q_len, _ = hidden_states.size()
+
+        qkv_states = self.wqkv(hidden_states, im_mask)
+
+        qkv_states = rearrange(
+            qkv_states,
+            "b q (h gs d) -> b q h gs d",
+            gs=2 + self.num_key_value_groups,
+            d=self.head_dim,
+        )
+
+        query_states = qkv_states[..., : self.num_key_value_groups, :]
+        query_states = rearrange(query_states, "b q h gs d -> b q (h gs) d")
+        key_states = qkv_states[..., -2, :]
+        value_states = qkv_states[..., -1, :]
+
+        query_states = query_states.transpose(1, 2)
+        key_states = key_states.transpose(1, 2)
+        value_states = value_states.transpose(1, 2)
+
+        kv_seq_len = key_states.shape[-2]
+        if past_key_value is not None:
+            kv_seq_len += past_key_value[0].shape[-2]
+
+        cos, sin = self.rotary_emb(value_states, seq_len=kv_seq_len)
+
+        query_states, key_states = apply_rotary_pos_emb(query_states, key_states, cos, sin, position_ids)
+
+        if past_key_value is not None:
+            # reuse k, v, self_attention
+            key_states = torch.cat([past_key_value[0], key_states], dim=2)
+            value_states = torch.cat([past_key_value[1], value_states], dim=2)
+
+        past_key_value = (key_states, value_states) if use_cache else None
+
+        query_states = query_states.transpose(1, 2)
+        key_states = key_states.transpose(1, 2)
+        value_states = value_states.transpose(1, 2)
+
+        attn_output = self._flash_attention_forward(
+            query_states, key_states, value_states, attention_mask, q_len
+        )
+
+        attn_output = attn_output.reshape(bsz, q_len, self.hidden_size).contiguous()
+        attn_output = self.wo(attn_output, im_mask)
+
+        if not output_attentions:
+            attn_weights = None
+
+        return attn_output, attn_weights, past_key_value
+
+    def _flash_attention_forward(
+        self, query_states, key_states, value_states, attention_mask, query_length, dropout=0.0, softmax_scale=None
+    ):
+        """
+        Calls the forward method of Flash Attention - if the input hidden states contain at least one padding token
+        first unpad the input, then computes the attention scores and pad the final attention scores.
+
+        Args:
+            query_states (`torch.Tensor`):
+                Input query states to be passed to Flash Attention API
+            key_states (`torch.Tensor`):
+                Input key states to be passed to Flash Attention API
+            value_states (`torch.Tensor`):
+                Input value states to be passed to Flash Attention API
+            attention_mask (`torch.Tensor`):
+                The padding mask - corresponds to a tensor of size `(batch_size, seq_len)` where 0 stands for the
+                position of padding tokens and 1 for the position of non-padding tokens.
+            dropout (`int`, *optional*):
+                Attention dropout
+            softmax_scale (`float`, *optional*):
+                The scaling of QK^T before applying softmax. Default to 1 / sqrt(head_dim)
+        """
+        # Contains at least one padding token in the sequence
+        causal = self.is_causal and query_length != 1
+        if attention_mask is not None:
+            batch_size = query_states.shape[0]
+            query_states, key_states, value_states, indices_q, cu_seq_lens, max_seq_lens = self._unpad_input(
+                query_states, key_states, value_states, attention_mask, query_length
+            )
+
+            cu_seqlens_q, cu_seqlens_k = cu_seq_lens
+            max_seqlen_in_batch_q, max_seqlen_in_batch_k = max_seq_lens
+
+            attn_output_unpad = flash_attn_varlen_func(
+                query_states,
+                key_states,
+                value_states,
+                cu_seqlens_q=cu_seqlens_q,
+                cu_seqlens_k=cu_seqlens_k,
+                max_seqlen_q=max_seqlen_in_batch_q,
+                max_seqlen_k=max_seqlen_in_batch_k,
+                dropout_p=dropout,
+                softmax_scale=softmax_scale,
+                causal=causal,
+            )
+
+            attn_output = pad_input(attn_output_unpad, indices_q, batch_size, query_length)
+        else:
+            attn_output = flash_attn_func(
+                query_states, key_states, value_states, dropout, softmax_scale=softmax_scale, causal=causal
+            )
+
+        return attn_output
+
+    def _unpad_input(self, query_layer, key_layer, value_layer, attention_mask, query_length):
+        indices_k, cu_seqlens_k, max_seqlen_in_batch_k = _get_unpad_data(attention_mask)
+        batch_size, kv_seq_len, num_key_value_heads, head_dim = key_layer.shape
+
+        key_layer = index_first_axis(
+            key_layer.reshape(batch_size * kv_seq_len, num_key_value_heads, head_dim), indices_k
+        )
+        value_layer = index_first_axis(
+            value_layer.reshape(batch_size * kv_seq_len, num_key_value_heads, head_dim), indices_k
+        )
+
+        if query_length == kv_seq_len:
+            query_layer = index_first_axis(
+                query_layer.reshape(batch_size * kv_seq_len, self.num_heads, head_dim), indices_k
+            )
+            cu_seqlens_q = cu_seqlens_k
+            max_seqlen_in_batch_q = max_seqlen_in_batch_k
+            indices_q = indices_k
+        elif query_length == 1:
+            max_seqlen_in_batch_q = 1
+            cu_seqlens_q = torch.arange(
+                batch_size + 1, dtype=torch.int32, device=query_layer.device
+            )  # There is a memcpy here, that is very bad.
+            indices_q = cu_seqlens_q[:-1]
+            query_layer = query_layer.squeeze(1)
+        else:
+            # The -q_len: slice assumes left padding.
+            attention_mask = attention_mask[:, -query_length:]
+            query_layer, indices_q, cu_seqlens_q, max_seqlen_in_batch_q = unpad_input(query_layer, attention_mask)
+
+        return (
+            query_layer,
+            key_layer,
+            value_layer,
+            indices_q.to(torch.int64),
+            (cu_seqlens_q, cu_seqlens_k),
+            (max_seqlen_in_batch_q, max_seqlen_in_batch_k),
+        )
+
+INTERNLM2_ATTENTION_CLASSES = {
+    "eager": InternLM2Attention,
+    "flash_attention_2": InternLM2FlashAttention2,
+}
+
+# Modified from transformers.model.llama.modeling_llama.LlamaDecoderLayer
+class InternLM2DecoderLayer(nn.Module):
+    def __init__(self, config: InternLM2Config):
+        super().__init__()
+        self.hidden_size = config.hidden_size
+
+        self.attention = INTERNLM2_ATTENTION_CLASSES[config.attn_implementation](config=config)
+
+        self.feed_forward = InternLM2MLP(config)
+        self.attention_norm = InternLM2RMSNorm(config.hidden_size, eps=config.rms_norm_eps)
+        self.ffn_norm = InternLM2RMSNorm(config.hidden_size, eps=config.rms_norm_eps)
+
+    def forward(
+        self,
+        hidden_states: torch.Tensor,
+        attention_mask: Optional[torch.Tensor] = None,
+        position_ids: Optional[torch.LongTensor] = None,
+        past_key_value: Optional[Tuple[torch.Tensor]] = None,
+        output_attentions: Optional[bool] = False,
+        use_cache: Optional[bool] = False,
+        im_mask: Optional[Tuple[torch.Tensor]] = None,
+        **kwargs,
+    ) -> Tuple[torch.FloatTensor, Optional[Tuple[torch.FloatTensor, torch.FloatTensor]]]:
+        """
+        Args:
+            hidden_states (`torch.FloatTensor`): input to the layer of shape `(batch, seq_len, embed_dim)`
+            attention_mask (`torch.FloatTensor`, *optional*):
+                attention mask of size `(batch_size, sequence_length)` if flash attention is used or `(batch_size, 1,
+                query_sequence_length, key_sequence_length)` if default attention is used.
+            output_attentions (`bool`, *optional*):
+                Whether or not to return the attentions tensors of all attention layers. See `attentions` under
+                returned tensors for more detail.
+            use_cache (`bool`, *optional*):
+                If set to `True`, `past_key_values` key value states are returned and can be used to speed up decoding
+                (see `past_key_values`).
+            past_key_value (`Tuple(torch.FloatTensor)`, *optional*): cached past key and value projection states
+        """
+        if "padding_mask" in kwargs:
+            warnings.warn(
+                "Passing `padding_mask` is deprecated and will be removed in v4.37. "
+                "Please make sure use `attention_mask` instead.`"
+            )
+
+        residual = hidden_states
+
+        hidden_states = self.attention_norm(hidden_states)
+
+        # Self Attention
+        hidden_states, self_attn_weights, present_key_value = self.attention(
+            hidden_states=hidden_states,
+            attention_mask=attention_mask,
+            position_ids=position_ids,
+            past_key_value=past_key_value,
+            output_attentions=output_attentions,
+            use_cache=use_cache,
+            im_mask=im_mask,
+            **kwargs,
+        )
+        hidden_states = residual + hidden_states
+
+        # Fully Connected
+        residual = hidden_states
+        hidden_states = self.ffn_norm(hidden_states)
+        hidden_states = self.feed_forward(hidden_states, im_mask)
+        hidden_states = residual + hidden_states
+
+        outputs = (hidden_states,)
+
+        if output_attentions:
+            outputs += (self_attn_weights,)
+
+        if use_cache:
+            outputs += (present_key_value,)
+
+        return outputs
+
+
+InternLM2_START_DOCSTRING = r"""
+    This model inherits from [`PreTrainedModel`]. Check the superclass documentation for the generic methods the
+    library implements for all its model (such as downloading or saving, resizing the input embeddings, pruning heads
+    etc.)
+
+    This model is also a PyTorch [torch.nn.Module](https://pytorch.org/docs/stable/nn.html#torch.nn.Module) subclass.
+    Use it as a regular PyTorch Module and refer to the PyTorch documentation for all matter related to general usage
+    and behavior.
+
+    Parameters:
+        config ([`InternLM2Config`]):
+            Model configuration class with all the parameters of the model. Initializing with a config file does not
+            load the weights associated with the model, only the configuration. Check out the
+            [`~PreTrainedModel.from_pretrained`] method to load the model weights.
+"""
+
+
+# Copied from transformers.models.llama.modeling_llama.LlamaPreTrainedModel with Llama->InternLM2
+@add_start_docstrings(
+    "The bare InternLM2 Model outputting raw hidden-states without any specific head on top.",
+    InternLM2_START_DOCSTRING,
+)
+class InternLM2PreTrainedModel(PreTrainedModel):
+    config_class = InternLM2Config
+    base_model_prefix = "model"
+    supports_gradient_checkpointing = True
+    _no_split_modules = ["InternLM2DecoderLayer"]
+    _skip_keys_device_placement = "past_key_values"
+
+    def _init_weights(self, module):
+        std = self.config.initializer_range
+        if isinstance(module, nn.Linear):
+            module.weight.data.normal_(mean=0.0, std=std)
+            if module.bias is not None:
+                module.bias.data.zero_()
+        elif isinstance(module, nn.Embedding):
+            module.weight.data.normal_(mean=0.0, std=std)
+            if module.padding_idx is not None:
+                module.weight.data[module.padding_idx].zero_()
+
+
+InternLM2_INPUTS_DOCSTRING = r"""
+    Args:
+        input_ids (`torch.LongTensor` of shape `(batch_size, sequence_length)`):
+            Indices of input sequence tokens in the vocabulary. Padding will be ignored by default should you provide
+            it.
+
+            Indices can be obtained using [`AutoTokenizer`]. See [`PreTrainedTokenizer.encode`] and
+            [`PreTrainedTokenizer.__call__`] for details.
+
+            [What are input IDs?](../glossary#input-ids)
+        attention_mask (`torch.Tensor` of shape `(batch_size, sequence_length)`, *optional*):
+            Mask to avoid performing attention on padding token indices. Mask values selected in `[0, 1]`:
+
+            - 1 for tokens that are **not masked**,
+            - 0 for tokens that are **masked**.
+
+            [What are attention masks?](../glossary#attention-mask)
+
+            Indices can be obtained using [`AutoTokenizer`]. See [`PreTrainedTokenizer.encode`] and
+            [`PreTrainedTokenizer.__call__`] for details.
+
+            If `past_key_values` is used, optionally only the last `input_ids` have to be input (see
+            `past_key_values`).
+
+            If you want to change padding behavior, you should read [`modeling_opt._prepare_decoder_attention_mask`]
+            and modify to your needs. See diagram 1 in [the paper](https://arxiv.org/abs/1910.13461) for more
+            information on the default strategy.
+
+            - 1 indicates the head is **not masked**,
+            - 0 indicates the head is **masked**.
+        position_ids (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*):
+            Indices of positions of each input sequence tokens in the position embeddings. Selected in the range `[0,
+            config.n_positions - 1]`.
+
+            [What are position IDs?](../glossary#position-ids)
+        past_key_values (`tuple(tuple(torch.FloatTensor))`, *optional*, returned when `use_cache=True` is passed or
+            when `config.use_cache=True`):
+            Tuple of `tuple(torch.FloatTensor)` of length `config.n_layers`, with each tuple having 2 tensors of shape
+            `(batch_size, num_heads, sequence_length, embed_size_per_head)`) and 2 additional tensors of shape
+            `(batch_size, num_heads, decoder_sequence_length, embed_size_per_head)`.
+
+            Contains pre-computed hidden-states (key and values in the self-attention blocks and in the cross-attention
+            blocks) that can be used (see `past_key_values` input) to speed up sequential decoding.
+
+            If `past_key_values` are used, the user can optionally input only the last `input_ids` (those that don't
+            have their past key value states given to this model) of shape `(batch_size, 1)` instead of all `input_ids`
+            of shape `(batch_size, sequence_length)`.
+        inputs_embeds (`torch.FloatTensor` of shape `(batch_size, sequence_length, hidden_size)`, *optional*):
+            Optionally, instead of passing `input_ids` you can choose to directly pass an embedded representation. This
+            is useful if you want more control over how to convert `input_ids` indices into associated vectors than the
+            model's internal embedding lookup matrix.
+        use_cache (`bool`, *optional*):
+            If set to `True`, `past_key_values` key value states are returned and can be used to speed up decoding (see
+            `past_key_values`).
+        output_attentions (`bool`, *optional*):
+            Whether or not to return the attentions tensors of all attention layers. See `attentions` under returned
+            tensors for more detail.
+        output_hidden_states (`bool`, *optional*):
+            Whether or not to return the hidden states of all layers. See `hidden_states` under returned tensors for
+            more detail.
+        return_dict (`bool`, *optional*):
+            Whether or not to return a [`~utils.ModelOutput`] instead of a plain tuple.
+"""
+
+
+# Modified from transformers.model.llama.modeling_llama.LlamaModel
+@add_start_docstrings(
+    "The bare InternLM2 Model outputting raw hidden-states without any specific head on top.",
+    InternLM2_START_DOCSTRING,
+)
+class InternLM2Model(InternLM2PreTrainedModel):
+    """
+    Transformer decoder consisting of *config.num_hidden_layers* layers. Each layer is a [`InternLM2DecoderLayer`]
+
+    Args:
+        config: InternLM2Config
+    """
+
+    _auto_class = "AutoModel"
+
+    def __init__(self, config: InternLM2Config):
+        super().__init__(config)
+        self.padding_idx = config.pad_token_id
+        self.vocab_size = config.vocab_size
+        self.config = config
+
+        self.tok_embeddings = nn.Embedding(config.vocab_size, config.hidden_size, self.padding_idx)
+
+        self.layers = nn.ModuleList([InternLM2DecoderLayer(config) for _ in range(config.num_hidden_layers)])
+        self.norm = InternLM2RMSNorm(config.hidden_size, eps=config.rms_norm_eps)
+
+        self.gradient_checkpointing = False
+        # Initialize weights and apply final processing
+        self.post_init()
+
+    def get_input_embeddings(self):
+        return self.tok_embeddings
+
+    def set_input_embeddings(self, value):
+        self.tok_embeddings = value
+
+    def _prepare_decoder_attention_mask(self, attention_mask, input_shape, inputs_embeds, past_key_values_length):
+        # create causal mask
+        # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len]
+        combined_attention_mask = None
+        if input_shape[-1] > 1:
+            combined_attention_mask = _make_causal_mask(
+                input_shape,
+                inputs_embeds.dtype,
+                device=inputs_embeds.device,
+                past_key_values_length=past_key_values_length,
+            )
+
+        if attention_mask is not None:
+            # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len]
+            expanded_attn_mask = _expand_mask(attention_mask, inputs_embeds.dtype, tgt_len=input_shape[-1]).to(
+                inputs_embeds.device
+            )
+            combined_attention_mask = (
+                expanded_attn_mask if combined_attention_mask is None else expanded_attn_mask + combined_attention_mask
+            )
+
+        return combined_attention_mask
+
+    @add_start_docstrings_to_model_forward(InternLM2_INPUTS_DOCSTRING)
+    def forward(
+        self,
+        input_ids: torch.LongTensor = None,
+        attention_mask: Optional[torch.Tensor] = None,
+        position_ids: Optional[torch.LongTensor] = None,
+        past_key_values: Optional[List[torch.FloatTensor]] = None,
+        inputs_embeds: Optional[torch.FloatTensor] = None,
+        use_cache: Optional[bool] = None,
+        output_attentions: Optional[bool] = None,
+        output_hidden_states: Optional[bool] = None,
+        return_dict: Optional[bool] = None,
+        **kwargs
+    ) -> Union[Tuple, BaseModelOutputWithPast]:
+
+        im_mask = kwargs.get('im_mask', None)
+
+        output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions
+        output_hidden_states = (
+            output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
+        )
+        use_cache = use_cache if use_cache is not None else self.config.use_cache
+
+        return_dict = return_dict if return_dict is not None else self.config.use_return_dict
+
+        if self.config.attn_implementation == "flash_attention_2":
+            _import_flash_attn()
+
+        # retrieve input_ids and inputs_embeds
+        if input_ids is not None and inputs_embeds is not None:
+            raise ValueError("You cannot specify both input_ids and inputs_embeds at the same time")
+        elif input_ids is not None:
+            batch_size, seq_length = input_ids.shape[:2]
+        elif inputs_embeds is not None:
+            batch_size, seq_length = inputs_embeds.shape[:2]
+        else:
+            raise ValueError("You have to specify either input_ids or inputs_embeds")
+
+        seq_length_with_past = seq_length
+        past_key_values_length = 0
+        if past_key_values is not None:
+            past_key_values_length = past_key_values[0][0].shape[2]
+            seq_length_with_past = seq_length_with_past + past_key_values_length
+
+        if position_ids is None:
+            device = input_ids.device if input_ids is not None else inputs_embeds.device
+            position_ids = torch.arange(
+                past_key_values_length, seq_length + past_key_values_length, dtype=torch.long, device=device
+            )
+            position_ids = position_ids.unsqueeze(0)
+
+        if inputs_embeds is None:
+            inputs_embeds = self.tok_embeddings(input_ids)
+            im_mask = torch.zeros(inputs_embeds.shape[:2]).to(inputs_embeds.device).bool()
+
+        if self.config.attn_implementation == "flash_attention_2":
+            # 2d mask is passed through the layers
+            attention_mask = attention_mask if (attention_mask is not None and 0 in attention_mask) else None
+        else:
+            if attention_mask is None:
+                attention_mask = torch.ones(
+                    (batch_size, seq_length_with_past), dtype=torch.bool, device=inputs_embeds.device
+                )
+            attention_mask = self._prepare_decoder_attention_mask(
+                attention_mask, (batch_size, seq_length), inputs_embeds, past_key_values_length
+            )
+
+        # embed positions
+        hidden_states = inputs_embeds
+
+        if self.gradient_checkpointing and self.training:
+            if use_cache:
+                logger.warning_once(
+                    "`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`..."
+                )
+                use_cache = False
+
+        # decoder layers
+        all_hidden_states = () if output_hidden_states else None
+        all_self_attns = () if output_attentions else None
+        next_decoder_cache = () if use_cache else None
+
+        for idx, decoder_layer in enumerate(self.layers):
+            if output_hidden_states:
+                all_hidden_states += (hidden_states,)
+
+            past_key_value = past_key_values[idx] if past_key_values is not None else None
+
+            if self.gradient_checkpointing and self.training:
+
+                def create_custom_forward(module):
+                    def custom_forward(*inputs):
+                        # None for past_key_value
+                        return module(*inputs, output_attentions, None, im_mask)
+
+                    return custom_forward
+
+                layer_outputs = torch.utils.checkpoint.checkpoint(
+                    create_custom_forward(decoder_layer),
+                    hidden_states,
+                    attention_mask,
+                    position_ids,
+                    None,
+                )
+            else:
+                layer_outputs = decoder_layer(
+                    hidden_states,
+                    attention_mask=attention_mask,
+                    position_ids=position_ids,
+                    past_key_value=past_key_value,
+                    output_attentions=output_attentions,
+                    use_cache=use_cache,
+                    im_mask=im_mask,
+                )
+
+            hidden_states = layer_outputs[0]
+
+            if use_cache:
+                next_decoder_cache += (layer_outputs[2 if output_attentions else 1],)
+
+            if output_attentions:
+                all_self_attns += (layer_outputs[1],)
+
+        hidden_states = self.norm(hidden_states)
+
+        # add hidden states from the last decoder layer
+        if output_hidden_states:
+            all_hidden_states += (hidden_states,)
+
+        next_cache = next_decoder_cache if use_cache else None
+        if not return_dict:
+            return tuple(v for v in [hidden_states, next_cache, all_hidden_states, all_self_attns] if v is not None)
+        return BaseModelOutputWithPast(
+            last_hidden_state=hidden_states,
+            past_key_values=next_cache,
+            hidden_states=all_hidden_states,
+            attentions=all_self_attns,
+        )
diff --git a/base/modeling_internlm_.py b/base/modeling_internlm_.py
new file mode 100644
index 0000000000000000000000000000000000000000..9ab466049f47d9c1e511a882b25de98f1848fff1
--- /dev/null
+++ b/base/modeling_internlm_.py
@@ -0,0 +1,1658 @@
+# Copyright (c) The InternLM team and The HuggingFace Inc. team. All rights reserved.
+#
+# This code is based on transformers/src/transformers/models/llama/modeling_llama.py
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+""" PyTorch InternLM2 model."""
+import math
+import queue
+import threading
+import warnings
+import copy
+import numpy as np
+from typing import List, Optional, Tuple, Union
+from torchvision import transforms
+from torchvision.transforms.functional import InterpolationMode
+from PIL import Image
+
+import re
+import torch
+import torch.nn.functional as F
+import torch.utils.checkpoint
+import torch.distributed as dist
+
+from einops import rearrange
+from torch import nn
+from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
+from transformers.activations import ACT2FN
+from transformers.modeling_outputs import (
+    BaseModelOutputWithPast,
+    CausalLMOutputWithPast,
+    SequenceClassifierOutputWithPast,
+)
+from transformers.modeling_utils import PreTrainedModel
+from transformers.utils import (
+    add_start_docstrings,
+    add_start_docstrings_to_model_forward,
+    logging,
+    replace_return_docstrings,
+)
+
+try:
+    from transformers.generation.streamers import BaseStreamer
+except:  # noqa # pylint: disable=bare-except
+    BaseStreamer = None
+
+from .configuration_internlm2 import InternLM2Config
+from .build_mlp import build_vision_tower, build_vision_projector, PLoRA
+
+logger = logging.get_logger(__name__)
+
+_CONFIG_FOR_DOC = "InternLM2Config"
+
+flash_attn_func, flash_attn_varlen_func = None, None
+pad_input, index_first_axis, unpad_input = None, None, None
+def _import_flash_attn():
+    global flash_attn_func, flash_attn_varlen_func
+    global pad_input, index_first_axis, unpad_input
+    try:
+        from flash_attn import flash_attn_func as _flash_attn_func, flash_attn_varlen_func as _flash_attn_varlen_func
+        from flash_attn.bert_padding import pad_input as _pad_input, index_first_axis as _index_first_axis, unpad_input as _unpad_input
+        flash_attn_func, flash_attn_varlen_func = _flash_attn_func, _flash_attn_varlen_func
+        pad_input, index_first_axis, unpad_input = _pad_input, _index_first_axis, _unpad_input
+    except ImportError:
+        raise ImportError("flash_attn is not installed.")
+
+# Copied from transformers.models.llama.modeling_llama._get_unpad_data
+def _get_unpad_data(attention_mask):
+    seqlens_in_batch = attention_mask.sum(dim=-1, dtype=torch.int32)
+    indices = torch.nonzero(attention_mask.flatten(), as_tuple=False).flatten()
+    max_seqlen_in_batch = seqlens_in_batch.max().item()
+    cu_seqlens = F.pad(torch.cumsum(seqlens_in_batch, dim=0, dtype=torch.torch.int32), (1, 0))
+    return (
+        indices,
+        cu_seqlens,
+        max_seqlen_in_batch,
+    )
+
+
+# Copied from transformers.models.bart.modeling_bart._make_causal_mask
+def _make_causal_mask(
+    input_ids_shape: torch.Size, dtype: torch.dtype, device: torch.device, past_key_values_length: int = 0
+):
+    """
+    Make causal mask used for bi-directional self-attention.
+    """
+    bsz, tgt_len = input_ids_shape
+    mask = torch.full((tgt_len, tgt_len), torch.tensor(torch.finfo(dtype).min, device=device), device=device)
+    mask_cond = torch.arange(mask.size(-1), device=device)
+    mask.masked_fill_(mask_cond < (mask_cond + 1).view(mask.size(-1), 1), 0)
+    mask = mask.to(dtype)
+
+    if past_key_values_length > 0:
+        mask = torch.cat([torch.zeros(tgt_len, past_key_values_length, dtype=dtype, device=device), mask], dim=-1)
+    return mask[None, None, :, :].expand(bsz, 1, tgt_len, tgt_len + past_key_values_length)
+
+
+# Copied from transformers.models.bart.modeling_bart._expand_mask
+def _expand_mask(mask: torch.Tensor, dtype: torch.dtype, tgt_len: Optional[int] = None):
+    """
+    Expands attention_mask from `[bsz, seq_len]` to `[bsz, 1, tgt_seq_len, src_seq_len]`.
+    """
+    bsz, src_len = mask.size()
+    tgt_len = tgt_len if tgt_len is not None else src_len
+
+    expanded_mask = mask[:, None, None, :].expand(bsz, 1, tgt_len, src_len).to(dtype)
+
+    inverted_mask = 1.0 - expanded_mask
+
+    return inverted_mask.masked_fill(inverted_mask.to(torch.bool), torch.finfo(dtype).min)
+
+
+# Copied from transformers.models.llama.modeling_llama.LlamaRMSNorm with Llama->InternLM2
+class InternLM2RMSNorm(nn.Module):
+    def __init__(self, hidden_size, eps=1e-6):
+        """
+        InternLM2RMSNorm is equivalent to T5LayerNorm
+        """
+        super().__init__()
+        self.weight = nn.Parameter(torch.ones(hidden_size))
+        self.variance_epsilon = eps
+
+    def forward(self, hidden_states):
+        input_dtype = hidden_states.dtype
+        hidden_states = hidden_states.to(torch.float32)
+        variance = hidden_states.pow(2).mean(-1, keepdim=True)
+        hidden_states = hidden_states * torch.rsqrt(variance + self.variance_epsilon)
+        return self.weight * hidden_states.to(input_dtype)
+
+
+# Copied from transformers.model.llama.modeling_llama.LlamaRotaryEmbedding with Llama->InternLM2
+class InternLM2RotaryEmbedding(nn.Module):
+    def __init__(self, dim, max_position_embeddings=2048, base=10000, device=None):
+        super().__init__()
+
+        self.dim = dim
+        self.max_position_embeddings = max_position_embeddings
+        self.base = base
+        inv_freq = 1.0 / (self.base ** (torch.arange(0, self.dim, 2).float().to(device) / self.dim))
+        self.register_buffer("inv_freq", inv_freq, persistent=False)
+
+        # Build here to make `torch.jit.trace` work.
+        self._set_cos_sin_cache(
+            seq_len=max_position_embeddings, device=self.inv_freq.device, dtype=torch.get_default_dtype()
+        )
+
+    def _set_cos_sin_cache(self, seq_len, device, dtype):
+        self.max_seq_len_cached = seq_len
+        t = torch.arange(self.max_seq_len_cached, device=device, dtype=self.inv_freq.dtype)
+
+        freqs = torch.einsum("i,j->ij", t, self.inv_freq)
+        # Different from paper, but it uses a different permutation in order to obtain the same calculation
+        emb = torch.cat((freqs, freqs), dim=-1)
+        self.register_buffer("cos_cached", emb.cos().to(dtype), persistent=False)
+        self.register_buffer("sin_cached", emb.sin().to(dtype), persistent=False)
+
+    def forward(self, x, seq_len=None):
+        # x: [bs, num_attention_heads, seq_len, head_size]
+        if seq_len > self.max_seq_len_cached:
+            self._set_cos_sin_cache(seq_len=seq_len, device=x.device, dtype=torch.float32)
+
+        return (
+            self.cos_cached[:seq_len].to(dtype=x.dtype),
+            self.sin_cached[:seq_len].to(dtype=x.dtype),
+        )
+
+
+# Copied from transformers.model.llama.modeling_llama.LlamaLinearScalingRotaryEmbedding with Llama->InternLM2
+class InternLM2LinearScalingRotaryEmbedding(InternLM2RotaryEmbedding):
+    """InternLM2RotaryEmbedding extended with linear scaling. Credits to the Reddit user /u/kaiokendev"""
+
+    def __init__(self, dim, max_position_embeddings=2048, base=10000, device=None, scaling_factor=1.0):
+        self.scaling_factor = scaling_factor
+        super().__init__(dim, max_position_embeddings, base, device)
+
+    def _set_cos_sin_cache(self, seq_len, device, dtype):
+        self.max_seq_len_cached = seq_len
+        t = torch.arange(self.max_seq_len_cached, device=device, dtype=self.inv_freq.dtype)
+        t = t / self.scaling_factor
+
+        freqs = torch.einsum("i,j->ij", t, self.inv_freq)
+        # Different from paper, but it uses a different permutation in order to obtain the same calculation
+        emb = torch.cat((freqs, freqs), dim=-1)
+        self.register_buffer("cos_cached", emb.cos().to(dtype), persistent=False)
+        self.register_buffer("sin_cached", emb.sin().to(dtype), persistent=False)
+
+
+# Copied from transformers.model.llama.modeling_llama.LlamaDynamicNTKScalingRotaryEmbedding with Llama->InternLM2
+class InternLM2DynamicNTKScalingRotaryEmbedding(InternLM2RotaryEmbedding):
+    """InternLM2RotaryEmbedding extended with Dynamic NTK scaling.
+    Credits to the Reddit users /u/bloc97 and /u/emozilla.
+    """
+
+    def __init__(self, dim, max_position_embeddings=2048, base=10000, device=None, scaling_factor=1.0):
+        self.scaling_factor = scaling_factor
+        super().__init__(dim, max_position_embeddings, base, device)
+
+    def _set_cos_sin_cache(self, seq_len, device, dtype):
+        self.max_seq_len_cached = seq_len
+
+        if seq_len > self.max_position_embeddings:
+            base = self.base * (
+                (self.scaling_factor * seq_len / self.max_position_embeddings) - (self.scaling_factor - 1)
+            ) ** (self.dim / (self.dim - 2))
+            inv_freq = 1.0 / (base ** (torch.arange(0, self.dim, 2).float().to(device) / self.dim))
+            self.register_buffer("inv_freq", inv_freq, persistent=False)
+
+        t = torch.arange(self.max_seq_len_cached, device=device, dtype=self.inv_freq.dtype)
+
+        freqs = torch.einsum("i,j->ij", t, self.inv_freq)
+        # Different from paper, but it uses a different permutation in order to obtain the same calculation
+        emb = torch.cat((freqs, freqs), dim=-1)
+        self.register_buffer("cos_cached", emb.cos().to(dtype), persistent=False)
+        self.register_buffer("sin_cached", emb.sin().to(dtype), persistent=False)
+
+
+# Copied from transformers.model.llama.modeling_llama.rotate_half
+def rotate_half(x):
+    """Rotates half the hidden dims of the input."""
+    x1 = x[..., : x.shape[-1] // 2]
+    x2 = x[..., x.shape[-1] // 2 :]
+    return torch.cat((-x2, x1), dim=-1)
+
+
+# Copied from transformers.model.llama.modeling_llama.apply_rotary_pos_emb
+def apply_rotary_pos_emb(q, k, cos, sin, position_ids, unsqueeze_dim=1):
+    """Applies Rotary Position Embedding to the query and key tensors."""
+    cos = cos[position_ids].unsqueeze(unsqueeze_dim)
+    sin = sin[position_ids].unsqueeze(unsqueeze_dim)
+    q_embed = (q * cos) + (rotate_half(q) * sin)
+    k_embed = (k * cos) + (rotate_half(k) * sin)
+    return q_embed, k_embed
+
+
+class InternLM2MLP(nn.Module):
+    def __init__(self, config):
+        super().__init__()
+        self.config = config
+        self.hidden_size = config.hidden_size
+        self.intermediate_size = config.intermediate_size
+        #self.w1 = nn.Linear(self.hidden_size, self.intermediate_size, bias=False)
+        #self.w3 = nn.Linear(self.hidden_size, self.intermediate_size, bias=False)
+        #self.w2 = nn.Linear(self.intermediate_size, self.hidden_size, bias=False)
+        
+        self.w1 = PLoRA(self.hidden_size, self.intermediate_size, bias=False,
+                            lora_r=256, lora_alpha=256, lora_len=1225)
+        self.w3 = PLoRA(self.hidden_size, self.intermediate_size, bias=False,
+                            lora_r=256, lora_alpha=256, lora_len=1225)
+        self.w2 = PLoRA(self.intermediate_size, self.hidden_size, bias=False,
+                            lora_r=256, lora_alpha=256, lora_len=1225)
+
+        self.act_fn = ACT2FN[config.hidden_act]
+
+    def forward(self, x, im_mask):
+        down_proj = self.w2(self.act_fn(self.w1(x, im_mask)) * self.w3(x, im_mask), im_mask)
+
+        return down_proj
+
+
+# Copied from transformers.model.llama.modeling_llama.repeat_kv
+def repeat_kv(hidden_states: torch.Tensor, n_rep: int) -> torch.Tensor:
+    """
+    This is the equivalent of torch.repeat_interleave(x, dim=1, repeats=n_rep). The hidden states go from (batch,
+    num_key_value_heads, seqlen, head_dim) to (batch, num_attention_heads, seqlen, head_dim)
+    """
+    batch, num_key_value_heads, slen, head_dim = hidden_states.shape
+    if n_rep == 1:
+        return hidden_states
+    hidden_states = hidden_states[:, :, None, :, :].expand(batch, num_key_value_heads, n_rep, slen, head_dim)
+    return hidden_states.reshape(batch, num_key_value_heads * n_rep, slen, head_dim)
+
+
+# Modified from transformers.model.llama.modeling_llama.LlamaAttention
+class InternLM2Attention(nn.Module):
+    """Multi-headed attention from 'Attention Is All You Need' paper"""
+
+    def __init__(self, config: InternLM2Config):
+        super().__init__()
+        self.config = config
+        self.hidden_size = config.hidden_size
+        self.num_heads = config.num_attention_heads
+        self.head_dim = self.hidden_size // self.num_heads
+        self.num_key_value_heads = config.num_key_value_heads
+        self.num_key_value_groups = self.num_heads // self.num_key_value_heads
+        self.max_position_embeddings = config.max_position_embeddings
+        self.is_causal = True
+
+        if (self.head_dim * self.num_heads) != self.hidden_size:
+            raise ValueError(
+                f"hidden_size must be divisible by num_heads (got `hidden_size`: {self.hidden_size}"
+                f" and `num_heads`: {self.num_heads})."
+            )
+
+        #self.wqkv = nn.Linear(
+        self.wqkv = PLoRA(
+            self.hidden_size,
+            (self.num_heads + 2 * self.num_key_value_heads) * self.head_dim,
+            bias=config.bias,
+            lora_r=256, lora_alpha=256, lora_len=1225
+        )
+
+        #self.wo = nn.Linear(self.num_heads * self.head_dim, self.hidden_size, bias=config.bias)
+        self.wo = PLoRA(self.num_heads * self.head_dim, self.hidden_size, bias=config.bias,
+                           lora_r=256, lora_alpha=256, lora_len=1225)
+        self._init_rope()
+    
+    def _init_rope(self):
+        if self.config.rope_scaling is None:
+            self.rotary_emb = InternLM2RotaryEmbedding(
+                self.head_dim,
+                max_position_embeddings=self.max_position_embeddings,
+                base=self.config.rope_theta,
+            )
+        else:
+            scaling_type = self.config.rope_scaling["type"]
+            scaling_factor = self.config.rope_scaling["factor"]
+            if scaling_type == "dynamic":
+                self.rotary_emb = InternLM2DynamicNTKScalingRotaryEmbedding(
+                    self.head_dim,
+                    max_position_embeddings=self.max_position_embeddings,
+                    base=self.config.rope_theta,
+                    scaling_factor=scaling_factor,
+                )
+            elif scaling_type == "linear":
+                self.rotary_emb = InternLM2LinearScalingRotaryEmbedding(
+                    self.head_dim,
+                    max_position_embeddings=self.max_position_embeddings,
+                    base=self.config.rope_theta,
+                    scaling_factor=scaling_factor,
+                )
+            else:
+                raise ValueError("Currently we only support rotary embedding's type being 'dynamic' or 'linear'.")
+        return self.rotary_emb
+
+    def _shape(self, tensor: torch.Tensor, seq_len: int, bsz: int):
+        return tensor.view(bsz, seq_len, self.num_heads, self.head_dim).transpose(1, 2).contiguous()
+
+    def forward(
+        self,
+        hidden_states: torch.Tensor,
+        attention_mask: Optional[torch.Tensor] = None,
+        position_ids: Optional[torch.LongTensor] = None,
+        past_key_value: Optional[Tuple[torch.Tensor]] = None,
+        output_attentions: bool = False,
+        use_cache: bool = False,
+        im_mask: Optional[Tuple[torch.Tensor]] = None,
+        **kwargs,
+    ) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[Tuple[torch.Tensor]]]:
+        if "padding_mask" in kwargs:
+            warnings.warn(
+                "Passing `padding_mask` is deprecated and will be removed in v4.37. "
+                "Please make sure use `attention_mask` instead.`"
+            )
+
+        bsz, q_len, _ = hidden_states.size()
+
+        qkv_states = self.wqkv(hidden_states, im_mask)
+
+        qkv_states = rearrange(
+            qkv_states,
+            "b q (h gs d) -> b q h gs d",
+            gs=2 + self.num_key_value_groups,
+            d=self.head_dim,
+        )
+
+        query_states = qkv_states[..., : self.num_key_value_groups, :]
+        query_states = rearrange(query_states, "b q h gs d -> b q (h gs) d")
+        key_states = qkv_states[..., -2, :]
+        value_states = qkv_states[..., -1, :]
+
+        query_states = query_states.transpose(1, 2)
+        key_states = key_states.transpose(1, 2)
+        value_states = value_states.transpose(1, 2)
+
+        kv_seq_len = key_states.shape[-2]
+        if past_key_value is not None:
+            kv_seq_len += past_key_value[0].shape[-2]
+        cos, sin = self.rotary_emb(value_states, seq_len=kv_seq_len)
+        query_states, key_states = apply_rotary_pos_emb(query_states, key_states, cos, sin, position_ids)
+
+        if past_key_value is not None:
+            # reuse k, v, self_attention
+            key_states = torch.cat([past_key_value[0], key_states], dim=2)
+            value_states = torch.cat([past_key_value[1], value_states], dim=2)
+
+        past_key_value = (key_states, value_states) if use_cache else None
+
+        key_states = repeat_kv(key_states, self.num_key_value_groups)
+        value_states = repeat_kv(value_states, self.num_key_value_groups)
+
+        attn_weights = torch.matmul(query_states, key_states.transpose(2, 3)) / math.sqrt(self.head_dim)
+
+        if attn_weights.size() != (bsz, self.num_heads, q_len, kv_seq_len):
+            raise ValueError(
+                f"Attention weights should be of size {(bsz, self.num_heads, q_len, kv_seq_len)}, but is"
+                f" {attn_weights.size()}"
+            )
+
+        if attention_mask is not None:
+            if attention_mask.size() != (bsz, 1, q_len, kv_seq_len):
+                raise ValueError(
+                    f"Attention mask should be of size {(bsz, 1, q_len, kv_seq_len)}, but is {attention_mask.size()}"
+                )
+            attn_weights = attn_weights + attention_mask
+
+        # upcast attention to fp32
+        attn_weights = nn.functional.softmax(attn_weights, dim=-1, dtype=torch.float32).to(query_states.dtype)
+        attn_output = torch.matmul(attn_weights, value_states)
+
+        if attn_output.size() != (bsz, self.num_heads, q_len, self.head_dim):
+            raise ValueError(
+                f"`attn_output` should be of size {(bsz, self.num_heads, q_len, self.head_dim)}, but is"
+                f" {attn_output.size()}"
+            )
+
+        attn_output = attn_output.transpose(1, 2).contiguous()
+        attn_output = attn_output.reshape(bsz, q_len, self.hidden_size)
+
+        attn_output = self.wo(attn_output, im_mask)
+
+        if not output_attentions:
+            attn_weights = None
+
+        return attn_output, attn_weights, past_key_value
+
+
+# Modified from transformers.model.llama.modeling_llama.InternLM2FlashAttention2
+class InternLM2FlashAttention2(InternLM2Attention):
+    """
+    InternLM2 flash attention module. This module inherits from `InternLM2Attention` as the weights of the module stays
+    untouched. The only required change would be on the forward pass where it needs to correctly call the public API of
+    flash attention and deal with padding tokens in case the input contains any of them.
+    """
+
+    def forward(
+        self,
+        hidden_states: torch.Tensor,
+        attention_mask: Optional[torch.LongTensor] = None,
+        position_ids: Optional[torch.LongTensor] = None,
+        past_key_value: Optional[Tuple[torch.Tensor]] = None,
+        output_attentions: bool = False,
+        use_cache: bool = False,
+        im_mask: Optional[Tuple[torch.Tensor]] = None,
+        **kwargs,
+    ) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[Tuple[torch.Tensor]]]:
+        # InternLM2FlashAttention2 attention does not support output_attentions
+        if "padding_mask" in kwargs:
+            warnings.warn(
+                "Passing `padding_mask` is deprecated and will be removed in v4.37. "
+                "Please make sure use `attention_mask` instead.`"
+            )
+
+            # overwrite attention_mask with padding_mask
+            attention_mask = kwargs.pop("padding_mask")
+
+        output_attentions = False
+
+        bsz, q_len, _ = hidden_states.size()
+
+        qkv_states = self.wqkv(hidden_states, im_mask)
+
+        qkv_states = rearrange(
+            qkv_states,
+            "b q (h gs d) -> b q h gs d",
+            gs=2 + self.num_key_value_groups,
+            d=self.head_dim,
+        )
+
+        query_states = qkv_states[..., : self.num_key_value_groups, :]
+        query_states = rearrange(query_states, "b q h gs d -> b q (h gs) d")
+        key_states = qkv_states[..., -2, :]
+        value_states = qkv_states[..., -1, :]
+
+        query_states = query_states.transpose(1, 2)
+        key_states = key_states.transpose(1, 2)
+        value_states = value_states.transpose(1, 2)
+
+        kv_seq_len = key_states.shape[-2]
+        if past_key_value is not None:
+            kv_seq_len += past_key_value[0].shape[-2]
+
+        cos, sin = self.rotary_emb(value_states, seq_len=kv_seq_len)
+
+        query_states, key_states = apply_rotary_pos_emb(query_states, key_states, cos, sin, position_ids)
+
+        if past_key_value is not None:
+            # reuse k, v, self_attention
+            key_states = torch.cat([past_key_value[0], key_states], dim=2)
+            value_states = torch.cat([past_key_value[1], value_states], dim=2)
+
+        past_key_value = (key_states, value_states) if use_cache else None
+
+        query_states = query_states.transpose(1, 2)
+        key_states = key_states.transpose(1, 2)
+        value_states = value_states.transpose(1, 2)
+
+        attn_output = self._flash_attention_forward(
+            query_states, key_states, value_states, attention_mask, q_len
+        )
+
+        attn_output = attn_output.reshape(bsz, q_len, self.hidden_size).contiguous()
+        attn_output = self.wo(attn_output, im_mask)
+
+        if not output_attentions:
+            attn_weights = None
+
+        return attn_output, attn_weights, past_key_value
+
+    def _flash_attention_forward(
+        self, query_states, key_states, value_states, attention_mask, query_length, dropout=0.0, softmax_scale=None
+    ):
+        """
+        Calls the forward method of Flash Attention - if the input hidden states contain at least one padding token
+        first unpad the input, then computes the attention scores and pad the final attention scores.
+
+        Args:
+            query_states (`torch.Tensor`):
+                Input query states to be passed to Flash Attention API
+            key_states (`torch.Tensor`):
+                Input key states to be passed to Flash Attention API
+            value_states (`torch.Tensor`):
+                Input value states to be passed to Flash Attention API
+            attention_mask (`torch.Tensor`):
+                The padding mask - corresponds to a tensor of size `(batch_size, seq_len)` where 0 stands for the
+                position of padding tokens and 1 for the position of non-padding tokens.
+            dropout (`int`, *optional*):
+                Attention dropout
+            softmax_scale (`float`, *optional*):
+                The scaling of QK^T before applying softmax. Default to 1 / sqrt(head_dim)
+        """
+        # Contains at least one padding token in the sequence
+        causal = self.is_causal and query_length != 1
+        if attention_mask is not None:
+            batch_size = query_states.shape[0]
+            query_states, key_states, value_states, indices_q, cu_seq_lens, max_seq_lens = self._unpad_input(
+                query_states, key_states, value_states, attention_mask, query_length
+            )
+
+            cu_seqlens_q, cu_seqlens_k = cu_seq_lens
+            max_seqlen_in_batch_q, max_seqlen_in_batch_k = max_seq_lens
+
+            attn_output_unpad = flash_attn_varlen_func(
+                query_states,
+                key_states,
+                value_states,
+                cu_seqlens_q=cu_seqlens_q,
+                cu_seqlens_k=cu_seqlens_k,
+                max_seqlen_q=max_seqlen_in_batch_q,
+                max_seqlen_k=max_seqlen_in_batch_k,
+                dropout_p=dropout,
+                softmax_scale=softmax_scale,
+                causal=causal,
+            )
+
+            attn_output = pad_input(attn_output_unpad, indices_q, batch_size, query_length)
+        else:
+            attn_output = flash_attn_func(
+                query_states, key_states, value_states, dropout, softmax_scale=softmax_scale, causal=causal
+            )
+
+        return attn_output
+
+    def _unpad_input(self, query_layer, key_layer, value_layer, attention_mask, query_length):
+        indices_k, cu_seqlens_k, max_seqlen_in_batch_k = _get_unpad_data(attention_mask)
+        batch_size, kv_seq_len, num_key_value_heads, head_dim = key_layer.shape
+
+        key_layer = index_first_axis(
+            key_layer.reshape(batch_size * kv_seq_len, num_key_value_heads, head_dim), indices_k
+        )
+        value_layer = index_first_axis(
+            value_layer.reshape(batch_size * kv_seq_len, num_key_value_heads, head_dim), indices_k
+        )
+
+        if query_length == kv_seq_len:
+            query_layer = index_first_axis(
+                query_layer.reshape(batch_size * kv_seq_len, self.num_heads, head_dim), indices_k
+            )
+            cu_seqlens_q = cu_seqlens_k
+            max_seqlen_in_batch_q = max_seqlen_in_batch_k
+            indices_q = indices_k
+        elif query_length == 1:
+            max_seqlen_in_batch_q = 1
+            cu_seqlens_q = torch.arange(
+                batch_size + 1, dtype=torch.int32, device=query_layer.device
+            )  # There is a memcpy here, that is very bad.
+            indices_q = cu_seqlens_q[:-1]
+            query_layer = query_layer.squeeze(1)
+        else:
+            # The -q_len: slice assumes left padding.
+            attention_mask = attention_mask[:, -query_length:]
+            query_layer, indices_q, cu_seqlens_q, max_seqlen_in_batch_q = unpad_input(query_layer, attention_mask)
+
+        return (
+            query_layer,
+            key_layer,
+            value_layer,
+            indices_q.to(torch.int64),
+            (cu_seqlens_q, cu_seqlens_k),
+            (max_seqlen_in_batch_q, max_seqlen_in_batch_k),
+        )
+
+INTERNLM2_ATTENTION_CLASSES = {
+    "eager": InternLM2Attention,
+    "flash_attention_2": InternLM2FlashAttention2,
+}
+
+# Modified from transformers.model.llama.modeling_llama.LlamaDecoderLayer
+class InternLM2DecoderLayer(nn.Module):
+    def __init__(self, config: InternLM2Config):
+        super().__init__()
+        self.hidden_size = config.hidden_size
+
+        self.attention = INTERNLM2_ATTENTION_CLASSES[config.attn_implementation](config=config)
+
+        self.feed_forward = InternLM2MLP(config)
+        self.attention_norm = InternLM2RMSNorm(config.hidden_size, eps=config.rms_norm_eps)
+        self.ffn_norm = InternLM2RMSNorm(config.hidden_size, eps=config.rms_norm_eps)
+
+    def forward(
+        self,
+        hidden_states: torch.Tensor,
+        attention_mask: Optional[torch.Tensor] = None,
+        position_ids: Optional[torch.LongTensor] = None,
+        past_key_value: Optional[Tuple[torch.Tensor]] = None,
+        output_attentions: Optional[bool] = False,
+        use_cache: Optional[bool] = False,
+        im_mask: Optional[Tuple[torch.Tensor]] = None,
+        **kwargs,
+    ) -> Tuple[torch.FloatTensor, Optional[Tuple[torch.FloatTensor, torch.FloatTensor]]]:
+        """
+        Args:
+            hidden_states (`torch.FloatTensor`): input to the layer of shape `(batch, seq_len, embed_dim)`
+            attention_mask (`torch.FloatTensor`, *optional*):
+                attention mask of size `(batch_size, sequence_length)` if flash attention is used or `(batch_size, 1,
+                query_sequence_length, key_sequence_length)` if default attention is used.
+            output_attentions (`bool`, *optional*):
+                Whether or not to return the attentions tensors of all attention layers. See `attentions` under
+                returned tensors for more detail.
+            use_cache (`bool`, *optional*):
+                If set to `True`, `past_key_values` key value states are returned and can be used to speed up decoding
+                (see `past_key_values`).
+            past_key_value (`Tuple(torch.FloatTensor)`, *optional*): cached past key and value projection states
+        """
+        if "padding_mask" in kwargs:
+            warnings.warn(
+                "Passing `padding_mask` is deprecated and will be removed in v4.37. "
+                "Please make sure use `attention_mask` instead.`"
+            )
+
+        residual = hidden_states
+
+        hidden_states = self.attention_norm(hidden_states)
+
+        # Self Attention
+        hidden_states, self_attn_weights, present_key_value = self.attention(
+            hidden_states=hidden_states,
+            attention_mask=attention_mask,
+            position_ids=position_ids,
+            past_key_value=past_key_value,
+            output_attentions=output_attentions,
+            use_cache=use_cache,
+            im_mask=im_mask,
+            **kwargs,
+        )
+        hidden_states = residual + hidden_states
+
+        # Fully Connected
+        residual = hidden_states
+        hidden_states = self.ffn_norm(hidden_states)
+        hidden_states = self.feed_forward(hidden_states, im_mask)
+        hidden_states = residual + hidden_states
+
+        outputs = (hidden_states,)
+
+        if output_attentions:
+            outputs += (self_attn_weights,)
+
+        if use_cache:
+            outputs += (present_key_value,)
+
+        return outputs
+
+
+InternLM2_START_DOCSTRING = r"""
+    This model inherits from [`PreTrainedModel`]. Check the superclass documentation for the generic methods the
+    library implements for all its model (such as downloading or saving, resizing the input embeddings, pruning heads
+    etc.)
+
+    This model is also a PyTorch [torch.nn.Module](https://pytorch.org/docs/stable/nn.html#torch.nn.Module) subclass.
+    Use it as a regular PyTorch Module and refer to the PyTorch documentation for all matter related to general usage
+    and behavior.
+
+    Parameters:
+        config ([`InternLM2Config`]):
+            Model configuration class with all the parameters of the model. Initializing with a config file does not
+            load the weights associated with the model, only the configuration. Check out the
+            [`~PreTrainedModel.from_pretrained`] method to load the model weights.
+"""
+
+
+# Copied from transformers.models.llama.modeling_llama.LlamaPreTrainedModel with Llama->InternLM2
+@add_start_docstrings(
+    "The bare InternLM2 Model outputting raw hidden-states without any specific head on top.",
+    InternLM2_START_DOCSTRING,
+)
+class InternLM2PreTrainedModel(PreTrainedModel):
+    config_class = InternLM2Config
+    base_model_prefix = "model"
+    supports_gradient_checkpointing = True
+    _no_split_modules = ["InternLM2DecoderLayer"]
+    _skip_keys_device_placement = "past_key_values"
+
+    def _init_weights(self, module):
+        std = self.config.initializer_range
+        if isinstance(module, nn.Linear):
+            module.weight.data.normal_(mean=0.0, std=std)
+            if module.bias is not None:
+                module.bias.data.zero_()
+        elif isinstance(module, nn.Embedding):
+            module.weight.data.normal_(mean=0.0, std=std)
+            if module.padding_idx is not None:
+                module.weight.data[module.padding_idx].zero_()
+
+
+InternLM2_INPUTS_DOCSTRING = r"""
+    Args:
+        input_ids (`torch.LongTensor` of shape `(batch_size, sequence_length)`):
+            Indices of input sequence tokens in the vocabulary. Padding will be ignored by default should you provide
+            it.
+
+            Indices can be obtained using [`AutoTokenizer`]. See [`PreTrainedTokenizer.encode`] and
+            [`PreTrainedTokenizer.__call__`] for details.
+
+            [What are input IDs?](../glossary#input-ids)
+        attention_mask (`torch.Tensor` of shape `(batch_size, sequence_length)`, *optional*):
+            Mask to avoid performing attention on padding token indices. Mask values selected in `[0, 1]`:
+
+            - 1 for tokens that are **not masked**,
+            - 0 for tokens that are **masked**.
+
+            [What are attention masks?](../glossary#attention-mask)
+
+            Indices can be obtained using [`AutoTokenizer`]. See [`PreTrainedTokenizer.encode`] and
+            [`PreTrainedTokenizer.__call__`] for details.
+
+            If `past_key_values` is used, optionally only the last `input_ids` have to be input (see
+            `past_key_values`).
+
+            If you want to change padding behavior, you should read [`modeling_opt._prepare_decoder_attention_mask`]
+            and modify to your needs. See diagram 1 in [the paper](https://arxiv.org/abs/1910.13461) for more
+            information on the default strategy.
+
+            - 1 indicates the head is **not masked**,
+            - 0 indicates the head is **masked**.
+        position_ids (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*):
+            Indices of positions of each input sequence tokens in the position embeddings. Selected in the range `[0,
+            config.n_positions - 1]`.
+
+            [What are position IDs?](../glossary#position-ids)
+        past_key_values (`tuple(tuple(torch.FloatTensor))`, *optional*, returned when `use_cache=True` is passed or
+            when `config.use_cache=True`):
+            Tuple of `tuple(torch.FloatTensor)` of length `config.n_layers`, with each tuple having 2 tensors of shape
+            `(batch_size, num_heads, sequence_length, embed_size_per_head)`) and 2 additional tensors of shape
+            `(batch_size, num_heads, decoder_sequence_length, embed_size_per_head)`.
+
+            Contains pre-computed hidden-states (key and values in the self-attention blocks and in the cross-attention
+            blocks) that can be used (see `past_key_values` input) to speed up sequential decoding.
+
+            If `past_key_values` are used, the user can optionally input only the last `input_ids` (those that don't
+            have their past key value states given to this model) of shape `(batch_size, 1)` instead of all `input_ids`
+            of shape `(batch_size, sequence_length)`.
+        inputs_embeds (`torch.FloatTensor` of shape `(batch_size, sequence_length, hidden_size)`, *optional*):
+            Optionally, instead of passing `input_ids` you can choose to directly pass an embedded representation. This
+            is useful if you want more control over how to convert `input_ids` indices into associated vectors than the
+            model's internal embedding lookup matrix.
+        use_cache (`bool`, *optional*):
+            If set to `True`, `past_key_values` key value states are returned and can be used to speed up decoding (see
+            `past_key_values`).
+        output_attentions (`bool`, *optional*):
+            Whether or not to return the attentions tensors of all attention layers. See `attentions` under returned
+            tensors for more detail.
+        output_hidden_states (`bool`, *optional*):
+            Whether or not to return the hidden states of all layers. See `hidden_states` under returned tensors for
+            more detail.
+        return_dict (`bool`, *optional*):
+            Whether or not to return a [`~utils.ModelOutput`] instead of a plain tuple.
+"""
+
+
+# Modified from transformers.model.llama.modeling_llama.LlamaModel
+@add_start_docstrings(
+    "The bare InternLM2 Model outputting raw hidden-states without any specific head on top.",
+    InternLM2_START_DOCSTRING,
+)
+class InternLM2Model(InternLM2PreTrainedModel):
+    """
+    Transformer decoder consisting of *config.num_hidden_layers* layers. Each layer is a [`InternLM2DecoderLayer`]
+
+    Args:
+        config: InternLM2Config
+    """
+
+    _auto_class = "AutoModel"
+
+    def __init__(self, config: InternLM2Config):
+        super().__init__(config)
+        self.padding_idx = config.pad_token_id
+        self.vocab_size = config.vocab_size
+        self.config = config
+
+        self.tok_embeddings = nn.Embedding(config.vocab_size, config.hidden_size, self.padding_idx)
+
+        self.layers = nn.ModuleList([InternLM2DecoderLayer(config) for _ in range(config.num_hidden_layers)])
+        self.norm = InternLM2RMSNorm(config.hidden_size, eps=config.rms_norm_eps)
+
+        self.gradient_checkpointing = False
+        # Initialize weights and apply final processing
+        self.post_init()
+
+    def get_input_embeddings(self):
+        return self.tok_embeddings
+
+    def set_input_embeddings(self, value):
+        self.tok_embeddings = value
+
+    def _prepare_decoder_attention_mask(self, attention_mask, input_shape, inputs_embeds, past_key_values_length):
+        # create causal mask
+        # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len]
+        combined_attention_mask = None
+        if input_shape[-1] > 1:
+            combined_attention_mask = _make_causal_mask(
+                input_shape,
+                inputs_embeds.dtype,
+                device=inputs_embeds.device,
+                past_key_values_length=past_key_values_length,
+            )
+
+        if attention_mask is not None:
+            # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len]
+            expanded_attn_mask = _expand_mask(attention_mask, inputs_embeds.dtype, tgt_len=input_shape[-1]).to(
+                inputs_embeds.device
+            )
+            combined_attention_mask = (
+                expanded_attn_mask if combined_attention_mask is None else expanded_attn_mask + combined_attention_mask
+            )
+
+        return combined_attention_mask
+
+    @add_start_docstrings_to_model_forward(InternLM2_INPUTS_DOCSTRING)
+    def forward(
+        self,
+        input_ids: torch.LongTensor = None,
+        attention_mask: Optional[torch.Tensor] = None,
+        position_ids: Optional[torch.LongTensor] = None,
+        past_key_values: Optional[List[torch.FloatTensor]] = None,
+        inputs_embeds: Optional[torch.FloatTensor] = None,
+        use_cache: Optional[bool] = None,
+        output_attentions: Optional[bool] = None,
+        output_hidden_states: Optional[bool] = None,
+        return_dict: Optional[bool] = None,
+        **kwargs
+    ) -> Union[Tuple, BaseModelOutputWithPast]:
+
+        im_mask = kwargs.get('im_mask', None)
+
+        output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions
+        output_hidden_states = (
+            output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
+        )
+        use_cache = use_cache if use_cache is not None else self.config.use_cache
+
+        return_dict = return_dict if return_dict is not None else self.config.use_return_dict
+
+        if self.config.attn_implementation == "flash_attention_2":
+            _import_flash_attn()
+
+        # retrieve input_ids and inputs_embeds
+        if input_ids is not None and inputs_embeds is not None:
+            raise ValueError("You cannot specify both input_ids and inputs_embeds at the same time")
+        elif input_ids is not None:
+            batch_size, seq_length = input_ids.shape[:2]
+        elif inputs_embeds is not None:
+            batch_size, seq_length = inputs_embeds.shape[:2]
+        else:
+            raise ValueError("You have to specify either input_ids or inputs_embeds")
+
+        seq_length_with_past = seq_length
+        past_key_values_length = 0
+        if past_key_values is not None:
+            past_key_values_length = past_key_values[0][0].shape[2]
+            seq_length_with_past = seq_length_with_past + past_key_values_length
+
+        if position_ids is None:
+            device = input_ids.device if input_ids is not None else inputs_embeds.device
+            position_ids = torch.arange(
+                past_key_values_length, seq_length + past_key_values_length, dtype=torch.long, device=device
+            )
+            position_ids = position_ids.unsqueeze(0)
+
+        if inputs_embeds is None:
+            inputs_embeds = self.tok_embeddings(input_ids)
+            im_mask = torch.zeros(inputs_embeds.shape[:2]).to(inputs_embeds.device).bool()
+
+        if self.config.attn_implementation == "flash_attention_2":
+            # 2d mask is passed through the layers
+            attention_mask = attention_mask if (attention_mask is not None and 0 in attention_mask) else None
+        else:
+            if attention_mask is None:
+                attention_mask = torch.ones(
+                    (batch_size, seq_length_with_past), dtype=torch.bool, device=inputs_embeds.device
+                )
+            attention_mask = self._prepare_decoder_attention_mask(
+                attention_mask, (batch_size, seq_length), inputs_embeds, past_key_values_length
+            )
+
+        # embed positions
+        hidden_states = inputs_embeds
+
+        if self.gradient_checkpointing and self.training:
+            if use_cache:
+                logger.warning_once(
+                    "`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`..."
+                )
+                use_cache = False
+
+        # decoder layers
+        all_hidden_states = () if output_hidden_states else None
+        all_self_attns = () if output_attentions else None
+        next_decoder_cache = () if use_cache else None
+
+        for idx, decoder_layer in enumerate(self.layers):
+            if output_hidden_states:
+                all_hidden_states += (hidden_states,)
+
+            past_key_value = past_key_values[idx] if past_key_values is not None else None
+
+            if self.gradient_checkpointing and self.training:
+
+                def create_custom_forward(module):
+                    def custom_forward(*inputs):
+                        # None for past_key_value
+                        return module(*inputs, output_attentions, None, im_mask)
+
+                    return custom_forward
+
+                layer_outputs = torch.utils.checkpoint.checkpoint(
+                    create_custom_forward(decoder_layer),
+                    hidden_states,
+                    attention_mask,
+                    position_ids,
+                    None,
+                )
+            else:
+                layer_outputs = decoder_layer(
+                    hidden_states,
+                    attention_mask=attention_mask,
+                    position_ids=position_ids,
+                    past_key_value=past_key_value,
+                    output_attentions=output_attentions,
+                    use_cache=use_cache,
+                    im_mask=im_mask,
+                )
+
+            hidden_states = layer_outputs[0]
+
+            if use_cache:
+                next_decoder_cache += (layer_outputs[2 if output_attentions else 1],)
+
+            if output_attentions:
+                all_self_attns += (layer_outputs[1],)
+
+        hidden_states = self.norm(hidden_states)
+
+        # add hidden states from the last decoder layer
+        if output_hidden_states:
+            all_hidden_states += (hidden_states,)
+
+        next_cache = next_decoder_cache if use_cache else None
+        if not return_dict:
+            return tuple(v for v in [hidden_states, next_cache, all_hidden_states, all_self_attns] if v is not None)
+        return BaseModelOutputWithPast(
+            last_hidden_state=hidden_states,
+            past_key_values=next_cache,
+            hidden_states=all_hidden_states,
+            attentions=all_self_attns,
+        )
+
+
+# Modified from transformers.model.llama.modeling_llama.LlamaForCausalLM
+class InternLM2ForCausalLM(InternLM2PreTrainedModel):
+    _auto_class = "AutoModelForCausalLM"
+
+    _tied_weights_keys = ["output.weight"]
+
+    def __init__(self, config):
+        super().__init__(config)
+        self.model = InternLM2Model(config)
+        self.vocab_size = config.vocab_size
+        self.output = nn.Linear(config.hidden_size, config.vocab_size, bias=False)
+        self.debug_flag = 1
+        self.mask_flag = 1
+        self.tokenizer = None
+
+        self.max_length = config.max_length
+        print (f'Set max length to {self.max_length}')
+        self.debug_flag = 1
+        # Initialize weights and apply final processing
+        self.post_init()
+        self.plora_glb_GN = nn.Parameter(torch.zeros([1, 1, 4096]))
+        self.plora_sub_GN = nn.Parameter(torch.zeros([1, 1, 1, 4096]))
+
+        self.vit = build_vision_tower()
+        self.vision_proj = build_vision_projector()
+        self.video_mem_proj = build_vision_projector(1536)
+        self.im_size = 490
+        self.vis_processor = transforms.Compose([
+            transforms.ToTensor(),
+            transforms.Normalize((0.48145466, 0.4578275, 0.40821073),
+                                 (0.26862954, 0.26130258, 0.27577711)),
+        ])
+        self.user_p = '[UNUSED_TOKEN_146]user\n'
+        self.bot_p = '[UNUSED_TOKEN_146]assistant\n'
+        self.end_p = '[UNUSED_TOKEN_145]\n'
+
+    def _set_gradient_checkpointing(self, module, value=False):
+        if isinstance(module, InternLM2Model):
+            module.gradient_checkpointing = value
+        if value:
+            self.vit.vision_tower.vision_model.encoder.gradient_checkpointing = value
+
+    def get_input_embeddings(self):
+        return self.model.tok_embeddings
+
+    def set_input_embeddings(self, value):
+        self.model.tok_embeddings = value
+
+    def get_output_embeddings(self):
+        return self.output
+
+    def set_output_embeddings(self, new_embeddings):
+        self.output = new_embeddings
+
+    def set_decoder(self, decoder):
+        self.model = decoder
+
+    def get_decoder(self):
+        return self.model
+
+    def encode_text(self, t, add_special_tokens=False):
+        t = t.replace('<|User|>:', '[UNUSED_TOKEN_146]user\n')
+        t = t.replace('<|Bot|>:', '[UNUSED_TOKEN_146]assistant\n')
+        t = t.replace('<TOKENS_UNUSED_0>', '[UNUSED_TOKEN_145]')
+        t = t.replace('<TOKENS_UNUSED_1>', '[UNUSED_TOKEN_145]')
+        t = t.replace('[UNUSED_TOKEN_0]', '[UNUSED_TOKEN_145]')
+        t = t.replace('[UNUSED_TOKEN_1]', '[UNUSED_TOKEN_145]')
+
+        text = t
+        token = self.tokenizer(text,
+                    return_tensors='pt',
+                    add_special_tokens=add_special_tokens).input_ids.to(self.device)
+        embs = self.model.tok_embeddings(token)
+        return embs
+
+    def encode_img(self, image):
+        if image is None:
+            return None
+        if isinstance(image, str):
+            image = Image.open(image).convert("RGB")
+            image = self.vis_processor(image).unsqueeze(0).to(self.device)
+        else:
+            assert isinstance(image, torch.Tensor)
+
+        img_embeds, _ = self.img2emb([image])
+        return img_embeds
+
+    def img2emb(self, image):
+        img_embeds, img_split = self.vit(image, 
+            self.plora_glb_GN, self.plora_sub_GN)
+        img_embeds = self.vision_proj(img_embeds)
+
+        return img_embeds, img_split
+    
+    def text_reorg(self, text):
+        new_text = []
+        for t in text:
+            t = t.replace('<|User|>:', '[UNUSED_TOKEN_146]user\n')
+            t = t.replace('<|Bot|>:', '[UNUSED_TOKEN_146]assistant\n')
+            t = t.replace('<TOKENS_UNUSED_0>', '[UNUSED_TOKEN_145]')
+            t = t.replace('<TOKENS_UNUSED_1>', '[UNUSED_TOKEN_145]')
+            new_text.append(t)
+        text = new_text
+        return text
+
+    def input_formulate(self, img_embeds, img_split, image_num, texts, temp_max_len=None, use_mask=True):
+        temp_embeds = []
+        temp_im_mask = []
+        temp_tars = []
+
+        for idx, text in enumerate(texts):
+            im_id = int(np.sum(image_num[:idx]))
+            images = []
+            for i in range(image_num[idx]):
+                st = int(np.sum(img_split[:im_id + i]))
+                sp = img_split[im_id + i]
+                temp_img = img_embeds[:, st:st+sp]
+                images.append(temp_img)
+            embeds, im_mask, tars = self.prompt_warp(images, text)
+            if not use_mask:
+                im_mask = im_mask * 0
+            temp_embeds.append(embeds)
+            temp_im_mask.append(im_mask)
+            temp_tars.append(tars)
+        
+        if temp_max_len is None:
+            temp_max_len = np.max([i.shape[1] for i in temp_embeds])
+        self.temp_max_len = temp_max_len
+        final_input = []
+        final_atts = []
+        final_tars = []
+        final_mask = []
+        pad = torch.ones([1, 1]) * self.tokenizer.pad_token_id
+        pad = pad.long().to(embeds.device)
+        pad_emb = self.model.tok_embeddings(pad)
+
+        for idx in range(len(temp_embeds)):
+            temp_len = temp_embeds[idx].shape[1]
+            if temp_len >= temp_max_len:
+                final_input.append(temp_embeds[idx][:, :temp_max_len])
+                final_atts.append(torch.ones(1, temp_max_len).to(tars.dtype).to(embeds.device))
+                final_tars.append(temp_tars[idx][:, :temp_max_len])
+                final_mask.append(temp_im_mask[idx][:, :temp_max_len])
+            else:
+                final_input.append(torch.cat([temp_embeds[idx], pad_emb.repeat(1, temp_max_len-temp_len, 1)], dim=1))
+                final_atts.append(torch.cat([torch.ones(1, temp_len), torch.zeros(1, temp_max_len-temp_len)], dim=1).to(tars.dtype).to(embeds.device))
+                final_tars.append(torch.cat([temp_tars[idx], (torch.ones(1, temp_max_len-temp_len)*-100).to(tars.dtype).to(embeds.device)], dim=1))
+                final_mask.append(torch.cat([temp_im_mask[idx], (torch.zeros(1, temp_max_len-temp_len)).to(tars.dtype).to(embeds.device)], dim=1))
+
+        inputs_embeds = torch.cat(final_input, dim=0)
+        attention_mask = torch.cat(final_atts, dim=0)
+        targets = torch.cat(final_tars, dim=0)
+        im_mask = torch.cat(final_mask, dim=0).bool().view(-1) ### B*N
+    
+        return inputs_embeds, attention_mask, targets, im_mask
+
+
+
+    def prompt_warp(self, images, text):
+        pattern = '\\[UNUSED_TOKEN_146\\]user\\\n|\\[UNUSED_TOKEN_146\\]assistant\\\n|\\[UNUSED_TOKEN_145\\]'
+        sp = [i for i in re.split(pattern, text) if i != '' and i!= '\n']
+        pre_pos = 0
+        temp = []
+        if len(sp) < 2:
+            sp = ['skip this question', 'skip']
+            print (f'SKIP {text}')
+
+        for q, a in zip(sp[::2],sp[1::2]):
+            temp.append(f'[UNUSED_TOKEN_146]user\n{q}[UNUSED_TOKEN_145]\n[UNUSED_TOKEN_146]assistant\n')
+            temp.append(f'{a}[UNUSED_TOKEN_145]\n')
+        text = temp
+        for t in text: 
+            pre_pos += len(t.split('<IM_POS>')) - 1 
+        
+        if pre_pos > 0:
+            assert pre_pos == len(images)
+        else:
+            #text[0] = '<IM_POS>' + text[0]
+            text[0] = text[0].replace('[UNUSED_TOKEN_146]user\n', '[UNUSED_TOKEN_146]user\n<IM_POS>', 1)
+
+        need_bos = True
+        im_idx = 0
+        embeds = []
+        im_mask = []
+        tars = []
+        for q, a in zip(text[::2],text[1::2]):
+            sub_q = q.split('<IM_POS>')
+            add_im = len(sub_q) - 1 
+            for subtext in sub_q:
+                if need_bos or len(subtext) > 0:
+                    text_embeds, text_tars = self.text2emb(subtext, add_special_tokens=need_bos, cal_loss=False)
+                    embeds.append(text_embeds)
+                    im_mask.append(torch.zeros(text_embeds.shape[:2]).cuda())
+                    tars.append(text_tars)
+                    need_bos = False
+
+                if im_idx < len(images) and add_im:
+                    image_embeds = images[im_idx]
+                    im_idx += 1
+                    add_im -= 1
+                    embeds.append(image_embeds)
+                    im_mask.append(torch.ones(image_embeds.shape[:2], dtype=torch.long).cuda())
+                    tars.append(torch.ones(image_embeds.shape[:2], dtype=torch.long).cuda() * -100)
+            
+            text_embeds, text_tars = self.text2emb(a, add_special_tokens=need_bos, cal_loss=True)
+            embeds.append(text_embeds)
+            im_mask.append(torch.zeros(text_embeds.shape[:2]).cuda())
+            tars.append(text_tars)
+        embeds = torch.cat(embeds, dim=1)
+        im_mask = torch.cat(im_mask, dim=1)
+        im_mask = im_mask.bool()
+        tars = torch.cat(tars, dim=1)
+        
+        if self.debug_flag and 0:
+            for tar in tars:
+                targets_vis = tar.clone()
+                targets_vis[targets_vis==-100] = 92399
+                targets_vis_tokens = ''.join(self.tokenizer.convert_ids_to_tokens(targets_vis)).replace('[UNUSED_TOKEN_2]', "__")
+                
+                print([targets_vis_tokens]) 
+        
+        return embeds, im_mask, tars
+
+    def text2emb(self, text, add_special_tokens=False, cal_loss=True):
+        to_regress_tokens = self.tokenizer(
+            text,
+            return_tensors="pt",
+            padding="longest",
+            truncation=True,
+            add_special_tokens=add_special_tokens
+        ).to(self.device)
+
+        targets = copy.deepcopy(to_regress_tokens.input_ids)
+        if not cal_loss:
+            targets[:,:] = -100
+        else:
+            targets[:,-1] = -100
+        targets = targets.to(self.device)
+        to_regress_embeds = self.model.tok_embeddings(to_regress_tokens.input_ids)
+
+        return to_regress_embeds, targets
+
+    @add_start_docstrings_to_model_forward(InternLM2_INPUTS_DOCSTRING)
+    @replace_return_docstrings(output_type=CausalLMOutputWithPast, config_class=_CONFIG_FOR_DOC)
+    def forward(
+        self,
+        input_ids: torch.LongTensor = None,
+        attention_mask: Optional[torch.Tensor] = None,
+        position_ids: Optional[torch.LongTensor] = None,
+        past_key_values: Optional[List[torch.FloatTensor]] = None,
+        inputs_embeds: Optional[torch.FloatTensor] = None,
+        labels: Optional[torch.LongTensor] = None,
+        use_cache: Optional[bool] = None,
+        output_attentions: Optional[bool] = None,
+        output_hidden_states: Optional[bool] = None,
+        return_dict: Optional[bool] = None,
+        **kwargs
+    ) -> Union[Tuple, CausalLMOutputWithPast]:
+        r"""
+        Args:
+            labels (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*):
+                Labels for computing the masked language modeling loss. Indices should either be in `[0, ...,
+                config.vocab_size]` or -100 (see `input_ids` docstring). Tokens with indices set to `-100` are ignored
+                (masked), the loss is only computed for the tokens with labels in `[0, ..., config.vocab_size]`.
+
+        Returns:
+
+        Example:
+
+        ```python
+        >>> from transformers import AutoTokenizer, InternLM2ForCausalLM
+
+        >>> model = InternLM2ForCausalLM.from_pretrained(PATH_TO_CONVERTED_WEIGHTS)
+        >>> tokenizer = AutoTokenizer.from_pretrained(PATH_TO_CONVERTED_TOKENIZER)
+
+        >>> prompt = "Hey, are you conscious? Can you talk to me?"
+        >>> inputs = tokenizer(prompt, return_tensors="pt")
+
+        >>> # Generate
+        >>> generate_ids = model.generate(inputs.input_ids, max_length=30)
+        >>> tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
+        "Hey, are you conscious? Can you talk to me?\nI'm not conscious, but I can talk to you."
+        ```"""
+        samples = kwargs.get('samples', None)
+        if samples:
+            if self.debug_flag:
+                self.debug_flag += 1
+            if self.debug_flag > 3:
+                self.debug_flag = 0
+
+            has_img = 'image' in samples.keys()
+
+            ### encode text
+            sp_token = samples["sp_token"]
+
+            text = samples['text_input'][0].split(sp_token)
+            text = ['<|User|>:' + t for t in text]
+            bs = len(text)
+
+            ### re-org image
+            image = samples["image"][0]
+            image_num = []
+            temp_image = []
+
+            for im in image:
+                if samples['data_type'][0] == 'video_mem':
+                    image_num.append(1)
+                    temp_image.append(im)
+                else:
+                    if type(im) is list:
+                        image_num.append(len(im))
+                        temp_image.extend(im)
+                    else:
+                        image_num.append(1)
+                        temp_image.append(im)
+            image = temp_image
+
+            ### re-org text
+            text = self.text_reorg(text)
+
+            if samples['data_type'][0] != 'nlp':
+                temp_max_txt = int(samples.get('max_length', [2048])[0])
+                assert type(image) is list and len(image_num) == bs
+                if samples['data_type'][0] == 'video_mem':
+                    img_split = []
+                    img_embeds = []
+                    for img in image:
+                        temp_emb = []
+                        if type(img) is list:
+                            if len(img) == 1:
+                                glb = img[0]
+                                lol, im = None, None
+                            elif len(img) == 2:
+                                glb, lol = img
+                                im = None
+                            elif len(img) == 3:
+                                glb, lol, im = img
+                            else:
+                                print('Video part number error', len(img))
+
+                            _, b, n, c = glb.shape
+                            glb = self.video_mem_proj(glb.view(1, -1, c))
+                            glb_text, _ = self.text2emb('This is video overview memory:', add_special_tokens=False, cal_loss=False)
+                            temp_emb.append(glb_text)
+                            temp_emb.append(glb)
+                            
+                            if lol is not None:
+                                _, b, n, c = lol.shape
+                                lol = self.video_mem_proj(lol.view(1, -1, c))
+                                lol_text, _ = self.text2emb('This is question related video memory:', add_special_tokens=False, cal_loss=False)
+                                temp_emb.append(lol_text)
+                                temp_emb.append(lol)
+
+                            if im is not None:
+                                im_embeds, _ = self.img2emb([im])
+                                im_text, _ = self.text2emb('This is question related image:', add_special_tokens=False, cal_loss=False)
+                                temp_emb.append(im_text)
+                                temp_emb.append(im_embeds)
+
+                            temp_emb = torch.cat(temp_emb, dim=1)
+                            img_split.append(temp_emb.shape[1])
+                            img_embeds.append(temp_emb)
+
+                    img_embeds = torch.cat(img_embeds, dim=1)
+                    use_mask = True
+                else:
+                    img_embeds, img_split = self.img2emb(image)
+                    use_mask = True
+                inputs_embeds, attention_mask, targets, im_mask = self.input_formulate(img_embeds, img_split, image_num, text, use_mask=use_mask)
+
+            else:
+                img_embeds, img_split = self.img2emb([torch.zeros(1,3,560,560).to(self.device).to(self.model.dtype)])
+                glb_embeds = self.video_mem_proj(torch.zeros(1,16,1536).to(self.device).to(self.model.dtype))
+                inputs_embeds, attention_mask, targets, im_mask = self.input_formulate([], [], [0] * len(text), text)
+                inputs_embeds += img_embeds.sum() * 0
+                inputs_embeds += glb_embeds.sum() * 0
+
+            temp_bs, temp_len = inputs_embeds.shape[:2]
+            if temp_bs * temp_len > 24000:
+                temp_num = int(np.ceil(24000 / temp_len) - 1)
+                temp_num = max(1, temp_num)
+                temp_max_len = int(24000 // temp_num)
+                inputs_embeds = inputs_embeds[:temp_num, :temp_max_len]
+                attention_mask = attention_mask[:temp_num, :temp_max_len]
+                targets = targets[:temp_num, :temp_max_len]
+                im_mask = im_mask.reshape(temp_bs, temp_len)
+                im_mask = im_mask[:temp_num, :temp_max_len].reshape(-1)
+            else:
+                temp_num = temp_bs
+                temp_max_len = temp_len
+
+            labels = targets
+            if self.debug_flag:
+                print (targets.shape, inputs_embeds.shape, attention_mask.shape, im_mask.shape)
+                le = len(image_num)
+                data_type = samples['data_type'][0]
+                print (f'DataType: {data_type}. BatchSize is {temp_num}/{temp_bs}, Length is {temp_max_len}/{temp_len}')
+                if has_img:
+                    print (img_embeds.shape, img_split, self.temp_max_len)
+
+        else:
+            self.debug_flag = 0
+            im_mask = kwargs.get('im_mask', None)
+            if im_mask is None and inputs_embeds is not None:
+                im_mask = torch.zeros(inputs_embeds.shape[:2]).to(inputs_embeds.device)
+                if self.mask_flag:
+                    print ('Warning! image mask will be 0')
+                    self.mask_flag = 0
+                im_mask = im_mask.bool()
+            im_mask = im_mask.view(-1)
+
+
+        output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions
+        output_hidden_states = (
+            output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
+        )
+        return_dict = return_dict if return_dict is not None else self.config.use_return_dict
+
+        if self.debug_flag:
+            global_rank = dist.get_rank()
+            print (f'{global_rank} HERE1, encoding')
+        # decoder outputs consists of (dec_features, layer_state, dec_hidden, dec_attn)
+        outputs = self.model(
+            input_ids=input_ids,
+            attention_mask=attention_mask,
+            position_ids=position_ids,
+            past_key_values=past_key_values,
+            inputs_embeds=inputs_embeds,
+            use_cache=use_cache,
+            output_attentions=output_attentions,
+            output_hidden_states=output_hidden_states,
+            return_dict=return_dict,
+            im_mask = im_mask,
+        )
+
+        hidden_states = outputs[0]
+        logits = self.output(hidden_states)
+        logits = logits.float()
+
+        if self.debug_flag:
+            global_rank = dist.get_rank()
+            print (f'{global_rank} HERE2')
+        loss = None
+        if labels is not None:
+            # Shift so that tokens < n predict n
+            shift_logits = logits[..., :-1, :].contiguous()
+            shift_labels = labels[..., 1:].contiguous()
+            # Flatten the tokens
+            loss_fct = CrossEntropyLoss(reduce=False)
+            B, N = shift_logits.shape[:2]
+            shift_logits = shift_logits.view(-1, self.config.vocab_size)
+            shift_labels = shift_labels.view(-1)
+            mask = shift_labels >= 0
+            # Enable model parallelism
+            shift_labels = shift_labels.to(shift_logits.device)
+            loss = loss_fct(shift_logits, shift_labels)
+            loss = (loss.view(B,N).sum(dim=1) / mask.view(B,N).sum(dim=1)).mean()
+
+        if self.debug_flag:
+            global_rank = dist.get_rank()
+            print (f'{global_rank} HERE3')
+
+
+        if not return_dict:
+            output = (logits,) + outputs[1:]
+            return (loss,) + output if loss is not None else output
+
+        return CausalLMOutputWithPast(
+            loss=loss,
+            logits=logits,
+            past_key_values=outputs.past_key_values,
+            hidden_states=outputs.hidden_states,
+            attentions=outputs.attentions,
+        )
+
+    def prepare_inputs_for_generation(
+        self, input_ids, past_key_values=None, attention_mask=None, inputs_embeds=None, im_mask=None, **kwargs
+    ):
+        if past_key_values is not None:
+            past_length = past_key_values[0][0].shape[2]
+
+            # Some generation methods already pass only the last input ID
+            if input_ids.shape[1] > past_length:
+                remove_prefix_length = past_length
+            else:
+                # Default to old behavior: keep only final ID
+                remove_prefix_length = input_ids.shape[1] - 1
+
+            input_ids = input_ids[:, remove_prefix_length:]
+
+        position_ids = kwargs.get("position_ids", None)
+        if attention_mask is not None and position_ids is None:
+            # create position_ids on the fly for batch generation
+            position_ids = attention_mask.long().cumsum(-1) - 1
+            position_ids.masked_fill_(attention_mask == 0, 1)
+            if past_key_values:
+                position_ids = position_ids[:, -input_ids.shape[1] :]
+
+        # if `inputs_embeds` are passed, we only want to use them in the 1st generation step
+        if inputs_embeds is not None and past_key_values is None:
+            model_inputs = {"inputs_embeds": inputs_embeds}
+        else:
+            model_inputs = {"input_ids": input_ids}
+
+        im_mask = im_mask
+
+        model_inputs.update(
+            {
+                "position_ids": position_ids,
+                "past_key_values": past_key_values,
+                "use_cache": kwargs.get("use_cache"),
+                "attention_mask": attention_mask,
+                "im_mask": im_mask,
+            }
+        )
+        return model_inputs
+
+    @staticmethod
+    def _reorder_cache(past_key_values, beam_idx):
+        reordered_past = ()
+        for layer_past in past_key_values:
+            reordered_past += (
+                tuple(past_state.index_select(0, beam_idx.to(past_state.device)) for past_state in layer_past),
+            )
+        return reordered_past
+
+    def build_inputs(self, tokenizer, query: str, history: List[Tuple[str, str]] = [], meta_instruction=""):
+        if tokenizer.add_bos_token:
+            prompt = ""
+        else:
+            prompt = tokenizer.bos_token
+        if meta_instruction:
+            prompt += f"""<|im_start|>system\n{meta_instruction}<|im_end|>\n"""
+        for record in history:
+            prompt += f"""<|im_start|>user\n{record[0]}<|im_end|>\n<|im_start|>assistant\n{record[1]}<|im_end|>\n"""
+        prompt += f"""<|im_start|>user\n{query}<|im_end|>\n<|im_start|>assistant\n"""
+        return tokenizer([prompt], return_tensors="pt")
+
+    @torch.no_grad()
+    def chat(
+        self,
+        tokenizer,
+        query: str,
+        history: List[Tuple[str, str]] = [],
+        streamer: Optional[BaseStreamer] = None,
+        max_new_tokens: int = 1024,
+        do_sample: bool = True,
+        temperature: float = 0.8,
+        top_p: float = 0.8,
+        meta_instruction: str = "You are an AI assistant whose name is InternLM (书生·浦语).\n"
+        "- InternLM (书生·浦语) is a conversational language model that is developed by Shanghai AI Laboratory (上海人工智能实验室). It is designed to be helpful, honest, and harmless.\n"
+        "- InternLM (书生·浦语) can understand and communicate fluently in the language chosen by the user such as English and 中文.",
+        **kwargs,
+    ):
+        inputs = self.build_inputs(tokenizer, query, history, meta_instruction)
+        inputs = {k: v.to(self.device) for k, v in inputs.items() if torch.is_tensor(v)}
+        # also add end-of-assistant token in eos token id to avoid unnecessary generation
+        eos_token_id = [tokenizer.eos_token_id, tokenizer.convert_tokens_to_ids(["<|im_end|>"])[0]]
+        outputs = self.generate(
+            **inputs,
+            streamer=streamer,
+            max_new_tokens=max_new_tokens,
+            do_sample=do_sample,
+            temperature=temperature,
+            top_p=top_p,
+            eos_token_id=eos_token_id,
+            **kwargs,
+        )
+        outputs = outputs[0].cpu().tolist()[len(inputs["input_ids"][0]) :]
+        response = tokenizer.decode(outputs, skip_special_tokens=True)
+        response = response.split("<|im_end|>")[0]
+        history = history + [(query, response)]
+        return response, history
+
+    @torch.no_grad()
+    def stream_chat(
+        self,
+        tokenizer,
+        query: str,
+        history: List[Tuple[str, str]] = [],
+        max_new_tokens: int = 1024,
+        do_sample: bool = True,
+        temperature: float = 0.8,
+        top_p: float = 0.8,
+        **kwargs,
+    ):
+        """
+        Return a generator in format: (response, history)
+        Eg.
+        ('你好，有什么可以帮助您的吗', [('你好', '你好，有什么可以帮助您的吗')])
+        ('你好，有什么可以帮助您的吗？', [('你好', '你好，有什么可以帮助您的吗？')])
+        """
+        if BaseStreamer is None:
+            raise ModuleNotFoundError(
+                "The version of `transformers` is too low. Please make sure "
+                "that you have installed `transformers>=4.28.0`."
+            )
+
+        response_queue = queue.Queue(maxsize=20)
+
+        class ChatStreamer(BaseStreamer):
+            def __init__(self, tokenizer) -> None:
+                super().__init__()
+                self.tokenizer = tokenizer
+                self.queue = response_queue
+                self.query = query
+                self.history = history
+                self.response = ""
+                self.cache = []
+                self.received_inputs = False
+                self.queue.put((self.response, history + [(self.query, self.response)]))
+
+            def put(self, value):
+                if len(value.shape) > 1 and value.shape[0] > 1:
+                    raise ValueError("ChatStreamer only supports batch size 1")
+                elif len(value.shape) > 1:
+                    value = value[0]
+
+                if not self.received_inputs:
+                    # The first received value is input_ids, ignore here
+                    self.received_inputs = True
+                    return
+
+                self.cache.extend(value.tolist())
+                token = self.tokenizer.decode(self.cache, skip_special_tokens=True)
+                if token.strip() != "<|im_end|>":
+                    self.response = self.response + token
+                    history = self.history + [(self.query, self.response)]
+                    self.queue.put((self.response, history))
+                    self.cache = []
+                else:
+                    self.end()
+
+            def end(self):
+                self.queue.put(None)
+
+        def stream_producer():
+            return self.chat(
+                tokenizer=tokenizer,
+                query=query,
+                streamer=ChatStreamer(tokenizer=tokenizer),
+                history=history,
+                max_new_tokens=max_new_tokens,
+                do_sample=do_sample,
+                temperature=temperature,
+                top_p=top_p,
+                **kwargs,
+            )
+
+        def consumer():
+            producer = threading.Thread(target=stream_producer)
+            producer.start()
+            while True:
+                res = response_queue.get()
+                if res is None:
+                    return
+                yield res
+
+        return consumer()
+
+
diff --git a/base/modeling_internlm_xcomposer2.py b/base/modeling_internlm_xcomposer2.py
new file mode 100644
index 0000000000000000000000000000000000000000..6bba1c96d828edd4ff9ee873c470a8ca6bfc7857
--- /dev/null
+++ b/base/modeling_internlm_xcomposer2.py
@@ -0,0 +1,906 @@
+# Copyright (c) The InternLM team and The HuggingFace Inc. team. All rights reserved.
+#
+# This code is based on transformers/src/transformers/models/llama/modeling_llama.py
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""PyTorch InternLMXComposer2 model."""
+import os
+import re
+import copy
+import queue
+import threading
+from typing import List, Optional, Tuple, Union
+
+import torch
+import torch.utils.checkpoint
+from PIL import Image
+import numpy as np
+import random
+from torch import nn
+from torch.nn import CrossEntropyLoss
+from torchvision import transforms
+from torchvision.transforms.functional import InterpolationMode
+from transformers.modeling_outputs import CausalLMOutputWithPast
+from transformers.utils import (add_start_docstrings_to_model_forward,
+                                replace_return_docstrings)
+from transformers import StoppingCriteria, StoppingCriteriaList
+from transformers import AutoModelForCausalLM, AutoTokenizer, set_seed
+try:
+    from transformers.generation.streamers import BaseStreamer
+except:  # noqa # pylint: disable=bare-except
+    BaseStreamer = None
+
+import torchvision.transforms as transforms
+from torchvision.transforms.functional import InterpolationMode
+
+from .build_mlp import build_vision_projector, build_vision_tower
+from .ixc_utils import Image_transform, Video_transform, load_video, frame2img, get_font
+from .configuration_internlm_xcomposer2 import InternLMXcomposer2Config
+from .modeling_internlm2 import (InternLM2_INPUTS_DOCSTRING, InternLM2Model,
+                                 InternLM2PreTrainedModel)
+
+_CONFIG_FOR_DOC = 'InternLMXcomposer2Config'
+
+image_extensions = {'.jpg', '.jpeg', '.png', '.gif', '.bmp', '.webp'}
+video_extensions = {'.mp4', '.avi', '.mkv', '.mov', '.wmv'}
+
+class StoppingCriteriaSub(StoppingCriteria):
+
+    def __init__(self, stops=[], encounters=1):
+        super().__init__()
+        self.stops = stops
+
+    def __call__(self, input_ids: torch.LongTensor, scores: torch.FloatTensor):
+        for stop in self.stops:
+            if torch.all((stop == input_ids[0][-len(stop):])).item():
+                return True
+        return False
+
+
+def get_stopping_criteria(stop_words_ids):
+    stop_words_ids = [torch.tensor([i]).cuda() for i in stop_words_ids]
+    stopping_criteria = StoppingCriteriaList(
+        [StoppingCriteriaSub(stops=stop_words_ids)])
+    return stopping_criteria
+
+def set_random_seed(seed, set_cudnn=False):
+    """Set the random seed for reproducibility.
+
+    Parameters:
+    seed (int): The seed to use for generating random numbers.
+    """
+    torch.manual_seed(seed)
+    if torch.cuda.is_available():
+        torch.cuda.manual_seed_all(seed)  # For multi-GPU.
+    np.random.seed(seed)
+    random.seed(seed)
+    if set_cudnn and torch.backends.cudnn.is_available():
+        torch.backends.cudnn.deterministic = True
+        torch.backends.cudnn.benchmark = False
+
+class InternLMXComposer2ForCausalLM(InternLM2PreTrainedModel):
+    _auto_class = 'AutoModelForCausalLM'
+
+    _tied_weights_keys = ['output.weight']
+
+    def __init__(self, config):
+        super().__init__(config)
+        self.model = InternLM2Model(config)
+        self.vocab_size = config.vocab_size
+        self.output = nn.Linear(
+            config.hidden_size, config.vocab_size, bias=False)
+        self.tokenizer = None
+        self.hd_num = 25
+        self.font = get_font()
+
+        self.max_length = config.max_length
+        print(f'Set max length to {self.max_length}')
+        # Initialize weights and apply final processing
+        self.post_init()
+        self.plora_glb_GN = nn.Parameter(torch.zeros([1, 1, 4096]))
+        self.plora_sub_GN = nn.Parameter(torch.zeros([1, 1, 1, 4096]))
+
+        self.vit = build_vision_tower()
+        self.vision_proj = build_vision_projector()
+        self.video_mem_proj = build_vision_projector(1536)
+        self.im_size = 490
+
+        self.vis_processor = transforms.Compose([
+            transforms.ToTensor(),
+            transforms.Normalize((0.48145466, 0.4578275, 0.40821073),
+                                 (0.26862954, 0.26130258, 0.27577711)),
+        ])
+
+
+    
+
+    def _set_gradient_checkpointing(self, module, value=False):
+        if isinstance(module, InternLM2Model):
+            module.gradient_checkpointing = value
+        if value:
+            self.vit.vision_tower.vision_model.encoder.gradient_checkpointing = value
+
+    def get_input_embeddings(self):
+        return self.model.tok_embeddings
+
+    def set_input_embeddings(self, value):
+        self.model.tok_embeddings = value
+
+    def get_output_embeddings(self):
+        return self.output
+
+    def set_output_embeddings(self, new_embeddings):
+        self.output = new_embeddings
+
+    def set_decoder(self, decoder):
+        self.model = decoder
+
+    def get_decoder(self):
+        return self.model
+
+    def encode_text(self, text, add_special_tokens=False):
+        token = self.tokenizer(
+            text, return_tensors='pt',
+            add_special_tokens=add_special_tokens).input_ids.to(self.device)
+        embs = self.model.tok_embeddings(token)
+        return embs
+
+    def encode_img(self, image, hd_num=25):
+        if image is None:
+            return None
+        if isinstance(image, str):
+            _, ext = os.path.splitext(image)
+            if ext.lower() in image_extensions:
+                image = Image.open(image)
+                image = Image_transform(image, hd_num = hd_num)
+            elif ext.lower() in video_extensions:
+                image = load_video(image)
+                image = frame2img(image, self.font)
+                image = Video_transform(image, hd_num = hd_num)
+            else:
+                print ('Unknow input format', image)
+                return None
+            image = self.vis_processor(image).unsqueeze(0).to(self.device)
+        else:
+            assert isinstance(image, torch.Tensor)
+
+        img_embeds, atts_img, img_target = self.img2emb(image)
+        return img_embeds
+
+    def img2emb(self, image):
+        img_embeds, img_split = self.vit([image], 
+            self.plora_glb_GN, self.plora_sub_GN)
+        if len(img_split) > 1:
+            print ('Batch Size >1 is not supported.')
+            assert 0
+        #print (img_embeds.shape)
+        img_embeds = self.vision_proj(img_embeds)
+        atts_img = torch.ones(
+            img_embeds.size()[:-1], dtype=torch.long).to(img_embeds.device)
+
+        img_target = torch.ones(
+            img_embeds.size()[:2], dtype=torch.long).to(
+                img_embeds.device) * -100
+
+        return img_embeds, atts_img, img_target
+
+    def prompt_wrap(self, img_embeds, prompt):
+        batch_size = img_embeds.shape[0]
+        p_before, p_after = prompt.split('<ImageHere>')
+        p_before_tokens = self.tokenizer(
+            p_before, return_tensors='pt',
+            add_special_tokens=True).to(img_embeds.device)
+
+        p_before_embeds = self.model.tok_embeddings(
+            p_before_tokens.input_ids).expand(batch_size, -1, -1)
+        wrapped_img_embeds = torch.cat([p_before_embeds, img_embeds], dim=1)
+
+        wrapped_atts_img = torch.ones(
+            wrapped_img_embeds.size()[:-1],
+            dtype=torch.long).to(img_embeds.device)
+
+        wrapped_target = torch.ones(
+            batch_size, wrapped_img_embeds.shape[1], dtype=torch.long).to(
+                img_embeds.device) * -100
+
+        return wrapped_img_embeds, wrapped_atts_img, wrapped_target
+
+    def text2emb(self, text, add_special_tokens=False):
+        to_regress_tokens = self.tokenizer(
+            text,
+            return_tensors='pt',
+            padding='longest',
+            truncation=True,
+            max_length=self.max_length,
+            add_special_tokens=add_special_tokens
+        ).to(self.device)
+
+        targets = self.mask_human_targets(to_regress_tokens.input_ids)
+        targets = targets.to(self.device)
+        return to_regress_tokens, targets
+
+    def interleav_wrap_chat(self, query, image, history = [], meta_instruction='', max_length=16384, hd_num=24):
+        self.max_length = max_length
+        prompt = ''
+        if meta_instruction:
+            prompt += f"""[UNUSED_TOKEN_146]system\n{meta_instruction}[UNUSED_TOKEN_145]\n"""
+        for record in history:
+            prompt += f"""[UNUSED_TOKEN_146]user\n{record[0]}[UNUSED_TOKEN_145]\n[UNUSED_TOKEN_146]assistant\n{record[1]}[UNUSED_TOKEN_145]\n"""
+        prompt += f"""[UNUSED_TOKEN_146]user\n{query}[UNUSED_TOKEN_145]\n[UNUSED_TOKEN_146]assistant\n"""
+
+        image_nums = len(image)
+        if image_nums == 1 and prompt.find('<ImageHere>') == -1:
+            #print ('auto append image at the begining')
+            prompt = '<ImageHere>' + prompt
+
+        parts = prompt.split('<ImageHere>')
+        wrap_embeds, wrap_im_mask = [], []
+        temp_len = 0
+        need_bos = True
+
+        if len(parts) != image_nums + 1:
+            #raise ValueError('Invalid <ImageHere> prompt format.')
+            print ('Waring! The image number != given position!')
+        if image_nums > 1:
+            hd_num = 6
+        else:
+            hu_num = hd_num
+        for idx, part in enumerate(parts):
+            if need_bos or len(part) > 0:
+                part_tokens = self.tokenizer(
+                    part,
+                    return_tensors='pt',
+                    padding='longest',
+                    add_special_tokens=need_bos).to(self.device)
+                if need_bos:
+                    need_bos = False
+
+                part_embeds = self.model.tok_embeddings(
+                    part_tokens.input_ids)
+                wrap_embeds.append(part_embeds)
+                wrap_im_mask.append(torch.zeros(part_embeds.shape[:2]))
+                temp_len += part_embeds.shape[1]
+            if idx < image_nums:
+                img = self.encode_img(image[idx], hd_num)
+                wrap_embeds.append(img)
+                wrap_im_mask.append(torch.ones(img.shape[:2]))
+                temp_len += img.shape[1]
+    
+            if temp_len > self.max_length:
+                break
+    
+        wrap_embeds = torch.cat(wrap_embeds, dim=1)
+        wrap_im_mask = torch.cat(wrap_im_mask, dim=1)
+        wrap_embeds = wrap_embeds[:, :self.max_length].to(self.device)
+        wrap_im_mask = wrap_im_mask[:, :self.max_length].to(self.device).bool()
+        inputs = {
+            'inputs_embeds': wrap_embeds
+        }
+        return inputs, wrap_im_mask, temp_len
+
+    def interleav_wrap(self, img_list, text_list, image_nums):
+        temp_embeds = []
+        temp_im_mask = []
+        temp_tars = []
+
+        # encode_image
+        img_embeds, img_split = self.vit(img_list, self.plora_glb_GN, self.plora_sub_GN)
+        img_embeds = self.vision_proj(img_embeds)
+
+        text_list = text_list[0]
+        for idx, text in enumerate(text_list):
+            image_num = image_nums[idx]
+            im_id = int(np.sum(image_nums[:idx]))
+            images = []
+            for i in range(image_nums[idx]):
+                st = int(np.sum(img_split[:im_id + i]))
+                sp = img_split[im_id + i]
+                temp_img = img_embeds[:, st:st+sp]
+                images.append(temp_img)
+            atts_img = torch.ones((len(images), images[0].shape[1]), dtype=torch.long).to(self.device)
+            img_target = torch.ones(
+                (len(images), images[0].shape[1]), dtype=torch.long).to(
+                    self.device) * -100
+
+            if image_num == 1 and text.find('<ImageHere>') == -1:
+                text = '<ImageHere>' + text
+            parts = text.split('<ImageHere>')
+
+            wrap_tokens, wrap_embeds, wrap_im_mask = [], [], []
+            temp_len = 0
+            need_bos = True
+            for idx, part in enumerate(parts):
+                if len(part) > 0:
+                    part_tokens = self.tokenizer(part, return_tensors='pt', padding='longest',
+                                                 add_special_tokens=need_bos).to(self.device)
+                    if need_bos:
+                        need_bos = False
+                    wrap_tokens.append(part_tokens.input_ids)
+                    part_embeds = self.model.tok_embeddings(part_tokens.input_ids)
+                    wrap_embeds.append(part_embeds)
+                    wrap_im_mask.append(torch.zeros(part_embeds.shape[:2]).to(self.device))
+                    temp_len += part_embeds.shape[1]
+                if idx < image_num:
+                    wrap_embeds.append(images[idx])
+                    wrap_token = torch.ones(images[idx].shape[:2], dtype=torch.long).to(self.device) * -100
+                    wrap_tokens.append(wrap_token)
+                    wrap_im_mask.append(torch.ones(images[idx].shape[:2]).to(self.device))
+                    temp_len += images[idx].shape[1]
+                if temp_len > self.max_length:
+                    break
+            wrap_tokens = torch.cat(wrap_tokens, dim=1)
+            wrap_embeds = torch.cat(wrap_embeds, dim=1)
+            wrap_im_mask = torch.cat(wrap_im_mask, dim=1)
+
+            wrap_target = self.mask_human_targets(wrap_tokens).to(self.device)
+
+            temp_embeds.append(wrap_embeds)
+            temp_im_mask.append(wrap_im_mask)
+            temp_tars.append(wrap_target)
+
+        temp_max_len = np.max([i.shape[1] for i in temp_embeds])
+        temp_max_len = min(temp_max_len, self.max_length)
+
+        final_input, final_atts, final_tars, final_mask = [], [], [], []
+        pad = torch.ones([1, 1]) * self.tokenizer.pad_token_id
+        pad = pad.long().to(self.device)
+        pad_emb = self.model.tok_embeddings(pad)
+
+        for idx in range(len(temp_embeds)):
+            temp_len = temp_embeds[idx].shape[1]
+            if temp_len >= temp_max_len:
+                final_input.append(temp_embeds[idx][:, :temp_max_len])
+                final_atts.append(torch.ones(1, temp_max_len).to(wrap_target.dtype).to(self.device))
+                final_tars.append(temp_tars[idx][:, :temp_max_len])
+                final_mask.append(temp_im_mask[idx][:, :temp_max_len])
+            else:
+                final_input.append(torch.cat([temp_embeds[idx], pad_emb.repeat(1, temp_max_len-temp_len, 1)], dim=1))
+                final_atts.append(torch.cat([torch.ones(1, temp_len), torch.zeros(1, temp_max_len-temp_len)], dim=1).to(wrap_target.dtype).to(self.device))
+                final_tars.append(torch.cat([temp_tars[idx], (torch.ones(1, temp_max_len-temp_len)*-100).to(wrap_target.dtype).to(self.device)], dim=1))
+                final_mask.append(torch.cat([temp_im_mask[idx], (torch.zeros(1, temp_max_len-temp_len)).to(wrap_target.dtype).to(self.device)], dim=1))
+
+        inputs_embeds = torch.cat(final_input, dim=0)
+        attention_mask = torch.cat(final_atts, dim=0)
+        targets = torch.cat(final_tars, dim=0)
+        im_mask = torch.cat(final_mask, dim=0)
+
+        return inputs_embeds, attention_mask, targets, im_mask
+
+    def mask_human_targets(self, input_ids, pure=False):
+        target_batch = []
+        for bs in range(input_ids.shape[0]):
+            ids = input_ids[bs]
+            targets = copy.deepcopy(ids)
+            end_count = 0
+            last_eoa = 0
+            for i, temp_id in enumerate(ids):
+                if temp_id == 92542:
+                    if end_count % 2 == 0:
+                        targets[last_eoa:i + 6] = -100
+                    else:
+                        last_eoa = i + 1
+                    end_count += 1
+                # # eos and following pad
+                elif temp_id == 2:
+                    # loss on eos, but not on pad
+                    targets[i + 1:] = -100
+                    break
+            # trunction, end at last question
+            if temp_id != 2 and end_count % 2 == 0:
+                # mask all after the last answer
+                targets[last_eoa + 1:] = -100
+            target_batch.append(targets.unsqueeze(0))
+        target_batch = torch.cat(target_batch, dim=0)
+        return target_batch
+
+    @add_start_docstrings_to_model_forward(InternLM2_INPUTS_DOCSTRING)
+    @replace_return_docstrings(
+        output_type=CausalLMOutputWithPast, config_class=_CONFIG_FOR_DOC)
+    def forward(self,
+                input_ids: torch.LongTensor = None,
+                attention_mask: Optional[torch.Tensor] = None,
+                position_ids: Optional[torch.LongTensor] = None,
+                past_key_values: Optional[List[torch.FloatTensor]] = None,
+                inputs_embeds: Optional[torch.FloatTensor] = None,
+                labels: Optional[torch.LongTensor] = None,
+                use_cache: Optional[bool] = None,
+                output_attentions: Optional[bool] = None,
+                output_hidden_states: Optional[bool] = None,
+                return_dict: Optional[bool] = None,
+                **kwargs) -> Union[Tuple, CausalLMOutputWithPast]:
+        r"""
+        Args:
+            labels (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*):
+                Labels for computing the masked language modeling loss. Indices should either be in `[0, ...,
+                config.vocab_size]` or -100 (see `input_ids` docstring). Tokens with indices set to `-100` are ignored
+                (masked), the loss is only computed for the tokens with labels in `[0, ..., config.vocab_size]`.
+        Returns:
+        """
+
+        samples = kwargs.get('samples', None)
+        if samples:
+            infer_mode = samples.get('infer_mode', 'base')
+            if samples['data_type'][0] == 'text':
+                has_img = False
+            elif samples['data_type'][0] == 'multi':
+                has_img = True
+            else:
+                raise NotImplementedError
+
+            # encode text
+            text = samples['text_input']
+            # encode image
+            if has_img:
+                image = samples['image'][0]
+                bs = len(samples['text_input'][0])
+                image_nums = []
+                temp_image = []
+                for im in image:
+                    if type(im) is list:
+                        image_nums.append(len(im))
+                        temp_image.extend(im)
+                    else:
+                        image_nums.append(1)
+                        temp_image.append(im)
+                image = temp_image
+                assert type(image) is list and len(image_nums) == bs
+
+                to_regress_embeds, attention_mask, targets, im_mask = self.interleav_wrap(
+                    image, text, image_nums)
+            else:
+                to_regress_tokens, targets = self.text2emb(
+                    text, add_special_tokens=True)
+                to_regress_embeds = self.model.tok_embeddings(
+                    to_regress_tokens.input_ids)
+                attention_mask = to_regress_tokens.attention_mask
+                im_mask = torch.zeros(to_regress_embeds.shape[:2]).cuda()
+
+            inputs_embeds = to_regress_embeds[:, :self.max_length]
+            attention_mask = attention_mask[:, :self.max_length]
+            targets = targets[:, :self.max_length]
+            im_mask = im_mask[:, :self.max_length].bool()
+            labels = targets
+        else:
+            im_mask = kwargs.get('im_mask', None)
+            infer_mode = kwargs.get('infer_mode', 'base')
+            if im_mask is None and inputs_embeds is not None:
+                im_mask = torch.zeros(inputs_embeds.shape[:2]).to(
+                    inputs_embeds.device)
+                im_mask = im_mask.bool()
+
+        output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions
+        output_hidden_states = (
+            output_hidden_states if output_hidden_states is not None else
+            self.config.output_hidden_states)
+        return_dict = return_dict if return_dict is not None else self.config.use_return_dict
+
+        # decoder outputs consists of (dec_features, layer_state, dec_hidden, dec_attn)
+        outputs = self.model(
+            input_ids=input_ids,
+            attention_mask=attention_mask,
+            position_ids=position_ids,
+            past_key_values=past_key_values,
+            inputs_embeds=inputs_embeds,
+            use_cache=use_cache,
+            output_attentions=output_attentions,
+            output_hidden_states=output_hidden_states,
+            return_dict=return_dict,
+            im_mask=im_mask,
+            infer_mode=infer_mode,
+        )
+
+        hidden_states = outputs[0]
+        logits = self.output(hidden_states)
+        logits = logits.float()
+
+        loss = None
+        if labels is not None:
+            # Shift so that tokens < n predict n
+            shift_logits = logits[..., :-1, :].contiguous()
+            shift_labels = labels[..., 1:].contiguous()
+            # Flatten the tokens
+            loss_fct = CrossEntropyLoss()
+            shift_logits = shift_logits.view(-1, self.config.vocab_size)
+            shift_labels = shift_labels.view(-1)
+            # Enable model parallelism
+            shift_labels = shift_labels.to(shift_logits.device)
+            loss = loss_fct(shift_logits, shift_labels)
+
+        if not return_dict:
+            output = (logits, ) + outputs[1:]
+            return (loss, ) + output if loss is not None else output
+
+        return CausalLMOutputWithPast(
+            loss=loss,
+            logits=logits,
+            past_key_values=outputs.past_key_values,
+            hidden_states=outputs.hidden_states,
+            attentions=outputs.attentions,
+        )
+
+    def prepare_inputs_for_generation(self,
+                                      input_ids,
+                                      past_key_values=None,
+                                      attention_mask=None,
+                                      inputs_embeds=None,
+                                      im_mask=None,
+                                      infer_mode='base',
+                                      **kwargs):
+        if past_key_values is not None:
+            past_length = past_key_values[0][0].shape[2]
+
+            # Some generation methods already pass only the last input ID
+            if input_ids.shape[1] > past_length:
+                remove_prefix_length = past_length
+            else:
+                # Default to old behavior: keep only final ID
+                remove_prefix_length = input_ids.shape[1] - 1
+
+            input_ids = input_ids[:, remove_prefix_length:]
+
+        position_ids = kwargs.get('position_ids', None)
+        if attention_mask is not None and position_ids is None:
+            # create position_ids on the fly for batch generation
+            position_ids = attention_mask.long().cumsum(-1) - 1
+            position_ids.masked_fill_(attention_mask == 0, 1)
+            if past_key_values:
+                position_ids = position_ids[:, -input_ids.shape[1]:]
+
+        # if `inputs_embeds` are passed, we only want to use them in the 1st generation step
+        if inputs_embeds is not None and past_key_values is None:
+            model_inputs = {'inputs_embeds': inputs_embeds}
+        else:
+            model_inputs = {'input_ids': input_ids}
+
+        im_mask = im_mask
+
+        model_inputs.update({
+            'position_ids': position_ids,
+            'past_key_values': past_key_values,
+            'use_cache': kwargs.get('use_cache'),
+            'attention_mask': attention_mask,
+            'im_mask': im_mask,
+            'infer_mode': infer_mode, 
+        })
+        return model_inputs
+
+    @staticmethod
+    def _reorder_cache(past_key_values, beam_idx):
+        reordered_past = ()
+        for layer_past in past_key_values:
+            reordered_past += (tuple(
+                past_state.index_select(0, beam_idx.to(past_state.device))
+                for past_state in layer_past), )
+        return reordered_past
+
+    def build_inputs(self,
+                     tokenizer,
+                     query: str,
+                     history: List[Tuple[str, str]] = [],
+                     meta_instruction=''):
+        prompt = ''
+        if meta_instruction:
+            prompt += f"""<s>[UNUSED_TOKEN_146]system\n{meta_instruction}[UNUSED_TOKEN_145]\n"""
+        else:
+            prompt += '<s>'
+        for record in history:
+            prompt += f"""[UNUSED_TOKEN_146]user\n{record[0]}[UNUSED_TOKEN_145]\n[UNUSED_TOKEN_146]assistant\n{record[1]}[UNUSED_TOKEN_145]\n"""
+        prompt += f"""[UNUSED_TOKEN_146]user\n{query}[UNUSED_TOKEN_145]\n[UNUSED_TOKEN_146]assistant\n"""
+        return tokenizer([prompt], return_tensors='pt')
+
+    @torch.no_grad()
+    def chat(
+        self,
+        tokenizer,
+        query: str,
+        image: List[Tuple[str, str]] = [],
+        hd_num: int = 24,
+        history: List[Tuple[str, str]] = [],
+        streamer: Optional[BaseStreamer] = None,
+        max_new_tokens: int = 1024,
+        do_sample: bool = True,
+        num_beams: int = 1,
+        temperature: float = 1.0,
+        top_p: float = 0.8,
+        repetition_penalty: float=1.005,
+        infer_mode: str = 'base',
+        use_meta: bool = False,
+        meta_instruction:
+        str = 'You are an AI assistant whose name is InternLM-XComposer (浦语·灵笔).\n'
+        '- InternLM-XComposer (浦语·灵笔) is a multi-modality conversational language model that is developed by Shanghai AI Laboratory (上海人工智能实验室). It is designed to be helpful, honest, and harmless.\n'
+        '- InternLM-XComposer (浦语·灵笔) can understand and communicate fluently in the language chosen by the user such as English and 中文.\n'
+        '- InternLM-XComposer (浦语·灵笔) is capable of comprehending and articulating responses effectively based on the provided image.',
+        **kwargs,
+    ):
+
+        if not use_meta:
+            meta_instruction = ''
+        if image is None:
+            inputs = self.build_inputs(tokenizer, query, history, meta_instruction)
+            im_mask = torch.zeros(inputs['input_ids'].shape[:2]).cuda().bool()
+        else:
+            inputs, im_mask, _ = self.interleav_wrap_chat(query, image, history=history, meta_instruction=meta_instruction, hd_num=hd_num)
+        inputs = {
+            k: v.to(self.device)
+            for k, v in inputs.items() if torch.is_tensor(v)
+        }
+        # also add end-of-assistant token in eos token id to avoid unnecessary generation
+        eos_token_id = [
+            tokenizer.eos_token_id,
+            tokenizer.convert_tokens_to_ids(['[UNUSED_TOKEN_145]'])[0]
+        ]
+        outputs = self.generate(
+            **inputs,
+            streamer=streamer,
+            max_new_tokens=max_new_tokens,
+            num_beams=num_beams,
+            do_sample=do_sample,
+            temperature=temperature,
+            top_p=top_p,
+            eos_token_id=eos_token_id,
+            repetition_penalty=repetition_penalty,
+            im_mask=im_mask,
+            infer_mode=infer_mode,
+            **kwargs,
+        )
+        if image is None:
+            outputs = outputs[0].cpu().tolist()[len(inputs['input_ids'][0]):]
+        else:
+            outputs = outputs[0].cpu().tolist()
+        response = tokenizer.decode(outputs, skip_special_tokens=True)
+        response = response.split('[UNUSED_TOKEN_145]')[0]
+        history = history + [(query, response)]
+        return response, history
+
+    @torch.no_grad()
+    def write_artical(
+        self,
+        inst: str,
+        image: List[Tuple[str, str]] = [],
+        hd_num: int = 25,
+        history: List[Tuple[str, str]] = [],
+        streamer: Optional[BaseStreamer] = None,
+        max_new_tokens: int = 1024,
+        do_sample: bool = True,
+        num_beams: int = 1,
+        temperature: float = 1.0,
+        top_p: float = 0.8,
+        repetition_penalty: float=1.005,
+        max_length: int=8192,
+        seed: int = -1,
+        use_meta: bool = False,
+        **kwargs,
+    ):
+        meta_instruction = """You are an AI assistant whose name is InternLM-XComposer (浦语·灵笔).
+- InternLM-XComposer (浦语·灵笔) is a conversational language model that is developed by Shanghai AI Laboratory (上海人工智能实验室). It is designed to be helpful, honest, and harmless.
+- InternLM-XComposer (浦语·灵笔) can understand and communicate fluently in the language chosen by the user such as English and 中文.
+"""
+        if seed != -1:
+            set_seed(seed)
+        if len(history):
+            print ('Only chat function support multi round now, history will be ignored in the artical mode')
+        stop_words_ids = [92542]
+        stopping_criteria = get_stopping_criteria(stop_words_ids)
+
+        if not use_meta:
+            meta_instruction = ''
+        with torch.no_grad():
+            inputs, im_mask, len_input_tokens = self.interleav_wrap_chat(inst, image, meta_instruction=meta_instruction, max_length=max_length)
+        with torch.autocast(device_type='cuda', dtype=torch.float16):
+            with torch.no_grad():
+                generate = self.generate(inputs_embeds=inputs['inputs_embeds'],
+                                          do_sample=do_sample,
+                                          num_beams=num_beams,
+                                          temperature=temperature,
+                                          repetition_penalty=repetition_penalty,
+                                          stopping_criteria=stopping_criteria,
+                                          max_new_tokens=max_length - len_input_tokens,
+                                          top_p=0.8,
+                                          top_k=40,
+                                          length_penalty=1.0,
+                                          im_mask=im_mask,
+                                          infer_mode='write'
+                                         )
+
+        response = generate[0].tolist()
+        response = self.tokenizer.decode(response, skip_special_tokens=True)
+        # remove eoa
+        response = response.replace('[UNUSED_TOKEN_145]', '')
+        response = response.replace('[UNUSED_TOKEN_146]', '')
+        
+        return response
+
+    @torch.no_grad()
+    def write_webpage(
+        self,
+        inst: str,
+        image: List[Tuple[str, str]] = [],
+        max_new_tokens: int = 4800,
+        do_sample: bool = True,
+        num_beams: int = 2,
+        temperature: float = 1.0,
+        repetition_penalty: float=3.0,
+        seed: int = -1,
+        use_meta: bool = False,
+        task: str = 'Instruction-aware Webpage Generation',
+        **kwargs,
+    ):
+        
+        if seed != -1:
+            set_random_seed(seed, set_cudnn=True)
+        with torch.no_grad():
+            inputs, im_mask, len_input_tokens = self.interleav_wrap_chat(inst, image)
+
+        with torch.autocast(device_type='cuda', dtype=torch.float16):
+            with torch.no_grad():
+                generate = self.generate(inputs_embeds=inputs['inputs_embeds'],
+                                          do_sample=do_sample,
+                                          temperature=temperature,
+                                          num_beams=num_beams,
+                                          repetition_penalty=repetition_penalty,
+                                          max_new_tokens=max_new_tokens,
+                                          im_mask=im_mask,
+                                          infer_mode='web'
+                                         )
+        response = generate[0].tolist()
+        response = self.tokenizer.decode(response, skip_special_tokens=True)
+        # remove eoa
+        response = response.replace('[UNUSED_TOKEN_145]', '')
+        out = response.replace('[UNUSED_TOKEN_146]', '')
+        image_type = 'random'
+        pattern = r'''https://source\.unsplash\.com/random/(\d+)x(\d+)/\?([^'"]+)'''
+        if image_type == 'placeholder':
+            out = re.sub(pattern, r"https://placehold.co/\1x\2", out)
+        elif image_type == 'random':
+            out = re.sub(pattern, r"https://picsum.photos/\1/\2", out)
+
+        with open(task.replace(' ', '_') + ".html", "w") as f:
+            f.write(out)
+        return out
+
+    @torch.no_grad()
+    def resume_2_webpage(
+        self,
+        inst: str,
+        image: List[Tuple[str, str]] = [],
+        max_new_tokens: int = 4800,
+        do_sample: bool = True,
+        num_beams: int = 2,
+        temperature: float = 1.0,
+        repetition_penalty: float=3.0,
+        seed: int = -1,
+        use_meta: bool = False,
+        task: str = 'Resume-to-Personal Page',
+        **kwargs,
+    ):
+        
+        if seed != -1:
+            set_random_seed(seed, set_cudnn=True)       
+        try:
+            with open(inst) as fd:
+                resume = fd.read()
+        except:
+            print ('The input should be a resume with markdown format.')
+        inst = ' Generate a personal page using the content in the resume:' + resume
+        with torch.no_grad():
+            inputs, im_mask, len_input_tokens = self.interleav_wrap_chat(inst, image)
+        with torch.autocast(device_type='cuda', dtype=torch.float16):
+            with torch.no_grad():
+                generate = self.generate(inputs_embeds=inputs['inputs_embeds'],
+                                          do_sample=do_sample,
+                                          temperature=temperature,
+                                          num_beams=num_beams,
+                                          repetition_penalty=repetition_penalty,
+                                          max_new_tokens=max_new_tokens,
+                                          im_mask=im_mask,
+                                          infer_mode='web'
+                                         )
+        response = generate[0].tolist()
+        response = self.tokenizer.decode(response, skip_special_tokens=True)
+        # remove eoa
+        response = response.replace('[UNUSED_TOKEN_145]', '')
+        html = response.replace('[UNUSED_TOKEN_146]', '')
+
+        if seed != -1:
+            set_random_seed(seed, set_cudnn=True)       
+        js_inst = ' Generate JavaScript events for the html code:' + html
+        with torch.no_grad():
+            inputs, im_mask, len_input_tokens = self.interleav_wrap_chat(js_inst, image)
+        with torch.autocast(device_type='cuda', dtype=torch.float16):
+            with torch.no_grad():
+                generate = self.generate(inputs_embeds=inputs['inputs_embeds'],
+                                          do_sample=do_sample,
+                                          temperature=temperature,
+                                          num_beams=num_beams,
+                                          repetition_penalty=repetition_penalty,
+                                          max_new_tokens=max_new_tokens,
+                                          im_mask=im_mask,
+                                          infer_mode='web'
+                                         )
+        response = generate[0].tolist()
+        response = self.tokenizer.decode(response, skip_special_tokens=True)
+        # remove eoa
+        response = response.replace('[UNUSED_TOKEN_145]', '')
+        js = response.replace('[UNUSED_TOKEN_146]', '')
+
+        if re.search(r'</script>', html):
+            js = re.findall(r'<script>([\s\S]*?)<\/script>', js)
+            html = re.sub(r'(</script>)', f'\n{js}\n' + r'\1', html)
+        elif re.search(r'</html>', html):
+            html = re.sub(r'(</html>)', f'\n{js}\n' + r'\1', html)
+        out = html
+
+        image_type = 'random'
+        pattern = r'''https://source\.unsplash\.com/random/(\d+)x(\d+)/\?([^'"]+)'''
+        if image_type == 'placeholder':
+            out = re.sub(pattern, r"https://placehold.co/\1x\2", out)
+        elif image_type == 'random':
+            out = re.sub(pattern, r"https://picsum.photos/\1/\2", out)
+
+        with open(task.replace(' ', '_') + ".html", "w") as f:
+            f.write(out)
+        return out
+
+    
+    @torch.no_grad()
+    def screen_2_webpage(
+        self,
+        inst: str,
+        image: List[Tuple[str, str]] = [],
+        max_new_tokens: int = 4800,
+        do_sample: bool = True,
+        num_beams: int = 2,
+        temperature: float = 1.0,
+        repetition_penalty: float=3.0,
+        seed: int = -1,
+        use_meta: bool = False,
+        task: str = 'Screenshot-to-Webpage',
+        **kwargs,
+    ):
+        
+        if seed != -1:
+            set_random_seed(seed, set_cudnn=True)
+        if len(image) == 0:
+            print ('No image is provided, skip')
+            return ''
+        inst = ' Generate the HTML code of this web image with Tailwind CSS.'
+        with torch.no_grad():
+            inputs, im_mask, len_input_tokens = self.interleav_wrap_chat(inst, image)
+
+        with torch.autocast(device_type='cuda'):
+            with torch.no_grad():
+                generate = self.generate(inputs_embeds=inputs['inputs_embeds'],
+                                          do_sample=do_sample,
+                                          temperature=temperature,
+                                          num_beams=num_beams,
+                                          repetition_penalty=repetition_penalty,
+                                          max_new_tokens=max_new_tokens,
+                                          im_mask=im_mask,
+                                          infer_mode='web'
+                                         )
+        response = generate[0].tolist()
+        response = self.tokenizer.decode(response, skip_special_tokens=True)
+        # remove eoa
+        response = response.replace('[UNUSED_TOKEN_145]', '')
+        out = response.replace('[UNUSED_TOKEN_146]', '')
+        image_type = 'random'
+        pattern = r'''https://source\.unsplash\.com/random/(\d+)x(\d+)/\?([^'"]+)'''
+        if image_type == 'placeholder':
+            out = re.sub(pattern, r"https://placehold.co/\1x\2", out)
+        elif image_type == 'random':
+            out = re.sub(pattern, r"https://picsum.photos/\1/\2", out)
+
+        with open(task.replace(' ', '_') + ".html", "w") as f:
+            f.write(out)
+        return out
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+    "vit.vision_tower.vision_model.encoder.layers.9.self_attn.v_proj.bias": "pytorch_model-00002-of-00002.bin",
+    "vit.vision_tower.vision_model.encoder.layers.9.self_attn.v_proj.weight": "pytorch_model-00002-of-00002.bin",
+    "vit.vision_tower.vision_model.pre_layrnorm.bias": "pytorch_model-00002-of-00002.bin",
+    "vit.vision_tower.vision_model.pre_layrnorm.weight": "pytorch_model-00002-of-00002.bin"
+  }
+}
diff --git a/base/special_tokens_map.json b/base/special_tokens_map.json
new file mode 100644
index 0000000000000000000000000000000000000000..1023d3510a8f6a72f071f934b9319d2b3dba616e
--- /dev/null
+++ b/base/special_tokens_map.json
@@ -0,0 +1,38 @@
+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|action_start|>",
+    "<|action_end|>",
+    "<|interpreter|>",
+    "<|plugin|>"
+  ],
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}
diff --git a/base/tokenization_internlm2.py b/base/tokenization_internlm2.py
new file mode 100644
index 0000000000000000000000000000000000000000..ff53eba214b313c86ef489a823167a7ef2b52c09
--- /dev/null
+++ b/base/tokenization_internlm2.py
@@ -0,0 +1,236 @@
+# coding=utf-8
+# Copyright (c) The InternLM team and The HuggingFace Inc. team. All rights reserved.
+#
+# This code is based on transformers/src/transformers/models/llama/tokenization_llama.py
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Tokenization classes for InternLM."""
+import os
+from shutil import copyfile
+from typing import Any, Dict, List, Optional, Tuple
+
+import sentencepiece as spm
+from transformers.tokenization_utils import PreTrainedTokenizer
+from transformers.utils import logging
+
+logger = logging.get_logger(__name__)
+
+VOCAB_FILES_NAMES = {"vocab_file": "./tokenizer.model"}
+
+PRETRAINED_VOCAB_FILES_MAP = {}
+
+
+# Modified from transformers.model.llama.tokenization_llama.LlamaTokenizer
+class InternLM2Tokenizer(PreTrainedTokenizer):
+    """
+    Construct a InternLM2 tokenizer. Based on byte-level Byte-Pair-Encoding.
+
+    Args:
+        vocab_file (`str`):
+            Path to the vocabulary file.
+    """
+
+    vocab_files_names = VOCAB_FILES_NAMES
+    pretrained_vocab_files_map = PRETRAINED_VOCAB_FILES_MAP
+    model_input_names = ["input_ids", "attention_mask"]
+    _auto_class = "AutoTokenizer"
+
+    def __init__(
+        self,
+        vocab_file,
+        unk_token="<unk>",
+        bos_token="<s>",
+        eos_token="</s>",
+        pad_token="</s>",
+        sp_model_kwargs: Optional[Dict[str, Any]] = None,
+        add_bos_token=True,
+        add_eos_token=False,
+        decode_with_prefix_space=False,
+        clean_up_tokenization_spaces=False,
+        **kwargs,
+    ):
+        self.sp_model_kwargs = {} if sp_model_kwargs is None else sp_model_kwargs
+        self.vocab_file = vocab_file
+        self.add_bos_token = add_bos_token
+        self.add_eos_token = add_eos_token
+        self.decode_with_prefix_space = decode_with_prefix_space
+        self.sp_model = spm.SentencePieceProcessor(**self.sp_model_kwargs)
+        self.sp_model.Load(vocab_file)
+        self._no_prefix_space_tokens = None
+        super().__init__(
+            bos_token=bos_token,
+            eos_token=eos_token,
+            unk_token=unk_token,
+            pad_token=pad_token,
+            clean_up_tokenization_spaces=clean_up_tokenization_spaces,
+            **kwargs,
+        )
+
+    @property
+    def no_prefix_space_tokens(self):
+        if self._no_prefix_space_tokens is None:
+            vocab = self.convert_ids_to_tokens(list(range(self.vocab_size)))
+            self._no_prefix_space_tokens = {i for i, tok in enumerate(vocab) if not tok.startswith("▁")}
+        return self._no_prefix_space_tokens
+
+    @property
+    def vocab_size(self):
+        """Returns vocab size"""
+        return self.sp_model.get_piece_size()
+
+    @property
+    def bos_token_id(self) -> Optional[int]:
+        return self.sp_model.bos_id()
+
+    @property
+    def eos_token_id(self) -> Optional[int]:
+        return self.sp_model.eos_id()
+
+    def get_vocab(self):
+        """Returns vocab as a dict"""
+        vocab = {self.convert_ids_to_tokens(i): i for i in range(self.vocab_size)}
+        vocab.update(self.added_tokens_encoder)
+        return vocab
+
+    def _tokenize(self, text):
+        """Returns a tokenized string."""
+        return self.sp_model.encode(text, out_type=str)
+
+    def _convert_token_to_id(self, token):
+        """Converts a token (str) in an id using the vocab."""
+        return self.sp_model.piece_to_id(token)
+
+    def _convert_id_to_token(self, index):
+        """Converts an index (integer) in a token (str) using the vocab."""
+        token = self.sp_model.IdToPiece(index)
+        return token
+
+    def _maybe_add_prefix_space(self, tokens, decoded):
+        if tokens and tokens[0] not in self.no_prefix_space_tokens:
+            return " " + decoded
+        else:
+            return decoded
+
+    def convert_tokens_to_string(self, tokens):
+        """Converts a sequence of tokens (string) in a single string."""
+        current_sub_tokens = []
+        out_string = ""
+        prev_is_special = False
+        for token in tokens:
+            # make sure that special tokens are not decoded using sentencepiece model
+            if token in self.all_special_tokens:
+                if not prev_is_special:
+                    out_string += " "
+                out_string += self.sp_model.decode(current_sub_tokens) + token
+                prev_is_special = True
+                current_sub_tokens = []
+            else:
+                current_sub_tokens.append(token)
+                prev_is_special = False
+        out_string += self.sp_model.decode(current_sub_tokens)
+        out_string = self.clean_up_tokenization(out_string)
+        out_string = self._maybe_add_prefix_space(tokens=tokens, decoded=out_string)
+        return out_string[1:]
+
+    def save_vocabulary(self, save_directory, filename_prefix: Optional[str] = None) -> Tuple[str]:
+        """
+        Save the vocabulary and special tokens file to a directory.
+
+        Args:
+            save_directory (`str`):
+                The directory in which to save the vocabulary.
+
+        Returns:
+            `Tuple(str)`: Paths to the files saved.
+        """
+        if not os.path.isdir(save_directory):
+            logger.error(f"Vocabulary path ({save_directory}) should be a directory")
+            return
+        out_vocab_file = os.path.join(
+            save_directory, (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]
+        )
+
+        if os.path.abspath(self.vocab_file) != os.path.abspath(out_vocab_file) and os.path.isfile(self.vocab_file):
+            copyfile(self.vocab_file, out_vocab_file)
+        elif not os.path.isfile(self.vocab_file):
+            with open(out_vocab_file, "wb") as fi:
+                content_spiece_model = self.sp_model.serialized_model_proto()
+                fi.write(content_spiece_model)
+
+        return (out_vocab_file,)
+
+    def build_inputs_with_special_tokens(self, token_ids_0, token_ids_1=None):
+        if self.add_bos_token:
+            bos_token_ids = [self.bos_token_id]
+        else:
+            bos_token_ids = []
+
+        output = bos_token_ids + token_ids_0
+
+        if token_ids_1 is not None:
+            output = output + token_ids_1
+
+        if self.add_eos_token:
+            output = output + [self.eos_token_id]
+
+        return output
+
+    def get_special_tokens_mask(
+        self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None, already_has_special_tokens: bool = False
+    ) -> List[int]:
+        """
+        Retrieve sequence ids from a token list that has no special tokens added. This method is called when adding
+        special tokens using the tokenizer `prepare_for_model` method.
+
+        Args:
+            token_ids_0 (`List[int]`):
+                List of IDs.
+            token_ids_1 (`List[int]`, *optional*):
+                Optional second list of IDs for sequence pairs.
+            already_has_special_tokens (`bool`, *optional*, defaults to `False`):
+                Whether or not the token list is already formatted with special tokens for the model.
+
+        Returns:
+            `List[int]`: A list of integers in the range [0, 1]: 1 for a special token, 0 for a sequence token.
+        """
+        if already_has_special_tokens:
+            return super().get_special_tokens_mask(
+                token_ids_0=token_ids_0, token_ids_1=token_ids_1, already_has_special_tokens=True
+            )
+
+        if token_ids_1 is None:
+            return [1] + ([0] * len(token_ids_0)) + [1]
+        return [1] + ([0] * len(token_ids_0)) + [1, 1] + ([0] * len(token_ids_1)) + [1]
+
+    def create_token_type_ids_from_sequences(
+        self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None
+    ) -> List[int]:
+        """
+        Create a mask from the two sequences passed to be used in a sequence-pair classification task. T5 does not make
+        use of token type ids, therefore a list of zeros is returned.
+
+        Args:
+            token_ids_0 (`List[int]`):
+                List of IDs.
+            token_ids_1 (`List[int]`, *optional*):
+                Optional second list of IDs for sequence pairs.
+
+        Returns:
+            `List[int]`: List of zeros.
+        """
+        eos = [self.eos_token_id]
+
+        if token_ids_1 is None:
+            return len(token_ids_0 + eos) * [0]
+        return len(token_ids_0 + eos + token_ids_1 + eos) * [0]
diff --git a/base/tokenizer.model b/base/tokenizer.model
new file mode 100644
index 0000000000000000000000000000000000000000..6600712949ca9c4ffb50f25275993a21fba0b408
--- /dev/null
+++ b/base/tokenizer.model
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f868398fc4e05ee1e8aeba95ddf18ddcc45b8bce55d5093bead5bbf80429b48b
+size 1477754
diff --git a/base/tokenizer_config.json b/base/tokenizer_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..c09328e63848220f5be589fd72e139f38ecbf5fb
--- /dev/null
+++ b/base/tokenizer_config.json
@@ -0,0 +1,99 @@
+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "92538": {
+      "content": "<|plugin|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "92539": {
+      "content": "<|interpreter|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "92540": {
+      "content": "<|action_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "92541": {
+      "content": "<|action_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "92542": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "92543": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|action_start|>",
+    "<|action_end|>",
+    "<|interpreter|>",
+    "<|plugin|>"
+  ],
+  "auto_map": {
+    "AutoTokenizer": [
+      "tokenization_internlm2.InternLM2Tokenizer",
+      null
+    ]
+  },
+  "bos_token": "<s>",
+  "chat_template": "{{ bos_token }}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "</s>",
+  "padding_side": "right",
+  "tokenizer_class": "InternLM2Tokenizer",
+  "unk_token": "<unk>"
+}
diff --git a/memory/.gitattributes b/memory/.gitattributes
new file mode 100644
index 0000000000000000000000000000000000000000..279ed54b50840fc7db83ba48fb918a5b21e7ced7
--- /dev/null
+++ b/memory/.gitattributes
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diff --git a/memory/added_tokens.json b/memory/added_tokens.json
new file mode 100644
index 0000000000000000000000000000000000000000..409be9f93d4810d569098a16c4bf30c977edf44a
--- /dev/null
+++ b/memory/added_tokens.json
@@ -0,0 +1,5 @@
+{
+  "<|endoftext|>": 151643,
+  "<|im_end|>": 151645,
+  "<|im_start|>": 151644
+}
diff --git a/memory/builder_compressor.py b/memory/builder_compressor.py
new file mode 100644
index 0000000000000000000000000000000000000000..d429136948257bb22cde7f09f054855907ef318e
--- /dev/null
+++ b/memory/builder_compressor.py
@@ -0,0 +1,192 @@
+import os
+from llava_phi import LlavaPhiForCausalLM, PhiConfig
+
+import torch
+import torch.nn as nn
+
+import re
+from transformers import AutoTokenizer, AutoModelForCausalLM, AutoConfig, BitsAndBytesConfig
+from typing import Optional, List
+
+class PhiCompressor(nn.Module):
+    def __init__(self, compressor):
+        super().__init__()
+
+        self.model_path = compressor
+        self.tokenizer = AutoTokenizer.from_pretrained(self.model_path)
+        self.compressor = LlavaPhiForCausalLM.from_pretrained(self.model_path)
+        self.select_layer = 15
+
+    def forward_video_encoding(
+        self,
+        input_ids: torch.LongTensor = None,
+        attention_mask: Optional[torch.Tensor] = None,
+        qs_ids: Optional[torch.LongTensor]= None,
+        qs_mask: Optional[torch.Tensor] = None,
+        time_labels: Optional[torch.FloatTensor] = None,
+        position_ids: Optional[torch.LongTensor] = None,
+        past_key_values: Optional[List[torch.FloatTensor]] = None,
+        inputs_embeds: Optional[torch.FloatTensor] = None,
+        labels: Optional[torch.LongTensor] = None,
+        use_cache: Optional[bool] = None,
+        output_attentions: Optional[bool] = None,
+        output_hidden_states: Optional[bool] = None,
+        images: Optional[torch.FloatTensor] = None,
+        projector: Optional[torch.LongTensor] = None,
+        select_layer: Optional[int] = None,
+        return_dict: Optional[bool] = None,
+    ) -> torch.FloatTensor:
+
+        full_memory, full_time = self.compressor.forward_video_encoding(
+            input_ids,
+            attention_mask,
+            qs_ids,
+            qs_mask,
+            time_labels,
+            position_ids,
+            past_key_values,
+            inputs_embeds,
+            labels,
+            use_cache,
+            output_attentions,
+            output_hidden_states,
+            images,
+            projector,
+            select_layer,
+            return_dict
+        )
+        return full_memory, full_time
+
+    def forward_question(
+        self,
+        input_ids: Optional[torch.Tensor] = None,
+        attention_mask: Optional[torch.Tensor] = None,
+        qs_ids: Optional[torch.LongTensor]= None,
+        qs_mask: Optional[torch.Tensor] = None,
+        time_labels: Optional[torch.FloatTensor] = None,
+        position_ids: Optional[torch.LongTensor] = None,
+        past_key_values: Optional[List[torch.FloatTensor]] = None,
+        inputs_embeds: Optional[torch.FloatTensor] = None,
+        labels: Optional[torch.LongTensor] = None,
+        use_cache: Optional[bool] = None,
+        output_attentions: Optional[bool] = None,
+        output_hidden_states: Optional[bool] = None,
+        memory: Optional[torch.FloatTensor] = None,
+        projector: Optional[torch.LongTensor] = None,
+        select_layer: Optional[int] = None,
+        return_dict: Optional[bool] = None,
+    ) -> torch.FloatTensor:
+
+        qs_token = self.compressor.forward_question(
+            input_ids,
+            attention_mask,
+            qs_ids,
+            qs_mask,
+            time_labels,
+            position_ids,
+            past_key_values,
+            inputs_embeds,
+            labels,
+            use_cache,
+            output_attentions,
+            output_hidden_states,
+            memory,
+            projector,
+            select_layer,
+            return_dict
+        )
+        return qs_token
+
+    def forward_compress(
+        self,
+        input_ids: torch.LongTensor = None,
+        attention_mask: Optional[torch.Tensor] = None,
+        qs_ids: Optional[torch.LongTensor]= None,
+        qs_mask: Optional[torch.Tensor] = None,
+        time_labels: Optional[torch.FloatTensor] = None,
+        position_ids: Optional[torch.LongTensor] = None,
+        past_key_values: Optional[List[torch.FloatTensor]] = None,
+        inputs_embeds: Optional[torch.FloatTensor] = None,
+        labels: Optional[torch.LongTensor] = None,
+        use_cache: Optional[bool] = None,
+        output_attentions: Optional[bool] = None,
+        output_hidden_states: Optional[bool] = None,
+        images: Optional[torch.FloatTensor] = None,
+        projector: Optional[torch.LongTensor] = None,
+        select_layer: Optional[int] = None,
+        return_dict: Optional[bool] = None,
+    ) -> torch.FloatTensor:
+
+        compress_tokens, loss, similarity = self.compressor.forward_token(
+            input_ids,
+            attention_mask,
+            qs_ids,
+            qs_mask,
+            time_labels,
+            position_ids,
+            past_key_values,
+            inputs_embeds,
+            labels,
+            use_cache,
+            output_attentions,
+            output_hidden_states,
+            images,
+            projector,
+            select_layer,
+            return_dict
+        )
+        return compress_tokens, loss, similarity
+    
+    def forward(self, clips, seqs, compress_mask, qs, qs_mask, time_labels):
+        return self.forward_compress(input_ids=seqs, attention_mask=compress_mask, qs_ids=qs, qs_mask=qs_mask, images=clips, select_layer=self.select_layer, time_labels=time_labels)
+
+
+    @property
+    def dummy_feature(self):
+        return torch.zeros(1, self.hidden_size, device=self.device, dtype=self.dtype)
+
+    @property
+    def dtype(self):
+        return self.compressor.dtype
+
+    @property
+    def device(self):
+        return self.compressor.device
+
+    @property
+    def config(self):
+        return self.compressor.config
+
+    @property
+    def hidden_size(self):
+        return self.config.hidden_size
+
+
+def build_compressor(compressor_cfg):
+    compressor = getattr(compressor_cfg, 'mm_compressor', getattr(compressor_cfg, 'compressor', None))
+    is_absolute_path_exists = os.path.exists(compressor)
+    if is_absolute_path_exists:
+        return PhiCompressor(compressor)
+    
+    raise ValueError(f'Unknown compressor: {compressor}')
+
+
+def build_compress_projector(config):
+    projector_type = getattr(config, 'compress_projector_type', 'linear')
+
+    if projector_type == 'linear':
+        return nn.Linear(config.compress_hidden_size, config.hidden_size)
+
+    mlp_gelu_match = re.match(r'^mlp(\d+)x_gelu$', projector_type)
+    if mlp_gelu_match:
+        mlp_depth = int(mlp_gelu_match.group(1))
+        modules = [nn.Linear(config.compress_hidden_size, config.hidden_size)]
+        for _ in range(1, mlp_depth):
+            modules.append(nn.GELU())
+            modules.append(nn.Linear(config.hidden_size, config.hidden_size))
+        return nn.Sequential(*modules)
+
+    if projector_type == 'identity':
+        return IdentityMap()
+    
+    raise ValueError(f'Unknown projector type: {projector_type}')
diff --git a/memory/builder_encoder.py b/memory/builder_encoder.py
new file mode 100644
index 0000000000000000000000000000000000000000..77d682fce61b3e347ca9e225d6e8e16b98f5990e
--- /dev/null
+++ b/memory/builder_encoder.py
@@ -0,0 +1,11 @@
+import os
+from clip_encoder import CLIPVisionTower
+
+
+def build_vision_tower(vision_tower_cfg, **kwargs):
+    vision_tower = getattr(vision_tower_cfg, 'mm_vision_tower', getattr(vision_tower_cfg, 'vision_tower', None))
+    is_absolute_path_exists = os.path.exists(vision_tower)
+    if is_absolute_path_exists or vision_tower.startswith("openai") or vision_tower.startswith("laion"):
+        return CLIPVisionTower(vision_tower, args=vision_tower_cfg, **kwargs)
+
+    raise ValueError(f'Unknown vision tower: {vision_tower}')
diff --git a/memory/builder_projector.py b/memory/builder_projector.py
new file mode 100644
index 0000000000000000000000000000000000000000..55e2fd4985ee551684f592298fc86f334c39d3df
--- /dev/null
+++ b/memory/builder_projector.py
@@ -0,0 +1,412 @@
+import torch
+import torch.nn as nn
+from torch.nn.init import trunc_normal_
+import torch.nn.functional as F
+import re
+import math
+import numpy as np
+import random
+
+class IdentityMap(nn.Module):
+    def __init__(self):
+        super().__init__()
+
+    def forward(self, x, *args, **kwargs):
+        return x
+
+    @property
+    def config(self):
+        return {"mm_projector_type": 'identity'}
+
+
+class SimpleResBlock(nn.Module):
+    def __init__(self, channels):
+        super().__init__()
+        self.pre_norm = nn.LayerNorm(channels)
+
+        self.proj = nn.Sequential(
+            nn.Linear(channels, channels),
+            nn.GELU(),
+            nn.Linear(channels, channels)
+        )
+    def forward(self, x):
+        x = self.pre_norm(x)
+        return x + self.proj(x)
+
+
+class SlotAttention(nn.Module):
+    """Slot Attention module."""
+
+    def __init__(self, num_slots, encoder_dims, iters=3, hidden_dim=128, out_dim=128, eps=1e-4):
+        """Builds the Slot Attention module.
+        Args:
+            iters: Number of iterations.
+            num_slots: Number of slots.
+            encoder_dims: Dimensionality of slot feature vectors.
+            hidden_dim: Hidden layer size of MLP.
+            eps: Offset for attention coefficients before normalization.
+        """
+        super(SlotAttention, self).__init__()
+        
+        self.eps = eps
+        self.iters = iters
+        self.num_slots = num_slots
+        self.scale = encoder_dims ** -0.5
+        self.norm_input = nn.LayerNorm(encoder_dims)
+        self.norm_slots = nn.LayerNorm(encoder_dims)
+        self.norm_pre_ff = nn.LayerNorm(encoder_dims)
+
+        self.slots_embedding = nn.Parameter(torch.randn(1, num_slots, encoder_dims))
+        self.project_q = nn.Linear(encoder_dims, encoder_dims)
+        self.project_k = nn.Linear(encoder_dims, encoder_dims)
+        self.project_v = nn.Linear(encoder_dims, encoder_dims)
+
+        hidden_dim = max(encoder_dims, hidden_dim)
+        self.mlp = nn.Sequential(
+            nn.Linear(encoder_dims, hidden_dim),
+            nn.GELU(),
+            nn.Linear(hidden_dim, encoder_dims)
+        )
+
+        self.head = nn.Linear(encoder_dims, out_dim)
+
+    def forward(self, inputs):
+        # inputs has shape [batch_size, num_inputs, inputs_size].
+        inputs = self.norm_input(inputs)  # Apply layer norm to the input.
+        k = self.project_k(inputs)  # Shape: [batch_size, num_inputs, slot_size].
+        v = self.project_v(inputs)  # Shape: [batch_size, num_inputs, slot_size].
+
+        # Initialize the slots. Shape: [batch_size, num_slots, slot_size].
+        b, n, d = inputs.shape
+        n_s = self.num_slots
+
+        # learnable slots initializations
+        init_slots = self.slots_embedding.expand(b, -1, -1)
+        slots = init_slots
+        # Multiple rounds of attention.
+        for t in range(self.iters):
+            slots_prev = slots
+            slots = self.norm_slots(slots)
+
+            # Attention.
+            q = self.project_q(slots)  # Shape: [batch_size, num_slots, slot_size].
+            dots = torch.einsum('bid,bjd->bij', q, k) * self.scale
+            attn = dots.softmax(dim=1) + self.eps
+            attn = attn / attn.sum(dim=-1, keepdim=True)  # weighted mean.
+
+            updates = torch.einsum('bjd,bij->bid', v, attn)
+            # `updates` has shape: [batch_size, num_slots, slot_size].
+
+            # Slot update.
+            slots = slots_prev + updates
+            slots = slots + self.mlp(self.norm_pre_ff(slots))
+            if t == self.iters-2:
+                slots = slots.detach() - init_slots.detach() + init_slots
+
+        output = self.head(slots)
+
+        return output
+
+
+class PerceiverSampler(nn.Module):
+
+    def __init__(self, num_query_token, num_vision_features, out_size):
+        super(PerceiverSampler, self).__init__()
+        self.Qformer, self.query_tokens = self.init_qformer(
+            num_query_token, num_vision_features)
+        self.Qformer.bert.embeddings.word_embeddings = None
+        self.Qformer.bert.embeddings.position_embeddings = None
+        for layer in self.Qformer.bert.encoder.layer:
+            layer.output = None
+            layer.intermediate = None
+        self.Qformer.cls = None
+        self.ln_vision = nn.LayerNorm(num_vision_features)
+        self.head = nn.Linear(self.Qformer.config.hidden_size, out_size)
+
+    @classmethod
+    def init_qformer(cls,
+                     num_query_token,
+                     vision_width,
+                     cross_attention_freq=2,
+                     pretrain=True):
+        encoder_config = BertConfig()
+        encoder_config.encoder_width = vision_width
+        # insert cross-attention layer every other block
+        encoder_config.add_cross_attention = True
+        encoder_config.cross_attention_freq = cross_attention_freq
+        encoder_config.query_length = num_query_token
+        Qformer = BertLMHeadModel(config=encoder_config)
+        query_tokens = nn.Parameter(
+            torch.randn(1, num_query_token, encoder_config.hidden_size))
+        query_tokens.data.normal_(mean=0.0,
+                                  std=encoder_config.initializer_range)
+        return Qformer, query_tokens
+
+    def forward(self, inputs):
+        image_embeds = self.ln_vision(inputs)
+        image_atts = torch.ones(image_embeds.size()[:-1],
+                                dtype=torch.long).to(inputs.device)
+        query_tokens = self.query_tokens.expand(image_embeds.shape[0], -1, -1)
+        query_output = self.Qformer.bert(
+            query_embeds=query_tokens,
+            encoder_hidden_states=image_embeds,
+            encoder_attention_mask=image_atts,
+            return_dict=True,
+        )
+        output = self.head(query_output.last_hidden_state)
+        return output
+
+
+class MultiProjector(nn.Module):
+
+    def __init__(self, mlp, sa):
+        super(MultiProjector, self).__init__()
+        self.mlp = mlp
+        self.sa = sa
+
+    def forward(self, inputs, projector=None):
+        if not self.training:
+            output = self.mlp(inputs)
+            return output
+
+        idx_mlp = torch.where(projector==0)[0]
+        idx_sa = torch.where(projector==1)[0]
+        feat_mlp = self.mlp(inputs)
+        feat_sa = self.sa(inputs)
+
+        if len(idx_mlp) == 0:
+            projector[random.randint(0, projector.shape[0]-1), 0] = 0
+        elif len(idx_sa) == 0:
+            projector[random.randint(0, projector.shape[0]-1), 0] = 1
+        
+        idx_mlp = torch.where(projector==0)[0]
+        idx_sa = torch.where(projector==1)[0]
+
+        output = []
+        for i in range(inputs.shape[0]):
+            if i in idx_mlp:
+                output.append(feat_mlp[i])
+            if i in idx_sa:
+                output.append(feat_sa[i])
+        assert len(output) == inputs.shape[0]
+        return output
+
+
+class CompressProjector(nn.Module):
+
+    def __init__(self, mlp, num_slot, embed_dim):
+        super(CompressProjector, self).__init__()
+        self.mlp = mlp
+        self.num_slot = num_slot
+        self.query = nn.Parameter(torch.zeros(num_slot, embed_dim))
+        trunc_normal_(self.query, std=.02)
+
+    def forward(self, inputs, projector=None):
+        
+        if type(inputs) is list:
+            concat_images, concat_features = inputs
+            concat_combine = torch.cat(
+                [concat_images.reshape(-1, concat_images.shape[-1]), concat_features.reshape(-1, concat_features.shape[-1])], dim=0)
+            concat_combine = self.mlp(concat_combine)
+            concat_images = concat_combine[:concat_images.shape[0]*concat_images.shape[1]].contiguous().view(*concat_images.shape[:2], -1)
+            concat_features = concat_combine[concat_images.shape[0]*concat_images.shape[1]:].contiguous().view(*concat_features.shape[:2], -1)
+            image_query = self.query.expand(concat_images.shape[0], -1, -1)
+            concat_images = torch.cat([concat_images, image_query], dim=1)
+            feature_query = self.query.expand(concat_features.shape[0], -1, -1)
+            concat_features = torch.cat([concat_features, feature_query], dim=1)
+            return concat_images, concat_features
+
+        output = self.mlp(inputs)
+        query = self.query.expand(output.shape[0], -1, -1)
+        output = torch.cat([output, query], dim=1)
+        return output
+
+
+class PoolProjector(nn.Module):
+
+    def __init__(self, mlp, resolution, pool_num):
+        super(PoolProjector, self).__init__()
+        self.mlp = mlp
+        self.pool_num = pool_num
+        self.resolution = resolution
+
+    def forward(self, inputs, projector=None):
+        
+        if type(inputs) is list:
+            concat_images, concat_features = inputs
+            assert concat_images.shape[1] == self.resolution
+            h = int(np.sqrt(self.resolution))
+            grid = int(np.sqrt(self.pool_num))
+            n, k, c = concat_images.shape
+            image_maps = concat_images.view(n, h, h, c)
+            image_maps = image_maps.view(n, grid, h//grid, grid, h//grid, c)
+            image_maps = image_maps.permute(0, 1, 3, 2, 4, 5).contiguous()
+            image_maps = image_maps.view(n, self.pool_num, self.resolution//self.pool_num, c)
+            image_slot = torch.mean(image_maps, dim=-2)
+            image_global = torch.mean(concat_images, dim=1, keepdim=True)
+            n, k, c = concat_features.shape
+            video_maps = concat_features.view(n, k//self.resolution, h, h, c)
+            video_maps = video_maps.view(n, k//self.resolution, grid, h//grid, grid, h//grid, c)
+            video_maps = video_maps.permute(0, 1, 2, 4, 3, 5, 6).contiguous()
+            video_maps = video_maps.view(n, k//self.resolution, self.pool_num, self.resolution//self.pool_num, c)
+            video_slot = torch.mean(video_maps, dim=-2).view(n, k//self.resolution*self.pool_num, c)
+            video_global = torch.mean(concat_features, dim=1, keepdim=True)
+            concat_images = torch.cat([concat_images, image_slot, image_global], dim=1) # stage 2 n k+1 c
+            concat_features = torch.cat([concat_features, video_slot, video_global], dim=1) # stage 2 n tk+t c
+            # concat_images = torch.cat([concat_images, image_slot], dim=1) # stage 1 n k c
+            # concat_features = torch.cat([concat_features, video_slot], dim=1) # stage 1 n tk c
+            concat_combine = torch.cat(
+                [concat_images.reshape(-1, concat_images.shape[-1]), concat_features.reshape(-1, concat_features.shape[-1])], dim=0)
+            concat_combine = self.mlp(concat_combine)
+            concat_images = concat_combine[:concat_images.shape[0]*concat_images.shape[1]].contiguous().view(*concat_images.shape[:2], -1)
+            concat_features = concat_combine[concat_images.shape[0]*concat_images.shape[1]:].contiguous().view(*concat_features.shape[:2], -1)
+            return concat_images, concat_features
+
+        n, k, c = inputs.shape
+        h = int(np.sqrt(self.resolution))
+        grid = int(np.sqrt(self.pool_num))
+        maps = inputs.view(n, k//self.resolution, h, h, c)
+        maps = maps.view(n, k//self.resolution, grid, h//grid, grid, h//grid, c)
+        maps = maps.permute(0, 1, 2, 4, 3, 5, 6).contiguous()
+        maps = maps.view(n, k//self.resolution, self.pool_num, self.resolution//self.pool_num, c)
+        slot = torch.mean(maps, dim=-2).view(n, k//self.resolution*self.pool_num, c)
+        global_pool = torch.mean(inputs, dim=1, keepdim=True)
+        output = self.mlp(torch.cat([inputs, slot, global_pool], dim=1)) # stage 2
+        # output = self.mlp(torch.cat([inputs, slot], dim=1)) # stage 1
+        return output
+
+
+class BaseProjector(nn.Module):
+
+    def __init__(self, mlp):
+        super(BaseProjector, self).__init__()
+        self.mlp = mlp
+
+    def forward(self, inputs, projector=None):
+        
+        if type(inputs) is list:
+            concat_images, concat_features = inputs
+            time_token = torch.mean(concat_features, dim=2) # n t c
+            spatial_token = torch.mean(concat_features, dim=1) # n k c
+            concat_features = torch.cat([time_token, spatial_token], dim=1) # n t+k c
+            concat_combine = torch.cat(
+                [concat_images.reshape(-1, concat_images.shape[-1]), concat_features.reshape(-1, concat_features.shape[-1])], dim=0)
+            concat_combine = self.mlp(concat_combine)
+            concat_images = concat_combine[:concat_images.shape[0]*concat_images.shape[1]].contiguous().view(*concat_images.shape[:2], -1)
+            concat_features = concat_combine[concat_images.shape[0]*concat_images.shape[1]:].contiguous().view(*concat_features.shape[:2], -1)
+            return concat_images, concat_features
+        
+        if inputs.ndim == 3:
+            output = self.mlp(inputs)
+            return output
+        
+        if inputs.ndim == 4:
+            time_token = torch.mean(inputs, dim=2) # n t c
+            spatial_token = torch.mean(inputs, dim=1) # n k c
+            token = torch.cat([time_token, spatial_token], dim=1)
+            output = self.mlp(token) # n t+k c
+            return output
+
+
+class BaseMixProjector(nn.Module):
+
+    def __init__(self, mlp):
+        super(BaseMixProjector, self).__init__()
+        self.mlp = mlp
+
+    def forward(self, inputs, projector=None):
+        
+        if type(inputs) is list:
+            concat_images, concat_features = inputs
+            n, t, k, c = concat_features.shape
+            concat_features = concat_features.view(n, t*k, c) # n t*k c
+            concat_combine = torch.cat(
+                [concat_images.reshape(-1, concat_images.shape[-1]), concat_features.reshape(-1, concat_features.shape[-1])], dim=0)
+            concat_combine = self.mlp(concat_combine)
+            concat_images = concat_combine[:concat_images.shape[0]*concat_images.shape[1]].contiguous().view(*concat_images.shape[:2], -1)
+            concat_features = concat_combine[concat_images.shape[0]*concat_images.shape[1]:].contiguous().view(*concat_features.shape[:2], -1)
+            return concat_images, concat_features
+        
+        if inputs.ndim == 3:
+            output = self.mlp(inputs)
+            return output
+        
+        if inputs.ndim == 4:
+            n, t, k, c = inputs.shape
+            token = inputs.view(n, t*k, c)
+            output = self.mlp(token) # n t*k c
+            return output
+
+
+def build_vision_projector(config, delay_load=False, **kwargs):
+    projector_type = getattr(config, 'mm_projector_type', 'linear')
+
+    if projector_type == 'linear':
+        return nn.Linear(config.mm_hidden_size, config.hidden_size)
+
+    mlp_gelu_match = re.match(r'^mlp(\d+)x_gelu$', projector_type)
+    if mlp_gelu_match:
+        mlp_depth = int(mlp_gelu_match.group(1))
+        modules = [nn.Linear(config.mm_hidden_size, config.hidden_size)]
+        for _ in range(1, mlp_depth):
+            modules.append(nn.GELU())
+            modules.append(nn.Linear(config.hidden_size, config.hidden_size))
+        return nn.Sequential(*modules)
+
+    if projector_type == 'identity':
+        return IdentityMap()
+    
+    if projector_type == 'slot':
+        return SlotAttention(config.n_slot, config.mm_hidden_size, 3, config.hidden_size, config.hidden_size)
+    
+    if projector_type == 'perceiver':
+        return PerceiverSampler(config.n_slot, config.mm_hidden_size, config.hidden_size)
+
+    if projector_type == 'mlpslot':
+        mlp_depth = 2
+        modules = [nn.Linear(config.mm_hidden_size, config.hidden_size)]
+        for _ in range(1, mlp_depth):
+            modules.append(nn.GELU())
+            modules.append(nn.Linear(config.hidden_size, config.hidden_size))
+        mlp = nn.Sequential(*modules)
+        sa = SlotAttention(config.n_slot, config.mm_hidden_size, 3, config.hidden_size, config.hidden_size)
+        return MultiProjector(mlp, sa)
+    
+    if projector_type == 'compress':
+        mlp_depth = 2
+        modules = [nn.Linear(4*config.mm_hidden_size, config.hidden_size)]
+        for _ in range(1, mlp_depth):
+            modules.append(nn.GELU())
+            modules.append(nn.Linear(config.hidden_size, config.hidden_size))
+        mlp = nn.Sequential(*modules)
+        return CompressProjector(mlp, config.n_slot, config.hidden_size)
+
+    if projector_type == 'pool':
+        mlp_depth = 2
+        modules = [nn.Linear(4*config.mm_hidden_size, config.hidden_size)]
+        for _ in range(1, mlp_depth):
+            modules.append(nn.GELU())
+            modules.append(nn.Linear(config.hidden_size, config.hidden_size))
+        mlp = nn.Sequential(*modules)
+        pool_num = config.pool_num if hasattr(config, 'pool_num') else 1
+        return PoolProjector(mlp, config.resolution, pool_num)
+
+    if projector_type == 'base':
+        mlp_depth = 2
+        modules = [nn.Linear(config.mm_hidden_size, config.hidden_size)]
+        for _ in range(1, mlp_depth):
+            modules.append(nn.GELU())
+            modules.append(nn.Linear(config.hidden_size, config.hidden_size))
+        mlp = nn.Sequential(*modules)
+        return BaseProjector(mlp)
+
+    if projector_type == 'base_mix':
+        mlp_depth = 2
+        modules = [nn.Linear(4*config.mm_hidden_size, config.hidden_size)]
+        for _ in range(1, mlp_depth):
+            modules.append(nn.GELU())
+            modules.append(nn.Linear(config.hidden_size, config.hidden_size))
+        mlp = nn.Sequential(*modules)
+        return BaseMixProjector(mlp)
+
+    raise ValueError(f'Unknown projector type: {projector_type}')
diff --git a/memory/clip_encoder.py b/memory/clip_encoder.py
new file mode 100644
index 0000000000000000000000000000000000000000..dbb9015b0fc9fa93483ba77cc303b793e86c36fc
--- /dev/null
+++ b/memory/clip_encoder.py
@@ -0,0 +1,78 @@
+import torch
+import torch.nn as nn
+
+from transformers import CLIPVisionModel, CLIPImageProcessor, CLIPVisionConfig
+
+
+class CLIPVisionTower(nn.Module):
+    def __init__(self, vision_tower, args, delay_load=False):
+        super().__init__()
+
+        self.is_loaded = False
+
+        self.vision_tower_name = vision_tower
+        self.select_layer = args.mm_vision_select_layer
+        self.select_feature = getattr(args, 'mm_vision_select_feature', 'patch')
+
+        if not delay_load:
+            self.load_model()
+        else:
+            self.cfg_only = CLIPVisionConfig.from_pretrained(self.vision_tower_name)
+
+    def load_model(self):
+        self.image_processor = CLIPImageProcessor.from_pretrained(self.vision_tower_name)
+        self.vision_tower = CLIPVisionModel.from_pretrained(self.vision_tower_name)
+        self.vision_tower.requires_grad_(False)
+
+        self.is_loaded = True
+
+    def feature_select(self, image_forward_outs):
+        image_features = image_forward_outs.hidden_states[self.select_layer]
+        if self.select_feature == 'patch':
+            image_features = image_features[:, 1:]
+        elif self.select_feature == 'cls_patch':
+            image_features = image_features
+        else:
+            raise ValueError(f'Unexpected select feature: {self.select_feature}')
+        return image_features
+
+    @torch.no_grad()
+    def forward(self, images):
+        if type(images) is list:
+            image_features = []
+            for image in images:
+                image_forward_out = self.vision_tower(image.to(device=self.device, dtype=self.dtype).unsqueeze(0), output_hidden_states=True)
+                image_feature = self.feature_select(image_forward_out).to(image.dtype)
+                image_features.append(image_feature)
+        else:
+            image_forward_outs = self.vision_tower(images.to(device=self.device, dtype=self.dtype), output_hidden_states=True)
+            image_features = self.feature_select(image_forward_outs).to(images.dtype)
+
+        return image_features
+
+    @property
+    def dummy_feature(self):
+        return torch.zeros(1, self.hidden_size, device=self.device, dtype=self.dtype)
+
+    @property
+    def dtype(self):
+        return self.vision_tower.dtype
+
+    @property
+    def device(self):
+        return self.vision_tower.device
+
+    @property
+    def config(self):
+        if self.is_loaded:
+            return self.vision_tower.config
+        else:
+            return self.cfg_only
+
+    @property
+    def hidden_size(self):
+        return self.config.hidden_size
+
+    @property
+    def num_patches(self):
+        return (self.config.image_size // self.config.patch_size) ** 2
diff --git a/memory/config.json b/memory/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..55c0bb1dc1264df0a403b0d806067095c078dd0b
--- /dev/null
+++ b/memory/config.json
@@ -0,0 +1,44 @@
+{
+  "_name_or_path": "/mnt/hwfile/mllm/qianrui/checkpoints/llava-qwen-2-pool-16f-64r-4p-causal",
+  "architectures": [
+    "GroundQwenForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "eos_token_id": 151645,
+  "freeze_mm_mlp_adapter": false,
+  "hidden_act": "silu",
+  "hidden_size": 1536,
+  "image_aspect_ratio": "square",
+  "initializer_range": 0.02,
+  "intermediate_size": 8960,
+  "max_position_embeddings": 32768,
+  "max_window_layers": 28,
+  "mm_hidden_size": 1024,
+  "mm_projector_lr": null,
+  "mm_projector_type": "pool",
+  "mm_use_im_patch_token": false,
+  "mm_use_im_start_end": false,
+  "mm_vision_select_feature": "patch",
+  "mm_vision_select_layer": -2,
+  "mm_vision_tower": "openai/clip-vit-large-patch14",
+  "model_type": "ground_qwen",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 2,
+  "pool_num": 4,
+  "resolution": 64,
+  "rms_norm_eps": 1e-06,
+  "rope_theta": 1000000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "tokenizer_model_max_length": 32768,
+  "tokenizer_padding_side": "right",
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.41.2",
+  "tune_mm_mlp_adapter": false,
+  "use_cache": true,
+  "use_mm_proj": true,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}
diff --git a/memory/configuration_qwen.py b/memory/configuration_qwen.py
new file mode 100644
index 0000000000000000000000000000000000000000..fc8a667e079aed148fa9dcc651ad7291b439b81a
--- /dev/null
+++ b/memory/configuration_qwen.py
@@ -0,0 +1,140 @@
+# coding=utf-8
+# Copyright 2024 The Qwen team, Alibaba Group and the HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Qwen2 model configuration"""
+
+from transformers.configuration_utils import PretrainedConfig
+from transformers.utils import logging
+
+
+logger = logging.get_logger(__name__)
+
+
+class Qwen2Config(PretrainedConfig):
+    r"""
+    This is the configuration class to store the configuration of a [`Qwen2Model`]. It is used to instantiate a
+    Qwen2 model according to the specified arguments, defining the model architecture. Instantiating a configuration
+    with the defaults will yield a similar configuration to that of
+    Qwen2-7B-beta [Qwen/Qwen2-7B-beta](https://huggingface.co/Qwen/Qwen2-7B-beta).
+
+    Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
+    documentation from [`PretrainedConfig`] for more information.
+
+
+    Args:
+        vocab_size (`int`, *optional*, defaults to 151936):
+            Vocabulary size of the Qwen2 model. Defines the number of different tokens that can be represented by the
+            `inputs_ids` passed when calling [`Qwen2Model`]
+        hidden_size (`int`, *optional*, defaults to 4096):
+            Dimension of the hidden representations.
+        intermediate_size (`int`, *optional*, defaults to 22016):
+            Dimension of the MLP representations.
+        num_hidden_layers (`int`, *optional*, defaults to 32):
+            Number of hidden layers in the Transformer encoder.
+        num_attention_heads (`int`, *optional*, defaults to 32):
+            Number of attention heads for each attention layer in the Transformer encoder.
+        num_key_value_heads (`int`, *optional*, defaults to 32):
+            This is the number of key_value heads that should be used to implement Grouped Query Attention. If
+            `num_key_value_heads=num_attention_heads`, the model will use Multi Head Attention (MHA), if
+            `num_key_value_heads=1` the model will use Multi Query Attention (MQA) otherwise GQA is used. When
+            converting a multi-head checkpoint to a GQA checkpoint, each group key and value head should be constructed
+            by meanpooling all the original heads within that group. For more details checkout [this
+            paper](https://arxiv.org/pdf/2305.13245.pdf). If it is not specified, will default to `32`.
+        hidden_act (`str` or `function`, *optional*, defaults to `"silu"`):
+            The non-linear activation function (function or string) in the decoder.
+        max_position_embeddings (`int`, *optional*, defaults to 32768):
+            The maximum sequence length that this model might ever be used with.
+        initializer_range (`float`, *optional*, defaults to 0.02):
+            The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
+        rms_norm_eps (`float`, *optional*, defaults to 1e-06):
+            The epsilon used by the rms normalization layers.
+        use_cache (`bool`, *optional*, defaults to `True`):
+            Whether or not the model should return the last key/values attentions (not used by all models). Only
+            relevant if `config.is_decoder=True`.
+        tie_word_embeddings (`bool`, *optional*, defaults to `False`):
+            Whether the model's input and output word embeddings should be tied.
+        rope_theta (`float`, *optional*, defaults to 10000.0):
+            The base period of the RoPE embeddings.
+        use_sliding_window (`bool`, *optional*, defaults to `False`):
+            Whether to use sliding window attention.
+        sliding_window (`int`, *optional*, defaults to 4096):
+            Sliding window attention (SWA) window size. If not specified, will default to `4096`.
+        max_window_layers (`int`, *optional*, defaults to 28):
+            The number of layers that use SWA (Sliding Window Attention). The bottom layers use SWA while the top use full attention.
+        attention_dropout (`float`, *optional*, defaults to 0.0):
+            The dropout ratio for the attention probabilities.
+
+    ```python
+    >>> from transformers import Qwen2Model, Qwen2Config
+
+    >>> # Initializing a Qwen2 style configuration
+    >>> configuration = Qwen2Config()
+
+    >>> # Initializing a model from the Qwen2-7B style configuration
+    >>> model = Qwen2Model(configuration)
+
+    >>> # Accessing the model configuration
+    >>> configuration = model.config
+    ```"""
+
+    model_type = "qwen2"
+    keys_to_ignore_at_inference = ["past_key_values"]
+
+    def __init__(
+        self,
+        vocab_size=151936,
+        hidden_size=4096,
+        intermediate_size=22016,
+        num_hidden_layers=32,
+        num_attention_heads=32,
+        num_key_value_heads=32,
+        hidden_act="silu",
+        max_position_embeddings=32768,
+        initializer_range=0.02,
+        rms_norm_eps=1e-6,
+        use_cache=True,
+        tie_word_embeddings=False,
+        rope_theta=10000.0,
+        use_sliding_window=False,
+        sliding_window=4096,
+        max_window_layers=28,
+        attention_dropout=0.0,
+        **kwargs,
+    ):
+        self.vocab_size = vocab_size
+        self.max_position_embeddings = max_position_embeddings
+        self.hidden_size = hidden_size
+        self.intermediate_size = intermediate_size
+        self.num_hidden_layers = num_hidden_layers
+        self.num_attention_heads = num_attention_heads
+        self.use_sliding_window = use_sliding_window
+        self.sliding_window = sliding_window if use_sliding_window else None
+        self.max_window_layers = max_window_layers
+
+        # for backward compatibility
+        if num_key_value_heads is None:
+            num_key_value_heads = num_attention_heads
+
+        self.num_key_value_heads = num_key_value_heads
+        self.hidden_act = hidden_act
+        self.initializer_range = initializer_range
+        self.rms_norm_eps = rms_norm_eps
+        self.use_cache = use_cache
+        self.rope_theta = rope_theta
+        self.attention_dropout = attention_dropout
+
+        super().__init__(
+            tie_word_embeddings=tie_word_embeddings,
+            **kwargs,
+        )
\ No newline at end of file
diff --git a/memory/constants.py b/memory/constants.py
new file mode 100644
index 0000000000000000000000000000000000000000..6964799be0cf9b66dde7fca8e09b709711d8edcb
--- /dev/null
+++ b/memory/constants.py
@@ -0,0 +1,13 @@
+CONTROLLER_HEART_BEAT_EXPIRATION = 30
+WORKER_HEART_BEAT_INTERVAL = 15
+
+LOGDIR = "."
+
+# Model Constants
+IGNORE_INDEX = -100
+IMAGE_TOKEN_INDEX = -200
+DEFAULT_IMAGE_TOKEN = "<image>"
+DEFAULT_IMAGE_PATCH_TOKEN = "<im_patch>"
+DEFAULT_IM_START_TOKEN = "<im_start>"
+DEFAULT_IM_END_TOKEN = "<im_end>"
+IMAGE_PLACEHOLDER = "<image-placeholder>"
\ No newline at end of file
diff --git a/memory/conversation.py b/memory/conversation.py
new file mode 100644
index 0000000000000000000000000000000000000000..713f014fc8f05b6e2d1a26a446c36f22fc6c7aff
--- /dev/null
+++ b/memory/conversation.py
@@ -0,0 +1,405 @@
+import dataclasses
+from enum import auto, Enum
+from typing import List, Tuple
+
+
+class SeparatorStyle(Enum):
+    """Different separator style."""
+    SINGLE = auto()
+    TWO = auto()
+    MPT = auto()
+    PLAIN = auto()
+    LLAMA_2 = auto()
+    PHI = auto()
+
+
+@dataclasses.dataclass
+class Conversation:
+    """A class that keeps all conversation history."""
+    system: str
+    roles: List[str]
+    messages: List[List[str]]
+    offset: int
+    sep_style: SeparatorStyle = SeparatorStyle.SINGLE
+    sep: str = "###"
+    sep2: str = None
+    version: str = "Unknown"
+
+    skip_next: bool = False
+
+    def get_prompt(self):
+        messages = self.messages
+        if len(messages) > 0 and type(messages[0][1]) is tuple:
+            messages = self.messages.copy()
+            init_role, init_msg = messages[0].copy()
+            init_msg = init_msg[0].replace("<image>", "").strip()
+            if 'mmtag' in self.version:
+                messages[0] = (init_role, init_msg)
+                messages.insert(0, (self.roles[0], "<Image><image></Image>"))
+                messages.insert(1, (self.roles[1], "Received."))
+            else:
+                messages[0] = (init_role, "<image>\n" + init_msg)
+
+        if self.sep_style == SeparatorStyle.SINGLE:
+            ret = self.system + self.sep
+            for role, message in messages:
+                if message:
+                    if type(message) is tuple:
+                        message, _, _ = message
+                    ret += role + ": " + message + self.sep
+                else:
+                    ret += role + ":"
+        elif self.sep_style == SeparatorStyle.TWO:
+            seps = [self.sep, self.sep2]
+            ret = self.system + seps[0]
+            for i, (role, message) in enumerate(messages):
+                if message:
+                    if type(message) is tuple:
+                        message, _, _ = message
+                    ret += role + ": " + message + seps[i % 2]
+                else:
+                    ret += role + ":"
+        elif self.sep_style == SeparatorStyle.PHI:
+            seps = [self.sep, self.sep2]
+            ret = self.system + seps[0]
+            for i, (role, message) in enumerate(messages):
+                if message:
+                    if type(message) is tuple:
+                        message, _, _ = message
+                    ret += role + ": " + message + seps[i % 2]
+                else:
+                    ret += role + ":"
+        elif self.sep_style == SeparatorStyle.MPT:
+            ret = self.system + self.sep
+            for role, message in messages:
+                if message:
+                    if type(message) is tuple:
+                        message, _, _ = message
+                    ret += role + message + self.sep
+                else:
+                    ret += role
+        elif self.sep_style == SeparatorStyle.LLAMA_2:
+            wrap_sys = lambda msg: f"<<SYS>>\n{msg}\n<</SYS>>\n\n"
+            wrap_inst = lambda msg: f"[INST] {msg} [/INST]"
+            ret = ""
+
+            for i, (role, message) in enumerate(messages):
+                if i == 0:
+                    assert message, "first message should not be none"
+                    assert role == self.roles[0], "first message should come from user"
+                if message:
+                    if type(message) is tuple:
+                        message, _, _ = message
+                    if i == 0: message = wrap_sys(self.system) + message
+                    if i % 2 == 0:
+                        message = wrap_inst(message)
+                        ret += self.sep + message
+                    else:
+                        ret += " " + message + " " + self.sep2
+                else:
+                    ret += ""
+            ret = ret.lstrip(self.sep)
+        elif self.sep_style == SeparatorStyle.PLAIN:
+            seps = [self.sep, self.sep2]
+            ret = self.system
+            for i, (role, message) in enumerate(messages):
+                if message:
+                    if type(message) is tuple:
+                        message, _, _ = message
+                    ret += message + seps[i % 2]
+                else:
+                    ret += ""
+        else:
+            raise ValueError(f"Invalid style: {self.sep_style}")
+
+        return ret
+
+    def append_message(self, role, message):
+        self.messages.append([role, message])
+
+    def get_images(self, return_pil=False):
+        images = []
+        for i, (role, msg) in enumerate(self.messages[self.offset:]):
+            if i % 2 == 0:
+                if type(msg) is tuple:
+                    import base64
+                    from io import BytesIO
+                    from PIL import Image
+                    msg, image, image_process_mode = msg
+                    if image_process_mode == "Pad":
+                        def expand2square(pil_img, background_color=(122, 116, 104)):
+                            width, height = pil_img.size
+                            if width == height:
+                                return pil_img
+                            elif width > height:
+                                result = Image.new(pil_img.mode, (width, width), background_color)
+                                result.paste(pil_img, (0, (width - height) // 2))
+                                return result
+                            else:
+                                result = Image.new(pil_img.mode, (height, height), background_color)
+                                result.paste(pil_img, ((height - width) // 2, 0))
+                                return result
+                        image = expand2square(image)
+                    elif image_process_mode in ["Default", "Crop"]:
+                        pass
+                    elif image_process_mode == "Resize":
+                        image = image.resize((336, 336))
+                    else:
+                        raise ValueError(f"Invalid image_process_mode: {image_process_mode}")
+                    max_hw, min_hw = max(image.size), min(image.size)
+                    aspect_ratio = max_hw / min_hw
+                    max_len, min_len = 800, 400
+                    shortest_edge = int(min(max_len / aspect_ratio, min_len, min_hw))
+                    longest_edge = int(shortest_edge * aspect_ratio)
+                    W, H = image.size
+                    if longest_edge != max(image.size):
+                        if H > W:
+                            H, W = longest_edge, shortest_edge
+                        else:
+                            H, W = shortest_edge, longest_edge
+                        image = image.resize((W, H))
+                    if return_pil:
+                        images.append(image)
+                    else:
+                        buffered = BytesIO()
+                        image.save(buffered, format="PNG")
+                        img_b64_str = base64.b64encode(buffered.getvalue()).decode()
+                        images.append(img_b64_str)
+        return images
+
+    def to_gradio_chatbot(self):
+        ret = []
+        for i, (role, msg) in enumerate(self.messages[self.offset:]):
+            if i % 2 == 0:
+                if type(msg) is tuple:
+                    import base64
+                    from io import BytesIO
+                    msg, image, image_process_mode = msg
+                    max_hw, min_hw = max(image.size), min(image.size)
+                    aspect_ratio = max_hw / min_hw
+                    max_len, min_len = 800, 400
+                    shortest_edge = int(min(max_len / aspect_ratio, min_len, min_hw))
+                    longest_edge = int(shortest_edge * aspect_ratio)
+                    W, H = image.size
+                    if H > W:
+                        H, W = longest_edge, shortest_edge
+                    else:
+                        H, W = shortest_edge, longest_edge
+                    image = image.resize((W, H))
+                    buffered = BytesIO()
+                    image.save(buffered, format="JPEG")
+                    img_b64_str = base64.b64encode(buffered.getvalue()).decode()
+                    img_str = f'<img src="data:image/png;base64,{img_b64_str}" alt="user upload image" />'
+                    msg = img_str + msg.replace('<image>', '').strip()
+                    ret.append([msg, None])
+                else:
+                    ret.append([msg, None])
+            else:
+                ret[-1][-1] = msg
+        return ret
+
+    def copy(self):
+        return Conversation(
+            system=self.system,
+            roles=self.roles,
+            messages=[[x, y] for x, y in self.messages],
+            offset=self.offset,
+            sep_style=self.sep_style,
+            sep=self.sep,
+            sep2=self.sep2,
+            version=self.version)
+
+    def dict(self):
+        if len(self.get_images()) > 0:
+            return {
+                "system": self.system,
+                "roles": self.roles,
+                "messages": [[x, y[0] if type(y) is tuple else y] for x, y in self.messages],
+                "offset": self.offset,
+                "sep": self.sep,
+                "sep2": self.sep2,
+            }
+        return {
+            "system": self.system,
+            "roles": self.roles,
+            "messages": self.messages,
+            "offset": self.offset,
+            "sep": self.sep,
+            "sep2": self.sep2,
+        }
+
+
+conv_vicuna_v0 = Conversation(
+    system="A chat between a curious human and an artificial intelligence assistant. "
+           "The assistant gives helpful, detailed, and polite answers to the human's questions.",
+    roles=("Human", "Assistant"),
+    messages=(
+        ("Human", "What are the key differences between renewable and non-renewable energy sources?"),
+        ("Assistant",
+            "Renewable energy sources are those that can be replenished naturally in a relatively "
+            "short amount of time, such as solar, wind, hydro, geothermal, and biomass. "
+            "Non-renewable energy sources, on the other hand, are finite and will eventually be "
+            "depleted, such as coal, oil, and natural gas. Here are some key differences between "
+            "renewable and non-renewable energy sources:\n"
+            "1. Availability: Renewable energy sources are virtually inexhaustible, while non-renewable "
+            "energy sources are finite and will eventually run out.\n"
+            "2. Environmental impact: Renewable energy sources have a much lower environmental impact "
+            "than non-renewable sources, which can lead to air and water pollution, greenhouse gas emissions, "
+            "and other negative effects.\n"
+            "3. Cost: Renewable energy sources can be more expensive to initially set up, but they typically "
+            "have lower operational costs than non-renewable sources.\n"
+            "4. Reliability: Renewable energy sources are often more reliable and can be used in more remote "
+            "locations than non-renewable sources.\n"
+            "5. Flexibility: Renewable energy sources are often more flexible and can be adapted to different "
+            "situations and needs, while non-renewable sources are more rigid and inflexible.\n"
+            "6. Sustainability: Renewable energy sources are more sustainable over the long term, while "
+            "non-renewable sources are not, and their depletion can lead to economic and social instability.\n")
+    ),
+    offset=2,
+    sep_style=SeparatorStyle.SINGLE,
+    sep="###",
+)
+
+conv_vicuna_v1 = Conversation(
+    system="A chat between a curious user and an artificial intelligence assistant. "
+    "The assistant gives helpful, detailed, and polite answers to the user's questions.",
+    roles=("USER", "ASSISTANT"),
+    version="v1",
+    messages=(),
+    offset=0,
+    sep_style=SeparatorStyle.TWO,
+    sep=" ",
+    sep2="</s>",
+)
+
+conv_phi = Conversation(
+    system="A chat between a curious user and an artificial intelligence assistant. "
+    "The assistant gives helpful, detailed, and polite answers to the user's questions.",
+    roles=("USER", "ASSISTANT"),
+    version="phi",
+    messages=(),
+    offset=0,
+    sep_style=SeparatorStyle.PHI,
+    sep=" ",
+    sep2="<|endoftext|>",
+)
+
+conv_llama_2 = Conversation(
+    system="""You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe.  Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature.
+
+If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information.""",
+    roles=("USER", "ASSISTANT"),
+    version="llama_v2",
+    messages=(),
+    offset=0,
+    sep_style=SeparatorStyle.LLAMA_2,
+    sep="<s>",
+    sep2="</s>",
+)
+
+conv_llava_llama_2 = Conversation(
+    system="You are a helpful language and vision assistant. "
+           "You are able to understand the visual content that the user provides, "
+           "and assist the user with a variety of tasks using natural language.",
+    roles=("USER", "ASSISTANT"),
+    version="llama_v2",
+    messages=(),
+    offset=0,
+    sep_style=SeparatorStyle.LLAMA_2,
+    sep="<s>",
+    sep2="</s>",
+)
+
+conv_mpt = Conversation(
+    system="""<|im_start|>system
+A conversation between a user and an LLM-based AI assistant. The assistant gives helpful and honest answers.""",
+    roles=("<|im_start|>user\n", "<|im_start|>assistant\n"),
+    version="mpt",
+    messages=(),
+    offset=0,
+    sep_style=SeparatorStyle.MPT,
+    sep="<|im_end|>",
+)
+
+conv_llava_plain = Conversation(
+    system="",
+    roles=("", ""),
+    messages=(
+    ),
+    offset=0,
+    sep_style=SeparatorStyle.PLAIN,
+    sep="\n",
+)
+
+conv_llava_v0 = Conversation(
+    system="A chat between a curious human and an artificial intelligence assistant. "
+           "The assistant gives helpful, detailed, and polite answers to the human's questions.",
+    roles=("Human", "Assistant"),
+    messages=(
+    ),
+    offset=0,
+    sep_style=SeparatorStyle.SINGLE,
+    sep="###",
+)
+
+conv_llava_v0_mmtag = Conversation(
+    system="A chat between a curious user and an artificial intelligence assistant. "
+           "The assistant is able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language."
+           "The visual content will be provided with the following format: <Image>visual content</Image>.",
+    roles=("Human", "Assistant"),
+    messages=(
+    ),
+    offset=0,
+    sep_style=SeparatorStyle.SINGLE,
+    sep="###",
+    version="v0_mmtag",
+)
+
+conv_llava_v1 = Conversation(
+    system="A chat between a curious human and an artificial intelligence assistant. "
+           "The assistant gives helpful, detailed, and polite answers to the human's questions.",
+    roles=("USER", "ASSISTANT"),
+    version="v1",
+    messages=(),
+    offset=0,
+    sep_style=SeparatorStyle.TWO,
+    sep=" ",
+    sep2="</s>",
+)
+
+conv_llava_v1_mmtag = Conversation(
+    system="A chat between a curious user and an artificial intelligence assistant. "
+           "The assistant is able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language."
+           "The visual content will be provided with the following format: <Image>visual content</Image>.",
+    roles=("USER", "ASSISTANT"),
+    messages=(),
+    offset=0,
+    sep_style=SeparatorStyle.TWO,
+    sep=" ",
+    sep2="</s>",
+    version="v1_mmtag",
+)
+
+default_conversation = conv_vicuna_v1
+conv_templates = {
+    "default": conv_vicuna_v0,
+    "v0": conv_vicuna_v0,
+    "v1": conv_vicuna_v1,
+    "vicuna_v1": conv_vicuna_v1,
+    "llama_2": conv_llama_2,
+
+    "plain": conv_llava_plain,
+    "v0_plain": conv_llava_plain,
+    "llava_v0": conv_llava_v0,
+    "v0_mmtag": conv_llava_v0_mmtag,
+    "llava_v1": conv_llava_v1,
+    "v1_mmtag": conv_llava_v1_mmtag,
+    "llava_llama_2": conv_llava_llama_2,
+
+    "mpt": conv_mpt,
+    'phi': conv_phi,
+}
+
+
+if __name__ == "__main__":
+    print(default_conversation.get_prompt())
diff --git a/memory/generation_config.json b/memory/generation_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..870b133592a2d13f3b405199c262e58092fa6ef2
--- /dev/null
+++ b/memory/generation_config.json
@@ -0,0 +1,14 @@
+{
+  "bos_token_id": 151643,
+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151643
+  ],
+  "pad_token_id": 151643,
+  "repetition_penalty": 1.1,
+  "temperature": 0.7,
+  "top_k": 20,
+  "top_p": 0.8,
+  "transformers_version": "4.41.2"
+}
diff --git a/memory/grounding.sh b/memory/grounding.sh
new file mode 100644
index 0000000000000000000000000000000000000000..7f332a4e6f2d9c21417ccea94a49905e99ef07e8
--- /dev/null
+++ b/memory/grounding.sh
@@ -0,0 +1,3 @@
+python -m model_grounding_ego \
+        --model-path /mnt/hwfile/mllm/qianrui/Long-Grounding-qwen \
+        --conv-mode v1
\ No newline at end of file
diff --git a/memory/grounding_qwen.py b/memory/grounding_qwen.py
new file mode 100644
index 0000000000000000000000000000000000000000..d450c97260d1024fa5a8faa7db78712ce553cc7c
--- /dev/null
+++ b/memory/grounding_qwen.py
@@ -0,0 +1,207 @@
+#    Copyright 2023 Haotian Liu
+#
+#    Licensed under the Apache License, Version 2.0 (the "License");
+#    you may not use this file except in compliance with the License.
+#    You may obtain a copy of the License at
+#
+#        http://www.apache.org/licenses/LICENSE-2.0
+#
+#    Unless required by applicable law or agreed to in writing, software
+#    distributed under the License is distributed on an "AS IS" BASIS,
+#    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#    See the License for the specific language governing permissions and
+#    limitations under the License.
+
+
+from typing import List, Optional, Tuple, Union
+
+import torch
+import torch.nn as nn
+
+from transformers import AutoConfig, AutoModelForCausalLM
+
+from modeling_qwen import *
+from configuration_qwen import Qwen2Config
+
+from transformers.modeling_outputs import CausalLMOutputWithPast
+
+from llava_arch import LlavaMetaModel, LlavaMetaForCausalLM
+
+
+class GroundQwenConfig(Qwen2Config):
+    model_type = "ground_qwen"
+
+
+class LlavaQwenModel(LlavaMetaModel, Qwen2Model):
+    config_class = GroundQwenConfig
+
+    def __init__(self, config: Qwen2Config):
+        super(LlavaQwenModel, self).__init__(config)
+
+class GroundQwenForCausalLM(Qwen2ForCausalLM, LlavaMetaForCausalLM):
+    config_class = GroundQwenConfig
+    supports_gradient_checkpointing = True
+
+    def __init__(self, config):
+        super(Qwen2ForCausalLM, self).__init__(config)
+        self.model = LlavaQwenModel(config)
+        self.lm_head = nn.Linear(config.hidden_size, config.vocab_size, bias=False)
+        self.vocab_size = config.vocab_size
+
+        # Initialize weights and apply final processing
+        self.post_init()
+    
+    def get_model(self):
+        return self.model
+
+    def _set_gradient_checkpointing(self, module, value=False):
+        if isinstance(module, LlavaQwenModel):
+            module.gradient_checkpointing = value
+
+    def forward_grounding(
+        self,
+        input_ids: torch.LongTensor = None,
+        attention_mask: Optional[torch.Tensor] = None,
+        qs_ids: Optional[torch.LongTensor] = None,
+        qs_mask: Optional[torch.Tensor] = None,
+        time_labels: Optional[torch.FloatTensor] = None,
+        position_ids: Optional[torch.LongTensor] = None,
+        past_key_values: Optional[List[torch.FloatTensor]] = None,
+        inputs_embeds: Optional[torch.FloatTensor] = None,
+        labels: Optional[torch.LongTensor] = None,
+        use_cache: Optional[bool] = None,
+        output_attentions: Optional[bool] = None,
+        output_hidden_states: Optional[bool] = None,
+        images: Optional[torch.FloatTensor] = None,
+        projector: Optional[torch.LongTensor] = None,
+        select_layer: Optional[int] = None,
+        return_simi: Optional[bool] = False,
+        return_dict: Optional[bool] = None,
+    ) -> torch.FloatTensor:
+    
+        if inputs_embeds is None:
+            (
+                input_ids,
+                position_ids,
+                attention_mask,
+                past_key_values,
+                inputs_embeds,
+                clip_embeds,
+                qs_embeds,
+                qs_mask,
+                labels
+            ) = self.prepare_inputs_labels_for_multimodal(
+                input_ids,
+                position_ids,
+                attention_mask,
+                qs_ids,
+                qs_mask,
+                past_key_values,
+                labels,
+                images,
+                projector
+            )
+        if isinstance(labels, tuple):
+            labels, indicators = labels
+        else:
+            indicators = None
+
+        loss, similarity, global_memory, clip_memory = super().forward_grounding_hm(
+            input_ids=input_ids,
+            attention_mask=attention_mask,
+            position_ids=position_ids,
+            past_key_values=past_key_values,
+            inputs_embeds=inputs_embeds,
+            clip_embeds=torch.stack(clip_embeds, dim=0),
+            qs_embeds=qs_embeds,
+            qs_mask=qs_mask,
+            labels=labels,
+            time_labels=time_labels,
+            indicators=indicators,
+            return_simi=return_simi,
+            select_layer=100,
+            use_cache=use_cache,
+            output_attentions=output_attentions,
+            output_hidden_states=output_hidden_states,
+            return_dict=return_dict
+        )
+        return similarity, global_memory, clip_memory
+
+    def forward(
+        self,
+        input_ids: torch.LongTensor = None,
+        attention_mask: Optional[torch.Tensor] = None,
+        qs_ids: Optional[torch.LongTensor] = None,
+        qs_mask: Optional[torch.Tensor] = None,
+        time_labels: Optional[torch.FloatTensor] = None,
+        position_ids: Optional[torch.LongTensor] = None,
+        past_key_values: Optional[List[torch.FloatTensor]] = None,
+        inputs_embeds: Optional[torch.FloatTensor] = None,
+        labels: Optional[torch.LongTensor] = None,
+        use_cache: Optional[bool] = None,
+        output_attentions: Optional[bool] = None,
+        output_hidden_states: Optional[bool] = None,
+        images: Optional[torch.FloatTensor] = None,
+        projector: Optional[torch.LongTensor] = None,
+        select_layer: Optional[int] = None,
+        return_dict: Optional[bool] = None,
+    ) -> torch.FloatTensor:
+    
+        if inputs_embeds is None:
+            (
+                input_ids,
+                position_ids,
+                attention_mask,
+                past_key_values,
+                inputs_embeds,
+                clip_embeds,
+                qs_embeds,
+                qs_mask,
+                labels
+            ) = self.prepare_inputs_labels_for_multimodal(
+                input_ids,
+                position_ids,
+                attention_mask,
+                qs_ids,
+                qs_mask,
+                past_key_values,
+                labels,
+                images,
+                projector
+            )
+        if isinstance(labels, tuple):
+            labels, indicators = labels
+        else:
+            indicators = None
+
+        loss, similarity = super().forward_grounding_hm(
+            input_ids=input_ids,
+            attention_mask=attention_mask,
+            position_ids=position_ids,
+            past_key_values=past_key_values,
+            inputs_embeds=inputs_embeds,
+            clip_embeds=torch.stack(clip_embeds, dim=0),
+            qs_embeds=qs_embeds,
+            qs_mask=qs_mask,
+            labels=labels,
+            time_labels=time_labels,
+            indicators=indicators,
+            select_layer=100,
+            use_cache=use_cache,
+            output_attentions=output_attentions,
+            output_hidden_states=output_hidden_states,
+            return_dict=return_dict
+        )
+        return CausalLMOutputWithPast(loss=loss, past_key_values=past_key_values)
+
+    def prepare_inputs_for_generation(self, input_ids, past_key_values=None, inputs_embeds=None, indicators=None, **kwargs):
+        images = kwargs.pop("images", None)
+        _inputs = super().prepare_inputs_for_generation(
+            input_ids, past_key_values=past_key_values, inputs_embeds=inputs_embeds, indicators=indicators, **kwargs
+        )
+        if images is not None:
+            _inputs['images'] = images
+        return _inputs
+
+AutoConfig.register("ground_qwen", GroundQwenConfig)
+AutoModelForCausalLM.register(GroundQwenConfig, GroundQwenForCausalLM)
diff --git a/memory/llava_arch.py b/memory/llava_arch.py
new file mode 100644
index 0000000000000000000000000000000000000000..729961ab9548fdccdfe1e82318e66a4a04304c54
--- /dev/null
+++ b/memory/llava_arch.py
@@ -0,0 +1,499 @@
+#    Copyright 2023 Haotian Liu
+#
+#    Licensed under the Apache License, Version 2.0 (the "License");
+#    you may not use this file except in compliance with the License.
+#    You may obtain a copy of the License at
+#
+#        http://www.apache.org/licenses/LICENSE-2.0
+#
+#    Unless required by applicable law or agreed to in writing, software
+#    distributed under the License is distributed on an "AS IS" BASIS,
+#    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#    See the License for the specific language governing permissions and
+#    limitations under the License.
+
+
+from abc import ABC, abstractmethod
+
+import numpy as np
+import torch
+import torch.nn as nn
+
+from builder_encoder import build_vision_tower
+from builder_projector import build_vision_projector
+
+from constants import IGNORE_INDEX, IMAGE_TOKEN_INDEX, DEFAULT_IMAGE_PATCH_TOKEN, DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN
+
+
+class LlavaMetaModel:
+
+    def __init__(self, config):
+        super(LlavaMetaModel, self).__init__(config)
+
+        if hasattr(config, "mm_vision_tower"):
+            self.vision_tower = build_vision_tower(config, delay_load=False)
+            self.mm_projector = build_vision_projector(config)
+
+    def get_vision_tower(self):
+        vision_tower = getattr(self, 'vision_tower', None)
+        if type(vision_tower) is list:
+            vision_tower = vision_tower[0]
+        return vision_tower
+
+    def initialize_vision_modules(self, model_args, fsdp=None):
+        vision_tower = model_args.vision_tower
+        mm_vision_select_layer = model_args.mm_vision_select_layer
+        mm_vision_select_feature = model_args.mm_vision_select_feature
+        pretrain_mm_mlp_adapter = model_args.pretrain_mm_mlp_adapter
+
+        self.config.mm_vision_tower = vision_tower
+
+        if self.get_vision_tower() is None:
+            vision_tower = build_vision_tower(model_args)
+
+            if fsdp is not None and len(fsdp) > 0:
+                self.vision_tower = [vision_tower]
+            else:
+                self.vision_tower = vision_tower
+        else:
+            if fsdp is not None and len(fsdp) > 0:
+                vision_tower = self.vision_tower[0]
+            else:
+                vision_tower = self.vision_tower
+            vision_tower.load_model()
+
+        self.config.use_mm_proj = True
+        self.config.mm_projector_type = getattr(model_args, 'mm_projector_type', 'linear')
+        self.config.mm_hidden_size = vision_tower.hidden_size
+        self.config.mm_vision_select_layer = mm_vision_select_layer
+        self.config.mm_vision_select_feature = mm_vision_select_feature
+
+        if getattr(self, 'mm_projector', None) is None:
+            self.mm_projector = build_vision_projector(self.config)
+        else:
+            # In case it is frozen by LoRA
+            for p in self.mm_projector.parameters():
+                p.requires_grad = True
+
+        if pretrain_mm_mlp_adapter is not None:
+            mm_projector_weights = torch.load(pretrain_mm_mlp_adapter, map_location='cpu')
+            def get_w(weights, keyword):
+                return {k.split(keyword + '.')[1]: v for k, v in weights.items() if keyword in k}
+
+            self.mm_projector = build_vision_projector(self.config)
+            self.mm_projector.load_state_dict(get_w(mm_projector_weights, 'mm_projector'), strict=False)
+
+
+class LlavaMetaForCausalLM(ABC):
+
+    @abstractmethod
+    def get_model(self):
+        pass
+
+    def get_vision_tower(self):
+        return self.get_model().get_vision_tower()
+
+    def encode_images(self, images, base_mode=False):
+        clip_features = self.get_model().get_vision_tower()(images)
+        if not base_mode:
+            clip_features = self.mix_spatial_tokens(clip_features)
+        else:
+            clip_features = self.mix_spatial_tokens(clip_features)
+        image_features = self.get_model().mm_projector(clip_features)
+        return clip_features, image_features
+    
+    def extract_images(self, images):
+        image_features_list = []
+        block_size = 16
+        for i in range(0, images.shape[0], block_size):
+            image_features = self.get_model().get_vision_tower()(images[i: i+block_size])
+            image_features_list.append(image_features)
+        image_features = torch.cat(image_features_list, dim=0)
+        assert image_features.shape[0] == images.shape[0]
+        return image_features
+    
+    def project_features(self, features):
+        proj_features = self.get_model().mm_projector(features)
+        return proj_features
+    
+    def mix_spatial_tokens(self, features):
+        # features b n c
+        # output b n//4 4c
+        b, n, c = features.shape
+        h = int(np.sqrt(n))
+        features = features.view(b, h//2, 2, h//2, 2, c).permute(0, 1, 3, 2, 4, 5).contiguous()
+        features = features.view(b, n//4, 4*c).contiguous()
+        return features
+
+    def prepare_inputs_labels_for_multimodal(
+        self, input_ids, position_ids, attention_mask, qs_ids, qs_mask, past_key_values, labels, images, projector
+    ):
+        vision_tower = self.get_vision_tower()
+        if hasattr(self.get_model().mm_projector, 'num_slot'):
+            base_mode = False
+            num_slot = self.get_model().mm_projector.num_slot
+        elif hasattr(self.get_model().mm_projector, 'resolution'):
+            base_mode = False
+            pool_num = self.get_model().mm_projector.pool_num
+            resolution = self.get_model().mm_projector.resolution + pool_num
+        else:
+            base_mode = True
+        
+        if vision_tower is None or images is None or input_ids.shape[1] == 1:
+            if isinstance(past_key_values, tuple) and vision_tower is not None and images is not None and input_ids.shape[1] == 1:
+                target_shape = past_key_values[-1][-1].shape[-2] + 1
+                attention_mask = torch.cat((attention_mask, torch.ones(
+                    (attention_mask.shape[0], target_shape - attention_mask.shape[1]),
+                    dtype=attention_mask.dtype,
+                    device=attention_mask.device
+                )), dim=1)
+                position_ids = torch.sum(attention_mask, dim=1).unsqueeze(-1) - 1
+            elif past_key_values is not None and past_key_values.seqlen_offset>0:
+                target_shape = past_key_values.seqlen_offset + 1
+                attention_mask = torch.cat((attention_mask, torch.ones(
+                    (attention_mask.shape[0], target_shape - attention_mask.shape[1]),
+                    dtype=attention_mask.dtype,
+                    device=attention_mask.device
+                )), dim=1)
+                position_ids = torch.sum(attention_mask, dim=1).unsqueeze(-1) - 1
+            return input_ids, position_ids, attention_mask, past_key_values, None, None, None, None, labels
+
+        ''' using pre-extraced video features
+        if type(images) is list:
+            concat_images = []
+            concat_features = []
+            modality_indicators = []
+            for image, projector_type in zip(images, projector):
+                if image.ndim == 2: # pre-extracted feature
+                    concat_features.append(image)
+                    modality_indicators.append(2)
+                elif image.ndim == 3: # single image
+                    concat_images.append(image.unsqueeze(0))
+                    modality_indicators.append(1)
+                elif image.ndim == 4: # multiple frames
+                    concat_images.append(image)
+                    modality_indicators.append(2)
+            concat_images = torch.cat(concat_images, dim=0)
+            concat_features = torch.stack(concat_features, dim=0)
+            concat_images = self.extract_images(concat_images)
+            concat_images, concat_features = self.project_features([concat_images, concat_features])
+            # concat_combine = torch.cat([concat_images.reshape(-1, concat_images.shape[-1]), concat_features.reshape(-1, concat_features.shape[-1])], dim=0)
+            # concat_combine = self.project_features(concat_combine)
+            # concat_images = concat_combine[:concat_images.shape[0]*concat_images.shape[1]].contiguous().view(*concat_images.shape[:2], -1)
+            # concat_features = concat_combine[concat_images.shape[0]*concat_images.shape[1]:].contiguous().view(*concat_features.shape[:2], -1)
+            image_features = []
+            image_index = 0
+            feature_index = 0
+            for image in images:
+                if image.ndim == 2:
+                    image_features.append(concat_features[feature_index])
+                    feature_index += 1
+                elif image.ndim == 3:
+                    image_features.append(concat_images[image_index])
+                    image_index += 1
+                elif image.ndim == 4:
+                    image_features.append(concat_images[image_index: image_index+image.shape[0]].flatten(0, 1))
+                    image_index += image.shape[0]
+            image_features = [x.to(self.device) for x in image_features]
+        '''
+
+        if qs_ids is not None:
+            qs_embeds = self.get_model().embed_tokens(qs_ids)
+        else:
+            qs_embeds = None
+
+        assert len(images) == len(input_ids)
+        if type(images) is list:
+            concat_images = []
+            concat_videos = []
+            modality_indicators = []
+            for image in images:
+                if image.ndim == 3: # single image
+                    concat_images.append(image.unsqueeze(0))
+                    modality_indicators.append(1)
+                elif image.ndim == 4: # multiple frames
+                    concat_videos.append(image)
+                    modality_indicators.append(2)
+            concat_images = torch.cat(concat_images, dim=0) # n c h w
+            concat_videos = torch.stack(concat_videos, dim=0) # n t c h w
+            mix_image_video = torch.cat([concat_images, concat_videos.view(-1, *concat_videos.shape[2:])], dim=0) # m c h w
+            mix_image_video = self.extract_images(mix_image_video) # m k c
+            if not base_mode:
+                mix_image_video = self.mix_spatial_tokens(mix_image_video)
+                concat_images = mix_image_video[:concat_images.shape[0]].contiguous() # n k c
+                concat_videos = mix_image_video[concat_images.shape[0]:].contiguous().view(
+                    concat_videos.shape[0], concat_videos.shape[1]*mix_image_video.shape[1], mix_image_video.shape[2]) # n, tk, c
+            else:
+                mix_image_video = self.mix_spatial_tokens(mix_image_video)
+                concat_images = mix_image_video[:concat_images.shape[0]].contiguous() # n k c
+                concat_videos = mix_image_video[concat_images.shape[0]:].contiguous().view(
+                    concat_videos.shape[0], concat_videos.shape[1], mix_image_video.shape[1], mix_image_video.shape[2]) # n, t, k, c
+            clip_features = []
+            image_index = 0
+            video_index = 0
+            for image in images:
+                if image.ndim == 3:
+                    clip_features.append(concat_images[image_index])
+                    image_index += 1
+                elif image.ndim == 4:
+                    clip_features.append(concat_videos[video_index])
+                    video_index += 1
+            clip_features = [x.to(self.device) for x in clip_features]
+
+            concat_images, concat_videos = self.project_features([concat_images, concat_videos])
+            image_features = []
+            image_index = 0
+            video_index = 0
+            for image in images:
+                if image.ndim == 3:
+                    image_features.append(concat_images[image_index])
+                    image_index += 1
+                elif image.ndim == 4:
+                    image_features.append(concat_videos[video_index])
+                    video_index += 1
+            image_features = [x.to(self.device) for x in image_features]
+        elif images.ndim == 5:
+            modality_indicators = [2 for _ in range(images.shape[0])]
+            concat_images = images.view(-1, *images.shape[2:]) # nt c h w
+            image_features = self.extract_images(concat_images)
+
+            # image_features = image_features.view(images.shape[0], images.shape[1], image_features.shape[1], image_features.shape[2]) # n t k c
+            # time_token = torch.mean(image_features, dim=2) # n t c
+            # spatial_token = torch.mean(image_features, dim=1) # n k c
+            # token = torch.cat([time_token, spatial_token], dim=1)
+            # output = self.project_features(token) # n t+k c
+            # image_features = [x.to(self.device) for x in output]
+            
+            if not base_mode:
+                image_features = self.mix_spatial_tokens(image_features) # nt k c
+                image_features = image_features.view(images.shape[0], images.shape[1]*image_features.shape[1], image_features.shape[2]) # n tk c
+            else:
+                image_features = self.mix_spatial_tokens(image_features) # nt k c
+                image_features = image_features.view(images.shape[0], images.shape[1], image_features.shape[1], image_features.shape[2]) # n t k c
+            clip_features = [x.to(self.device) for x in image_features]
+            image_features = self.project_features(image_features)
+            image_features = [x.to(self.device) for x in image_features]
+        elif images.ndim == 3:
+            modality_indicators = [2 for _ in range(images.shape[0])]
+            image_features = self.project_features(images).to(self.device)
+        else:
+            modality_indicators = [1 for _ in range(images.shape[0])]
+            clip_features, image_features = self.encode_images(images, base_mode)
+            clip_features = [x.to(self.device) for x in clip_features]
+            image_features = [x.to(self.device) for x in image_features]
+
+        # TODO: image start / end is not implemented here to support pretraining.
+        if getattr(self.config, 'tune_mm_mlp_adapter', False) and getattr(self.config, 'mm_use_im_start_end', False):
+            raise NotImplementedError
+
+        # Let's just add dummy tensors if they do not exist,
+        # it is a headache to deal with None all the time.
+        # But it is not ideal, and if you have a better idea,
+        # please open an issue / submit a PR, thanks.
+        _labels = labels
+        _position_ids = position_ids
+        _attention_mask = attention_mask
+        if attention_mask is None:
+            attention_mask = torch.ones_like(input_ids, dtype=torch.bool)
+        else:
+            attention_mask = attention_mask.bool()
+        if position_ids is None:
+            position_ids = torch.arange(0, input_ids.shape[1], dtype=torch.long, device=input_ids.device)
+        if labels is None:
+            labels = torch.full_like(input_ids, IGNORE_INDEX)
+        indicators = torch.zeros_like(input_ids)
+
+        # remove the padding using attention_mask -- TODO: double check
+        input_ids = [cur_input_ids[cur_attention_mask] for cur_input_ids, cur_attention_mask in zip(input_ids, attention_mask)]
+        labels = [cur_labels[cur_attention_mask] for cur_labels, cur_attention_mask in zip(labels, attention_mask)]
+        indicators = [cur_indicators[cur_attention_mask] for cur_indicators, cur_attention_mask in zip(indicators, attention_mask)]
+
+        new_input_embeds = []
+        new_labels = []
+        new_indicators = []
+        cur_image_idx = 0
+        for batch_idx, cur_input_ids in enumerate(input_ids):
+            num_images = (cur_input_ids == IMAGE_TOKEN_INDEX).sum()
+            if num_images == 0:
+                cur_image_features = image_features[cur_image_idx]
+                cur_input_embeds_1 = self.get_model().embed_tokens(cur_input_ids)
+                cur_input_embeds = torch.cat([cur_input_embeds_1, cur_image_features[0:0]], dim=0)
+                new_input_embeds.append(cur_input_embeds)
+                new_labels.append(labels[batch_idx])
+                new_indicators.append(indicators[batch_idx])
+                cur_image_idx += 1
+                continue
+
+            image_token_indices = [-1] + torch.where(cur_input_ids == IMAGE_TOKEN_INDEX)[0].tolist() + [cur_input_ids.shape[0]]
+            cur_input_ids_noim = []
+            cur_labels = labels[batch_idx]
+            cur_labels_noim = []
+            cur_indicators = indicators[batch_idx]
+            cur_indicators_noim = []
+            for i in range(len(image_token_indices) - 1):
+                cur_input_ids_noim.append(cur_input_ids[image_token_indices[i]+1:image_token_indices[i+1]])
+                cur_labels_noim.append(cur_labels[image_token_indices[i]+1:image_token_indices[i+1]])
+                cur_indicators_noim.append(cur_indicators[image_token_indices[i]+1:image_token_indices[i+1]])
+            split_sizes = [x.shape[0] for x in cur_labels_noim]
+            cur_input_embeds = self.get_model().embed_tokens(torch.cat(cur_input_ids_noim))
+            cur_input_embeds_no_im = torch.split(cur_input_embeds, split_sizes, dim=0)
+            cur_new_input_embeds = []
+            cur_new_labels = []
+            cur_new_indicators = []
+
+            if True: # stage 2
+                for i in range(num_images + 1):
+                    cur_new_input_embeds.append(cur_input_embeds_no_im[i])
+                    cur_new_labels.append(cur_labels_noim[i])
+                    cur_new_indicators.append(cur_indicators_noim[i])
+                    if i < num_images:
+                        cur_image_features = image_features[cur_image_idx]
+                        if hasattr(self.get_model().mm_projector, 'resolution'):
+                            assert (cur_image_features.shape[0]-1) % resolution == 0
+                            num_slot = (cur_image_features.shape[0]-1) // resolution * pool_num
+                        cur_image_idx += 1
+                        cur_new_input_embeds.append(cur_image_features)
+                        cur_new_labels.append(torch.full((cur_image_features.shape[0],), IGNORE_INDEX, device=cur_labels.device, dtype=cur_labels.dtype))
+                        tmp = modality_indicators[batch_idx]*torch.ones((cur_image_features.shape[0],), device=cur_indicators.device, dtype=cur_indicators.dtype)
+                        try:
+                            tmp[-num_slot-1: -1] = 100
+                            tmp[-1] = 200
+                        except:
+                            pass
+                        cur_new_indicators.append(tmp)
+                        # cur_new_indicators.append(modality_indicators[batch_idx]*torch.ones((cur_image_features.shape[0],), device=cur_indicators.device, dtype=cur_indicators.dtype))
+                        # cur_new_indicators.append(torch.ones((self.config.n_slot,), device=cur_indicators.device, dtype=cur_indicators.dtype)+1)
+
+            if False: # stage 1
+                for i in range(num_images + 1):
+                    cur_new_input_embeds.append(cur_input_embeds_no_im[i])
+                    cur_new_labels.append(cur_labels_noim[i])
+                    cur_new_indicators.append(cur_indicators_noim[i])
+                    if i < num_images:
+                        cur_image_features = image_features[cur_image_idx]
+                        if hasattr(self.get_model().mm_projector, 'resolution'):
+                            assert cur_image_features.shape[0] % resolution == 0
+                            num_slot = cur_image_features.shape[0] // resolution * pool_num
+                        cur_image_idx += 1
+                        cur_new_input_embeds.append(cur_image_features)
+                        cur_new_labels.append(torch.full((cur_image_features.shape[0],), IGNORE_INDEX, device=cur_labels.device, dtype=cur_labels.dtype))
+                        tmp = modality_indicators[batch_idx]*torch.ones((cur_image_features.shape[0],), device=cur_indicators.device, dtype=cur_indicators.dtype)
+                        tmp[-num_slot:] = 100
+                        cur_new_indicators.append(tmp)
+                        # cur_new_indicators.append(modality_indicators[batch_idx]*torch.ones((cur_image_features.shape[0],), device=cur_indicators.device, dtype=cur_indicators.dtype))
+                        # cur_new_indicators.append(torch.ones((self.config.n_slot,), device=cur_indicators.device, dtype=cur_indicators.dtype)+1)
+
+
+            cur_new_input_embeds = torch.cat(cur_new_input_embeds)
+            cur_new_labels = torch.cat(cur_new_labels)
+            cur_new_indicators = torch.cat(cur_new_indicators)
+
+            new_input_embeds.append(cur_new_input_embeds)
+            new_labels.append(cur_new_labels)
+            new_indicators.append(cur_new_indicators)
+
+        # Truncate sequences to max length as image embeddings can make the sequence longer
+        tokenizer_model_max_length = getattr(self.config, 'tokenizer_model_max_length', None)
+        if tokenizer_model_max_length is not None:
+            new_input_embeds = [x[:tokenizer_model_max_length] for x in new_input_embeds]
+            new_labels = [x[:tokenizer_model_max_length] for x in new_labels]
+            new_indicators = [x[:tokenizer_model_max_length] for x in new_indicators] 
+
+        # Combine them
+        max_len = max(x.shape[0] for x in new_input_embeds)
+        batch_size = len(new_input_embeds)
+
+        new_input_embeds_padded = []
+        new_labels_padded = torch.full((batch_size, max_len), IGNORE_INDEX, dtype=new_labels[0].dtype, device=new_labels[0].device)
+        new_indicators_padded = torch.zeros((batch_size, max_len), dtype=new_indicators[0].dtype, device=new_indicators[0].device)
+        attention_mask = torch.zeros((batch_size, max_len), dtype=attention_mask.dtype, device=attention_mask.device)
+        position_ids = torch.zeros((batch_size, max_len), dtype=position_ids.dtype, device=position_ids.device)
+
+        for i, (cur_new_embed, cur_new_labels, cur_new_indicators) in enumerate(zip(new_input_embeds, new_labels, new_indicators)):
+            cur_len = cur_new_embed.shape[0]
+            if getattr(self.config, 'tokenizer_padding_side', 'right') == "left":
+                new_input_embeds_padded.append(torch.cat((
+                    torch.zeros((max_len - cur_len, cur_new_embed.shape[1]), dtype=cur_new_embed.dtype, device=cur_new_embed.device),
+                    cur_new_embed
+                ), dim=0))
+                if cur_len > 0:
+                    new_labels_padded[i, -cur_len:] = cur_new_labels
+                    new_indicators_padded[i, -cur_len:] = cur_new_indicators
+                    attention_mask[i, -cur_len:] = True
+                    position_ids[i, -cur_len:] = torch.arange(0, cur_len, dtype=position_ids.dtype, device=position_ids.device)
+            else:
+                new_input_embeds_padded.append(torch.cat((
+                    cur_new_embed,
+                    torch.zeros((max_len - cur_len, cur_new_embed.shape[1]), dtype=cur_new_embed.dtype, device=cur_new_embed.device)
+                ), dim=0))
+                if cur_len > 0:
+                    new_labels_padded[i, :cur_len] = cur_new_labels
+                    new_indicators_padded[i, :cur_len] = cur_new_indicators
+                    attention_mask[i, :cur_len] = True
+                    position_ids[i, :cur_len] = torch.arange(0, cur_len, dtype=position_ids.dtype, device=position_ids.device)
+
+        new_input_embeds = torch.stack(new_input_embeds_padded, dim=0)
+        new_indicators = new_indicators_padded
+        # print('finish preparing labels multimodal')
+
+        if _labels is None:
+            new_labels = None
+        else:
+            new_labels = new_labels_padded
+
+        if _attention_mask is None:
+            attention_mask = None
+        else:
+            attention_mask = attention_mask.to(dtype=_attention_mask.dtype)
+
+        if _position_ids is None:
+            position_ids = None
+
+        if base_mode:
+            return None, position_ids, attention_mask, past_key_values, new_input_embeds, new_labels
+        else:
+            return None, position_ids, attention_mask, past_key_values, new_input_embeds, clip_features, qs_embeds, qs_mask, (new_labels, new_indicators)
+
+    def initialize_vision_tokenizer(self, model_args, tokenizer):
+        if model_args.mm_use_im_patch_token:
+            tokenizer.add_tokens([DEFAULT_IMAGE_PATCH_TOKEN], special_tokens=True)
+            self.resize_token_embeddings(len(tokenizer))
+
+        if model_args.mm_use_im_start_end:
+            num_new_tokens = tokenizer.add_tokens([DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN], special_tokens=True)
+            self.resize_token_embeddings(len(tokenizer))
+
+            if num_new_tokens > 0:
+                input_embeddings = self.get_input_embeddings().weight.data
+                output_embeddings = self.get_output_embeddings().weight.data
+
+                input_embeddings_avg = input_embeddings[:-num_new_tokens].mean(
+                    dim=0, keepdim=True)
+                output_embeddings_avg = output_embeddings[:-num_new_tokens].mean(
+                    dim=0, keepdim=True)
+
+                input_embeddings[-num_new_tokens:] = input_embeddings_avg
+                output_embeddings[-num_new_tokens:] = output_embeddings_avg
+
+            if model_args.tune_mm_mlp_adapter:
+                for p in self.get_input_embeddings().parameters():
+                    p.requires_grad = True
+                for p in self.get_output_embeddings().parameters():
+                    p.requires_grad = False
+
+            if model_args.pretrain_mm_mlp_adapter:
+                mm_projector_weights = torch.load(model_args.pretrain_mm_mlp_adapter, map_location='cpu')
+                embed_tokens_weight = mm_projector_weights['model.embed_tokens.weight']
+                assert num_new_tokens == 2
+                if input_embeddings.shape == embed_tokens_weight.shape:
+                    input_embeddings[-num_new_tokens:] = embed_tokens_weight[-num_new_tokens:]
+                elif embed_tokens_weight.shape[0] == num_new_tokens:
+                    input_embeddings[-num_new_tokens:] = embed_tokens_weight
+                else:
+                    raise ValueError(f"Unexpected embed_tokens_weight shape. Pretrained: {embed_tokens_weight.shape}. Current: {input_embeddings.shape}. Numer of new tokens: {num_new_tokens}.")
+        elif model_args.mm_use_im_patch_token:
+            if model_args.tune_mm_mlp_adapter:
+                for p in self.get_input_embeddings().parameters():
+                    p.requires_grad = False
+                for p in self.get_output_embeddings().parameters():
+                    p.requires_grad = False
diff --git a/memory/merges.txt b/memory/merges.txt
new file mode 100644
index 0000000000000000000000000000000000000000..31349551d90c7606f325fe0f11bbb8bd5fa0d7c7
--- /dev/null
+++ b/memory/merges.txt
@@ -0,0 +1,151388 @@
+#version: 0.2
+Ġ Ġ
+ĠĠ ĠĠ
+i n
+Ġ t
+ĠĠĠĠ ĠĠĠĠ
+e r
+ĠĠ Ġ
+o n
+Ġ a
+r e
+a t
+s t
+e n
+o r
+Ġt h
+Ċ Ċ
+Ġ c
+l e
+Ġ s
+i t
+a n
+a r
+a l
+Ġth e
+; Ċ
+Ġ p
+Ġ f
+o u
+Ġ =
+i s
+ĠĠĠĠ ĠĠĠ
+in g
+e s
+Ġ w
+i on
+e d
+i c
+Ġ b
+Ġ d
+e t
+Ġ m
+Ġ o
+ĉ ĉ
+r o
+a s
+e l
+c t
+n d
+Ġ in
+Ġ h
+en t
+i d
+Ġ n
+a m
+ĠĠĠĠĠĠĠĠ ĠĠĠ
+Ġt o
+Ġ re
+- -
+Ġ {
+Ġo f
+o m
+) ;Ċ
+i m
+č Ċ
+Ġ (
+i l
+/ /
+Ġa nd
+u r
+s e
+Ġ l
+e x
+Ġ S
+a d
+Ġ "
+c h
+u t
+i f
+* *
+Ġ }
+e m
+o l
+ĠĠĠĠĠĠĠĠ ĠĠĠĠĠĠĠĠ
+t h
+) Ċ
+Ġ{ Ċ
+Ġ g
+i g
+i v
+, Ċ
+c e
+o d
+Ġ v
+at e
+Ġ T
+a g
+a y
+Ġ *
+o t
+u s
+Ġ C
+Ġ st
+Ġ I
+u n
+u l
+u e
+Ġ A
+o w
+Ġ '
+e w
+Ġ <
+at ion
+( )
+Ġf or
+a b
+or t
+u m
+am e
+Ġ is
+p e
+t r
+c k
+â Ģ
+Ġ y
+i st
+-- --
+. ĊĊ
+h e
+Ġ e
+l o
+Ġ M
+Ġb e
+er s
+Ġ on
+Ġc on
+a p
+u b
+Ġ P
+ĠĠĠĠĠĠĠĠ ĠĠĠĠĠĠĠ
+as s
+in t
+> Ċ
+l y
+ur n
+Ġ $
+; ĊĊ
+a v
+p ort
+i r
+- >
+n t
+ct ion
+en d
+Ġd e
+it h
+ou t
+t urn
+ou r
+ĠĠĠĠ Ġ
+l ic
+re s
+p t
+= =
+Ġth is
+Ġw h
+Ġ if
+Ġ D
+v er
+ag e
+Ġ B
+h t
+ex t
+= "
+Ġth at
+** **
+Ġ R
+Ġ it
+es s
+Ġ F
+Ġ r
+o s
+an d
+Ġa s
+e ct
+k e
+ro m
+Ġ //
+c on
+Ġ L
+( "
+q u
+l ass
+Ġw ith
+i z
+d e
+Ġ N
+Ġa l
+o p
+u p
+g et
+Ġ} Ċ
+i le
+Ġa n
+at a
+o re
+r i
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+; čĊ
+ĉĉ ĉĉ
+t er
+a in
+Ġ W
+Ġ E
+Ġc om
+Ġre turn
+ar t
+Ġ H
+a ck
+im port
+ub lic
+Ġ or
+e st
+m ent
+Ġ G
+ab le
+Ġ -
+in e
+il l
+in d
+er e
+: :
+it y
+Ġ +
+Ġt r
+el f
+ig ht
+( '
+or m
+ul t
+st r
+. .
+" ,
+Ġy ou
+y pe
+p l
+Ġn ew
+Ġ j
+ĠĠĠĠĠĠĠĠ ĠĠĠĠĠĠĠĠĠĠĠ
+Ġf rom
+Ġ ex
+Ġ O
+l d
+Ġ [
+o c
+: Ċ
+Ġs e
+Ġ le
+---- ----
+. s
+{ Ċ
+' ,
+an t
+Ġa t
+as e
+. c
+Ġc h
+< /
+av e
+an g
+Ġa re
+Ġin t
+âĢ Ļ
+_ t
+er t
+i al
+a ct
+} Ċ
+iv e
+od e
+o st
+Ġc lass
+Ġn ot
+o g
+or d
+al ue
+al l
+f f
+( );Ċ
+on t
+im e
+a re
+Ġ U
+Ġp r
+Ġ :
+i es
+iz e
+u re
+Ġb y
+i re
+Ġ} ĊĊ
+. p
+Ġs h
+ic e
+a st
+pt ion
+tr ing
+o k
+_ _
+c l
+# #
+Ġh e
+ar d
+) .
+Ġ @
+i ew
+ĉĉ ĉ
+Ġw as
+i p
+th is
+Ġ u
+ĠT he
+id e
+a ce
+i b
+a c
+r ou
+Ġw e
+j ect
+Ġp ublic
+a k
+v e
+at h
+o id
+Ġ= >
+u st
+q ue
+Ġre s
+) )
+' s
+Ġ k
+an s
+y st
+un ction
+**** ****
+Ġ i
+Ġ us
+p p
+on e
+a il
+== ==
+n ame
+Ġst r
+Ġ /
+Ġ &
+a ch
+d iv
+yst em
+el l
+Ġh ave
+er r
+ou ld
+ul l
+p on
+Ġ J
+_ p
+Ġ= =
+ig n
+S t
+. Ċ
+Ġp l
+) ;ĊĊ
+f orm
+p ut
+ou nt
+} ĊĊ
+d d
+it e
+Ġg et
+r r
+om e
+Ġ âĢ
+ar am
+c c
+Ġ* /
+E R
+I n
+le s
+_ s
+on g
+i e
+Ġc an
+Ġ V
+er v
+p r
+Ġ un
+ro w
+b er
+Ġd o
+l l
+Ġ el
+Ġs elf
+at ed
+ar y
+Ġ .
+' ]
+u d
+Ġ en
+ĠT h
+ĠĠĠĠĠĠĠĠĠĠĠĠĠĠĠĠ ĠĠĠĠĠĠĠ
+t e
+_ c
+u ct
+Ġa b
+or k
+. get
+Ġ #
+a w
+res s
+o b
+N ame
+ap p
+[ '
+Ġal l
+or y
+it ion
+an ce
+e ar
+Ġcon t
+v ent
+i a
+Ġw ill
+I N
+ĠĠĠĠĠĠĠĠ Ġ
+re turn
+Ġ< /
+d ata
+) ĊĊ
+R e
+p le
+il d
+th er
+Ġy our
+" Ċ
+( $
+Ġ out
+) ,
+Ġh as
+S tring
+s o
+Ġ up
+a x
+Ġde f
+Ġb o
+g e
+al se
+O N
+p er
+ic h
+Ġb ut
+Ġ Ċ
+Ġ _
+_ m
+ad d
+que st
+od el
+s elf
+er y
+f t
+en s
+// //
+a ke
+. C
+Ġg o
+Ġf unction
+Ġ K
+iv ate
+Ġ im
+Ġcon st
+. t
+Ġ*/ Ċ
+) ;čĊ
+Ġv oid
+Ġs et
+ĠS ystem
+c ri
+( )Ċ
+l i
+ĉ if
+. m
+al ly
+s et
+e p
+âĢĻ s
+b o
+de f
+' ,Ċ
+Ġm e
+Ġ !
+at ch
+" >
+" ,Ċ
+e c
+ĠI n
+p h
+Ġ |
+_ f
+Ġv ar
+en ce
+I d
+re e
+in k
+le ct
+u g
+et h
+Ġel se
+-------- --------
+con t
+Ġs o
+at ic
+Ġl o
+p ro
+t on
+s s
+ow n
+ab el
+o int
+ou s
+el d
+S T
+T he
+ĠĠĠĠĠĠĠĠĠĠĠĠĠĠĠĠ ĠĠĠĠĠĠĠĠĠĠĠĠĠĠĠĠ
+R E
+" :
+ol or
+t p
+e g
+ke y
+u de
+ĠS t
+ou nd
+Ġa r
+" );Ċ
+en er
+s er
+b ject
+ess age
+f er
+Ġm ore
+ation s
+ent s
+Ġh is
+Ġthe y
+. S
+Ġ Y
+u se
+n e
+is h
+ol d
+_ d
+i o
+i eld
+Ġp er
+C ont
+ing s
+## ##
+Ġd ata
+Ġs a
+e f
+f o
+Ġon e
+en g
+Ġd is
+A T
+Ġn ame
+Ġtr ue
+v al
+le d
+. f
+Ġn e
+Ġ end
+. T
+c re
+ar k
+lo g
+E x
+err or
+_ id
+ur re
+ang e
+Ġn ull
+rr ay
+Ġm y
+p an
+ic t
+at or
+V iew
+L ist
+ĉ return
+âĢ Ŀ
+Ġp re
+Ġ x
+cl ude
+ar g
+o v
+. h
+Ġ >
+Ġthe ir
+' )
+ir st
+ic k
+g h
+L E
+O R
+Ġpr ivate
+t em
+čĊ čĊ
+us er
+Ġ )
+c om
+. A
+" ;Ċ
+Ġ id
+re ad
+Ġwh o
+_ b
+" >Ċ
+Ġt ime
+Ġm an
+r y
+==== ====
+rou p
+ro p
+p ublic
+v el
+um ber
+b le
+Ġwh ich
+******** ********
+Ġan y
+Ġf alse
+w e
+Ġv alue
+Ġl i
+" )
+nd er
+g r
+Ġn o
+p aram
+f ig
+.c om
+Ġa pp
+_ l
+ion s
+. D
+ĠC h
+Ġab out
+Ġa dd
+Ġs u
+Ġstr ing
+I D
+Ġo ver
+str ing
+. l
+our ce
+_ C
+] Ċ
+Ġ qu
+ĠS tring
+c a
+S E
+Ġ ro
+s h
+u al
+T ype
+s on
+n ew
+er n
+Ġa g
+A R
+] ;Ċ
+] .
+Ġ ?
+ic al
+Ġd es
+ut h
+i x
+ay s
+Ġt ype
+' t
+a ult
+Ġin ter
+v ar
+. b
+Ġp art
+. d
+urre nt
+I T
+E N
+en c
+( f
+r a
+v alue
+ch o
+ut ton
+o se
+Ġ! =
+at er
+Ã ©
+re ate
+ol l
+p os
+y le
+n g
+A L
+us ing
+am es
+Ġ{ čĊ
+at es
+el y
+Ġw ork
+Ġ em
+in al
+Ġs p
+Ġwh en
+.s et
+ĠĠĠĠ ĠĠ
+) :Ċ
+t o
+qu ire
+ind ow
+le ment
+pe ct
+as h
+[ i
+Ġu se
+. F
+pe c
+Ġa d
+o ve
+ce ption
+eng th
+in clude
+ad er
+ĠĠĠĠĠĠĠĠĠĠĠĠĠĠĠĠ ĠĠĠĠĠĠĠĠĠĠĠ
+at us
+T h
+it le
+r it
+v oid
+() .
+( Ċ
+Ġof f
+Ġo ther
+Ġ& &
+' ;Ċ
+m s
+Ġbe en
+Ġt e
+m l
+c o
+n c
+erv ice
+Ġ %
+** Ċ
+an n
+ad e
+ĊĊ ĊĊ
+lo ck
+con st
+pon se
+Ġs up
++ +
+d ate
+Ġa cc
+Ġh ad
+Ġb u
+ĠR e
+Ġw ere
+Ġf ile
+Ġw ould
+ĠâĢ ľ
+v en
+is s
+Ġ our
+c lass
+r aw
+Ġy ear
+D ata
+Ġv al
+Ġs ome
+f ter
+y s
+Ġ// /
+rou nd
+v iew
+Ġp e
+Ġth ere
+Ġsa id
+d u
+o f
+l ine
+/ *
+d uct
+Ġh er
+ĠĠĠĠĠĠĠĠ ĠĠĠĠĠ
+R es
+Ġc o
+Ġcom m
+is e
+m in
+ĠĠĠĠ Ċ
+# include
+eth od
+. P
+ut e
+Ġas s
+I nt
+as k
+lo c
+Ġli ke
+od y
+Ġle t
+lo ad
+Ġa m
+ro l
+Ġg r
+y p
+Ġal so
+ĠI t
+ur l
+if ic
+or s
+_ P
+_ n
+ig h
+Ġth an
+C om
+A N
+U L
+at ing
+ĠTh is
+re f
+_ S
+Ġst atic
+ro ll
+Ġj ust
+Ġres ult
+i an
+id th
+Ġthe m
+) );Ċ
+d er
+re ak
+C on
+: //
+u le
+.. .
+ar ch
+em ent
+Ġ< <
+us h
+en se
+ar r
+Ġint o
+c ess
+am p
+i ed
+um ent
+Ġ \
+] ,
+w o
+al s
+Ġwh at
+an c
+V alue
+= '
+ol um
+Ġp os
+ag es
+ay er
+Ġs c
+u es
+" )Ċ
+_ T
+Ġl ist
+( s
+Ġc ase
+C h
+ĉĉĉĉ ĉ
+//// ////
+pon ent
+Ġ z
+Ġk n
+le t
+D E
+re d
+Ġf e
+Ġ} ,Ċ
+Ġ ,
+( t
+Ġf irst
+' );Ċ
+w ord
+Ġ import
+Ġa ct
+Ġch ar
+C T
+ĠT r
+op le
+= {
+ĉ f
+i ent
+c ent
+. j
+le ction
+) )Ċ
+Ġon ly
+Ġpr int
+m er
+. W
+o ck
+Ġ --
+T ext
+Ġo p
+an k
+Ġit s
+Ġb ack
+[ "
+Ġne ed
+Ġc l
+Ġs ub
+Ġl a
+( (
+. "
+O bject
+Ġst art
+f ile
+( self
+n er
+e y
+Ġus er
+Ġ ent
+ĠC om
+it s
+ĠC on
+ou ble
+ow er
+it em
+ver y
+ĠW e
+lic k
+Ġ Q
+ph p
+t tp
+' :
+ic s
+Ġu nder
+Ġ* Ċ
+. L
+) ;
+ic es
+Ġre g
+) čĊ
+ĉ public
+S S
+Ġth en
+re at
+i ous
+. G
+e k
+ire ct
+he ck
+cri pt
+n ing
+ĠU n
+Ġm ay
+ĠW h
+B o
+I tem
+str uct
+. st
+re am
+ib le
+lo at
+Ġor g
+u nd
+s um
+_ in
+.. /
+_ M
+Ġh ow
+r ite
+' Ċ
+T o
+w w
+Ġpe ople
+ind ex
+. n
+ht tp
+( m
+ect or
+Ġin d
+Ġj av
+] ,Ċ
+ĠH e
+_ st
+f ul
+o le
+) {Ċ
+Ġsh ould
+op y
+el p
+i er
+_ name
+ers on
+I ON
+ot e
+Ġt est
+Ġb et
+rr or
+ul ar
+ã Ģ
+Ġ Ð
+b s
+t ing
+Ġm ake
+T r
+Ġa fter
+ar get
+R O
+olum n
+r c
+_ re
+def ine
+Ġr ight
+r ight
+d ay
+Ġl ong
+[ ]
+( p
+t d
+con d
+ĠP ro
+Ġre m
+ption s
+v id
+. g
+Ġ ext
+Ġ __
+' )Ċ
+p ace
+m p
+Ġm in
+st ance
+a ir
+a ction
+w h
+t ype
+ut il
+a it
+< ?
+I C
+t ext
+Ġp h
+Ġf l
+. M
+cc ess
+b r
+f ore
+ers ion
+) ,Ċ
+. re
+ate g
+Ġl oc
+in s
+- s
+tr ib
+ĠI nt
+Ġa rray
+, "
+P ro
+( c
+ess ion
+> ĊĊ
+Ġs he
+" ]
+ap h
+Ġex p
+ert y
+ĠS e
+Ġp ar
+un c
+E T
+Ġre ad
+pr int
+Ġre l
+Ġfor m
+Ġd r
+Ex ception
+in put
+Ġtr ans
+#### ####
+ord er
+B y
+Ġa w
+it ies
+u ff
+pl ay
+. add
+ĠâĢ ĵ
+Ġw ant
+Ġcom p
+ment s
+Ġ| |
+a z
+b e
+Ġn umber
+Ġre quire
+ĠE x
+Ġc ol
+Ġ key
+em ber
+Ġt wo
+Ġs ize
+Ġwh ere
+U T
+res ult
+ĠĠĠĠĠĠĠĠĠĠĠĠĠĠĠĠ ĠĠĠĠĠĠĠĠĠĠĠĠĠĠĠ
+ou gh
+or ld
+o od
+u ch
+at ive
+g er
+are nt
+Ġ/ *
+Ġar g
+Ġwh ile
+( this
+Ġre c
+Ġd if
+St ate
+Ġs pec
+r ide
+_ F
+Ġlo ok
+A M
+il ity
+et er
+âĢĻ t
+ĊĊ Ċ
+ay out
+---------------- ----------------
+ag er
+Ġc ould
+Ġb r
+end s
+u res
+Ġkn ow
+et s
+ĠI f
+ĠS h
+. w
+b ack
+Ġs er
+Ġ+ =
+Ġf r
+() );Ċ
+Ġh and
+I nd
+UL L
+I m
+() ;ĊĊ
+Ġm ost
+Ġtr y
+Ġn ow
+rou gh
+> čĊ
+ack age
+Ġh im
+. _
+if y
+Ġb reak
+Ġ );Ċ
+re n
+# define
+it t
+Ġa p
+ĉ c
+( n
+ĠY ou
+: ĊĊ
+- m
+Ġe very
+ust om
+li ent
+oc ument
+cri ption
+E rror
+- b
+Ð ¾
+] [
+tr ans
+Ġp oint
+Ġst d
+Ġf il
+T ime
+Ġm od
+Ġ ->
+Ġ error
+a h
+Ġt ext
+roll er
+lo se
+q l
+Ġp ol
+> </
+Ġsh ow
+U ser
+as ed
+Ġ{ ĊĊ
+Ġf ind
+Ð °
+E D
+s pan
+en u
+Ġc urrent
+Ġus ed
+ce pt
+cl ud
+Ġpl ay
+Ġl og
+ut ion
+f l
+Ġse e
+indow s
+Ġh elp
+Ġthe se
+Ġp ass
+Ġd own
+Ġe ven
+as on
+u ild
+f rom
+( d
+Ġb l
+l abel
+el se
+Ð µ
+Ġ( !
+iz ed
+() ,
+Ġo b
+Ġit em
+um p
+U R
+or n
+Ġd on
+S e
+m an
+am ple
+t n
+======== ========
+H e
+gr am
+Ġd id
+w n
+_ h
+iv er
+Ġs m
+Ġth rough
+ĠA n
+ch e
+Ġin v
+ou se
+Ġ es
+ĠN ew
+ex port
+m ary
+ut o
+l er
+Ġl ast
+Ġe vent
+tr y
+ï ¼
+il y
+ign ed
+in es
+oll ow
+ic ense
+so le
+le ar
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+ì¿ ½
+íĢ ħ
+íģ ¦
+íĤ ħ
+íĥ ¶
+íĥ ¹
+íĦ Ķ
+íħ £
+íĨ Ħ
+íĨ §
+íĨ ¹
+íĩ ¼
+íī ¤
+íĬ ½
+íĭ Ĥ
+íĭ ij
+íį Ī
+íį Ļ
+íį ¿
+íİ ¶
+íIJ Ŀ
+íĴ ľ
+íĵ Ŀ
+íĵ ª
+íĵ ±
+íĵ ·
+íĵ ¼
+íĶ Ļ
+íĶ ł
+íķ ļ
+íķ Ľ
+íķ ŀ
+íķ Ł
+íķ §
+íķ ¶
+íĸ Ĭ
+íĸ ĭ
+íĸ į
+íĸ Ķ
+íĸ ĺ
+íĸ ¡
+íĸ ¬
+íĹ £
+íĹ ¿
+íĺ ĸ
+íĺ Ń
+íļ °
+íĽ į
+íĽ ½
+íĿ Ł
+íĿ Ń
+íĿ ´
+íŀ ľ
+ï¤ ī
+ï¤ Ń
+ï¤ ²
+ï¤ µ
+ï¤ ¼
+ï¥ Ģ
+ï¥ ij
+ï¥ Ĵ
+ï¥ ķ
+ï¥ ĺ
+ï¥ Ļ
+ï¥ «
+ï¥ ¬
+ï¥ °
+ï ¥¿
+ï¦ ĭ
+ï¦ ı
+ï¦ Ķ
+ï¦ ĸ
+ï¦ ĺ
+ï¦ Ľ
+ï¦ ł
+ï¦ ®
+ï¦ ¯
+ï¦ º
+ï¦ »
+ï¦ ¾
+ï§ Ĩ
+ï§ ĸ
+ï§ Ľ
+ï§ ŀ
+ï§ Ł
+ï§ §
+ï§ ³
+ï§ º
+ï§ ½
+ï¨ ĥ
+ï¨ ļ
+ï¨ ¢
+ï© Ł
+ï¬ ¤
+ï¬ ¬
+ï¬ ¼
+ïŃ Ĵ
+ïŃ ķ
+ïŃ Ľ
+ïŃ Ŀ
+ïŃ ŀ
+ïŃ Ł
+ïŃ ¤
+ïŃ §
+ïŃ ¨
+ïŃ ®
+ïŃ °
+ïŃ ±
+ïŃ ·
+ïŃ ¹
+ïŃ »
+ï® Ģ
+ï® ĥ
+ï® Ħ
+ï® ħ
+ï® į
+ï® Ĵ
+ï® ĵ
+ï® ķ
+ï® ¦
+ï® ®
+ï® °
+ï¯ ĵ
+ï¯ ľ
+ï¯ ©
+ï¯ ª
+ï¯ ¬
+ï¯ Ń
+ï¯ ®
+ï¯ ·
+ï¯ ¹
+ï¯ »
+ï¯ ¼
+ï° ĥ
+ï° Į
+ï° IJ
+ï° ĺ
+ï° Ļ
+ï° ľ
+ï° ŀ
+ï° ¢
+ï° ®
+ï° °
+ï° ¼
+ï° ¿
+ï± Ģ
+ï± ģ
+ï± Ī
+ï± ĭ
+ï± ı
+ï± Ń
+ï² Ģ
+ï² ĩ
+ï² Ī
+ï² ĭ
+ï² İ
+ï² Ĵ
+ï² ľ
+ï² ł
+ï² ¬
+ï² »
+ï³ ĩ
+ï³ Ķ
+ï³ £
+ï³ «
+ï´ ĺ
+ï´ °
+ï´ ½
+ï ¶
+ï¶ °
+ï¸ ĸ
+ï¸ ´
+ï¸ ¹
+ï¹ į
+ï¹ Ĺ
+ï¹ ¢
+ï¹ ¤
+ï¹ ©
+ï¹ ±
+ï¾ °
+ï¿ Ĥ
+ï¿ ®
+ðIJĮ °
+ðIJĮ ¹
+ðIJĮ º
+ðIJĮ ½
+ðIJį Ĥ
+ðIJį ĥ
+ðIJį Ħ
+ðIJ İ
+ðIJİ ¹
+ðIJ¤ Ĥ
+ðIJ¤ į
+ðIJ¤ ı
+ðIJ¤ ĵ
+ðIJŃ ī
+ðIJŃ į
+ðIJ° ĩ
+ðIJ° °
+ðij Ĥ
+ðijĤ Ħ
+ðij ĺ
+ðijĺ ģ
+ðĴ Ģ
+ðĴĢ ¸
+ðĴ ģ
+ðĴģ º
+ðĴ Ħ
+ðĴĦ ·
+ðĴ Ĭ
+ðĴĬ ij
+ðĴ ĭ
+ðĴĭ Ĺ
+ð ĴĮ
+ðĴĮ ¨
+ðĵĥ ¢
+ðĵĥ °
+ðĸ ł
+ðĸł ļ
+ðĿĦ ĥ
+ðĿĦ ħ
+ðĿĦ ķ
+ðĿĦ Ļ
+ðĿĦ ±
+ðĿĦ ´
+ðĿĦ ¹
+ðĿħ İ
+ðĿħ ª
+ðĿĨ £
+ðĿĨ ³
+ðĿĨ ¹
+ðĿĩ Ĭ
+ðĿĩ Ĺ
+ðĿĩ ļ
+ðĿĩ ľ
+ðĿĩ ł
+ðĿIJ ī
+ðĿIJ ĸ
+ðĿIJ ĺ
+ðĿIJ £
+ðĿIJ ±
+ðĿij Ĭ
+ðĿij Ń
+ðĿij ¼
+ðĿij ½
+ðĿĴ °
+ðĿĴ ·
+ðĿĴ ¿
+ðĿĵ ģ
+ðĿĵ ĭ
+ðĿĵ İ
+ðĿĵ Ĵ
+ðĿ ĵĺ
+ðĿĵ ¢
+ðĿĵ ¦
+ðĿĵ «
+ðĿĵ ¿
+ðĿĶ İ
+ðĿĶ ±
+ðĿĶ ´
+ðĿĶ ·
+ðĿĶ ¸
+ðĿĶ ½
+ðĿķ Ĥ
+ðĿķ ĥ
+ðĿķ ĭ
+ðĿķ ı
+ðĿķ IJ
+ðĿķ ¥
+ðĿķ ´
+ðĿķ º
+ðĿĸ IJ
+ðĿĸ Ľ
+ðĿĸ Ŀ
+ðĿĸ ŀ
+ðĿĹ ©
+ðĿĹ ³
+ðĿĹ ½
+ðĿĺ Ĭ
+ðĿĺ ĭ
+ðĿĺ Ķ
+ðĿĺ ±
+ðĿĺ ´
+ðĿĺ ¿
+ðĿĻ Ĵ
+ðĿĻ Ŀ
+ðĿĻ Ł
+ðĿĻ ¬
+ðĿĻ Ń
+ðĿĻ »
+ðĿĻ ¾
+ðĿļ Ī
+ðĿļ ĭ
+ðĿļ ij
+ðĿļ Ł
+ðĿļ ł
+ðĿļ £
+ðĿĽ ½
+ðĿľ Ĥ
+ðĿľ Ķ
+ðĿľ Ļ
+ðŁ Ģ
+ðŁĢ Ħ
+ðŁĦ ²
+ðŁĦ ¶
+ðŁħ IJ
+ðŁħ ĸ
+ðŁħ ļ
+ðŁħ Ľ
+ðŁħ ¦
+ðŁħ ¶
+ðŁħ »
+ðŁħ ¼
+ðŁĨ ĥ
+ðŁĨ Ĩ
+ðŁĨ İ
+ðŁĪ ¯
+ðŁĪ ²
+ðŁĪ ¹
+ðŁĮ ĩ
+ðŁĮ ĵ
+ðŁį ĺ
+ðŁİ ij
+ðŁİ ¿
+ðŁı ı
+ðŁı Ĵ
+ðŁı ©
+ðŁı ¯
+ðŁIJ Ģ
+ðŁij Ŀ
+ðŁĴ ¹
+ðŁĴ º
+ðŁĵ Ł
+ðŁĵ ª
+ðŁĵ ¼
+ðŁĶ Ģ
+ðŁĶ Ĥ
+ðŁĶ ĥ
+ðŁĶ ĩ
+ðŁĶ ĵ
+ðŁĶ ¢
+ðŁĶ ¤
+ðŁĶ ©
+ðŁķ ĸ
+ðŁķ ļ
+ðŁķ ľ
+ðŁķ Ŀ
+ðŁķ ŀ
+ðŁķ ł
+ðŁķ ¢
+ðŁķ ³
+ðŁĸ ĩ
+ðŁĸ ij
+ðŁĸ ¶
+ðŁĹ ģ
+Ñ ¨
+Ú İ
+á¡ Į
+Ḡ°
+ẠĢ
+á¼ ®
+á½ Ŀ
+âĦ ¬
+âļ §
+⼠¤
+ã³ ¬
+êĻ ĭ
+ê¸ ij
+ëĶ ī
+ëĹ į
+ë¡ ij
+ë¯ ij
+ë» ħ
+ë¼ Ŀ
+ìĦ IJ
+ìī ¡
+ìĭ ²
+ìı ±
+ìĹ ¤
+ìĿ ©
+ìĿ ¿
+ìŁ Ļ
+ìł °
+ì¥ ī
+íĬ Ń
+íķ ®
+ï® ı
+ðŁħ ±
+ðŁĨ Ĵ
+ðŁķ ĭ
+É ĺ
+Ê ĵ
+Õ ĥ
+à´ ´
+འħ
+áĨ º
+áĪ Ĭ
+áĪ ¨
+áĪ ¾
+áī IJ
+áĮ ĥ
+áĮ ½
+áĶ Ń
+áł Ĥ
+áł ¬
+ᨠ¸
+á© ĭ
+ᶠı
+á¾ Ķ
+á¿ IJ
+á¿ ļ
+âĻ Ļ
+âļ Ĥ
+âļ Ĺ
+â¡ ¢
+⤠¦
+ëĸ °
+ë¤ Ĥ
+ë§ ł
+ë± ĭ
+ë± IJ
+ìĽ ¢
+ìľ ¾
+ì³ ħ
+ì» ģ
+íģ »
+íĥ Ļ
+íĵ ĸ
+íĵ Ń
+íķ ±
+íĽ ľ
+ï¤ ħ
+ï¤ Ĩ
+ï¦ ĥ
+ï§ ©
+ï¨ Ĥ
+ðIJ¤ Ķ
+ðIJŃ ĵ
+ðIJ° ¼
+ðĿĵ ŀ
+ðĿĵ °
+ðĿĻ ľ
+ðĿļ ģ
+ðŁħ ¢
+ðŁı ĩ
+È ²
+Ê ¶
+Ô Ī
+Ô ij
+Ý ĵ
+Ý ¥
+ठij
+ॠ±
+ଠī
+à° ³
+à° µ
+ಠŁ
+áĢ ı
+áģ ¼
+áī ¨
+áĬ Ĵ
+áĭ ©
+áĮ Ħ
+áĮ Ķ
+áIJ §
+á ĴĮ
+áĶ ħ
+áĶ Ĭ
+áł Ħ
+ᨠģ
+Ḡĥ
+Ḡ»
+âĶ ŀ
+âĺ µ
+âļ £
+â² ¢
+ãĪ ª
+ä¶ µ
+ê² Ļ
+ê² ´
+ê³ Ĥ
+ë¡ ¼
+ìĨ Ĭ
+ì¼ ĩ
+íĭ į
+íĵ ¬
+íĵ ®
+íĵ ¶
+íĵ »
+ï¤ ¦
+ï¥ ł
+ï¥ ±
+ïŃ ²
+ðIJŃ Ĭ
+ðIJ ±ħ
+ðĸ ¥
+ðĸ¥ ¨
+ðĿij ³
+ðĿĵ ķ
+ðĿĵ ¬
+ðĿĵ ¹
+ðĿĵ ¾
+ðĿĶ ĵ
+ðĿķ į
+ðĿķ ¡
+ðĿķ ±
+ðĿĸ ĸ
+ðĿĺ ı
+ðĿĺ IJ
+ðĿĺ ļ
+ðĿĻ ®
+ðĿĻ °
+ðĿĻ ¸
+ðĿĻ º
+ðĿĻ ¼
+ðĿĻ ½
+ðĿĻ ¿
+ðĿļ Ħ
+ðĿļ ı
+ðŁħ ħ
+ðŁħ ĵ
+Æ Ī
+àł Į
+áĻ ³
+á ļĮ
+ἠħ
+ἠIJ
+ᤠĬ
+ḠĬ
+âĶ ½
+âķ Ĭ
+⼠ĩ
+⼠ı
+âĿ ª
+âĿ «
+⣠°
+ãĦ į
+ãĦ ĵ
+ãĦ §
+ãħ ĸ
+ãī «
+ê¦ Ķ
+ï± Ĭ
+ຠĤ
+áħ £
+ᥠĶ
+ᥠ¤
+âĨ ¤
+âĨ ·
+âĩ ŀ
+âĸ ¤
+âŀ ¶
+ãĪ ¼
+ï¨ ·
+ðĵı §
+âĶ ²
+âĢ ´
+âĴ Ł
+âĴ ¡
+â° Ĥ
+â° į
+â° İ
+â° IJ
+â° ij
+â° Ł
+â° ł
+â° ¡
+â¼ Ń
+ãĬ ¥
+âĴ ł
+â½ º
+ãĩ º
+ãĩ ½
+ï¨ Ĭ
+áķ ·
+âį ¨
+⺠Ł
+â½ Ĺ
diff --git a/memory/mm_utils.py b/memory/mm_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..67d54d400621b02f65a0a92eeab8b659512b067b
--- /dev/null
+++ b/memory/mm_utils.py
@@ -0,0 +1,106 @@
+from PIL import Image
+from io import BytesIO
+import base64
+
+import torch
+from transformers import StoppingCriteria
+# from llava.constants import IMAGE_TOKEN_INDEX
+IGNORE_INDEX = -100
+IMAGE_TOKEN_INDEX = -200
+
+
+def load_image_from_base64(image):
+    return Image.open(BytesIO(base64.b64decode(image)))
+
+
+def expand2square(pil_img, background_color):
+    width, height = pil_img.size
+    if width == height:
+        return pil_img
+    elif width > height:
+        result = Image.new(pil_img.mode, (width, width), background_color)
+        result.paste(pil_img, (0, (width - height) // 2))
+        return result
+    else:
+        result = Image.new(pil_img.mode, (height, height), background_color)
+        result.paste(pil_img, ((height - width) // 2, 0))
+        return result
+
+
+def process_images(images, image_processor, model_cfg):
+    image_aspect_ratio = getattr(model_cfg, "image_aspect_ratio", None)
+    new_images = []
+    if image_aspect_ratio == 'pad':
+        for image in images:
+            image = expand2square(image, tuple(int(x*255) for x in image_processor.image_mean))
+            image = image_processor.preprocess(image, return_tensors='pt')['pixel_values'][0]
+            new_images.append(image)
+    else:
+        return image_processor(images, return_tensors='pt')['pixel_values']
+    if all(x.shape == new_images[0].shape for x in new_images):
+        new_images = torch.stack(new_images, dim=0)
+    return new_images
+
+
+def tokenizer_image_token(prompt, tokenizer, image_token_index=IMAGE_TOKEN_INDEX, return_tensors=None):
+    prompt_chunks = [tokenizer(chunk).input_ids for chunk in prompt.split('<image>')]
+
+    def insert_separator(X, sep):
+        return [ele for sublist in zip(X, [sep]*len(X)) for ele in sublist][:-1]
+
+    input_ids = []
+    offset = 0
+    if len(prompt_chunks) > 0 and len(prompt_chunks[0]) > 0 and prompt_chunks[0][0] == tokenizer.bos_token_id:
+        offset = 1
+        input_ids.append(prompt_chunks[0][0])
+
+    for x in insert_separator(prompt_chunks, [image_token_index] * (offset + 1)):
+        input_ids.extend(x[offset:])
+
+    if return_tensors is not None:
+        if return_tensors == 'pt':
+            return torch.tensor(input_ids, dtype=torch.long)
+        raise ValueError(f'Unsupported tensor type: {return_tensors}')
+    return input_ids
+
+
+def get_model_name_from_path(model_path):
+    model_path = model_path.strip("/")
+    model_paths = model_path.split("/")
+    if model_paths[-1].startswith('checkpoint-'):
+        return model_paths[-2] + "_" + model_paths[-1]
+    else:
+        return model_paths[-1]
+
+class KeywordsStoppingCriteria(StoppingCriteria):
+    def __init__(self, keywords, tokenizer, input_ids):
+        self.keywords = keywords
+        self.keyword_ids = []
+        self.max_keyword_len = 0
+        for keyword in keywords:
+            cur_keyword_ids = tokenizer(keyword).input_ids
+            if len(cur_keyword_ids) > 1 and cur_keyword_ids[0] == tokenizer.bos_token_id:
+                cur_keyword_ids = cur_keyword_ids[1:]
+            if len(cur_keyword_ids) > self.max_keyword_len:
+                self.max_keyword_len = len(cur_keyword_ids)
+            self.keyword_ids.append(torch.tensor(cur_keyword_ids))
+        self.tokenizer = tokenizer
+        self.start_len = input_ids.shape[1]
+    
+    def call_for_batch(self, output_ids: torch.LongTensor, scores: torch.FloatTensor, **kwargs) -> bool:
+        offset = min(output_ids.shape[1] - self.start_len, self.max_keyword_len)
+        self.keyword_ids = [keyword_id.to(output_ids.device) for keyword_id in self.keyword_ids]
+        for keyword_id in self.keyword_ids:
+            if (output_ids[0, -keyword_id.shape[0]:] == keyword_id).all():
+                return True
+        outputs = self.tokenizer.batch_decode(output_ids[:, -offset:], skip_special_tokens=True)[0]
+        for keyword in self.keywords:
+            if keyword in outputs:
+                return True
+        return False
+    
+    def __call__(self, output_ids: torch.LongTensor, scores: torch.FloatTensor, **kwargs) -> bool:
+        outputs = []
+        for i in range(output_ids.shape[0]):
+            outputs.append(self.call_for_batch(output_ids[i].unsqueeze(0), scores))
+        return all(outputs)
diff --git a/memory/model.safetensors b/memory/model.safetensors
new file mode 100644
index 0000000000000000000000000000000000000000..66967eadeb3e3d772a02c8841edfba71b8c0a883
--- /dev/null
+++ b/memory/model.safetensors
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9e02b76a117473e173b71056b963ac1bc918ca16905719076498cde0e14bf55d
+size 4177943760
diff --git a/memory/model_grounding_ego.py b/memory/model_grounding_ego.py
new file mode 100644
index 0000000000000000000000000000000000000000..6afb506914d12cd7ec5c2e3c5c585a4ddc11c1ba
--- /dev/null
+++ b/memory/model_grounding_ego.py
@@ -0,0 +1,202 @@
+import argparse
+import torch
+import os
+import json
+from tqdm import tqdm
+import shortuuid
+
+from grounding_qwen import GroundQwenForCausalLM
+from constants import IMAGE_TOKEN_INDEX, DEFAULT_IMAGE_TOKEN, DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN
+from conversation import conv_templates, SeparatorStyle
+from utils import disable_torch_init
+from mm_utils import tokenizer_image_token, process_images, get_model_name_from_path
+from torch.utils.data import Dataset, DataLoader
+
+from PIL import Image
+import math
+import pickle
+from decord import VideoReader
+import numpy as np
+
+from transformers import StoppingCriteria, StoppingCriteriaList, AutoTokenizer
+from petrel_client.client import Client
+client = Client('~/petreloss.conf')
+
+
+def get_seq_frames(total_num_frames, desired_num_frames):
+    seg_size = float(total_num_frames - 1) / desired_num_frames
+    seq = []
+    for i in range(desired_num_frames):
+        start = int(np.round(seg_size * i))
+        end = int(np.round(seg_size * (i + 1)))
+        seq.append((start + end) // 2)
+
+    return seq
+
+
+def get_seq_time(vr, frame_idx, num_clip):
+    frm_per_clip = len(frame_idx) // num_clip
+    key_frame = [[frame_idx[i*frm_per_clip], frame_idx[i*frm_per_clip+frm_per_clip-1]] for i in range(num_clip)]
+    time = vr.get_frame_timestamp(key_frame)
+    return np.hstack([time[:, 0, 0], time[:, 1, 1]])
+
+
+def calculate_diff(scene_sep, start_frame):
+    diff = [scene_sep[0]-start_frame]
+    for i in range(len(scene_sep)-1):
+        diff.append(scene_sep[i+1]-scene_sep[i])
+    return diff
+
+
+def load_video(vis_path, scene_sep, num_frm=16, max_clip=4):
+    block_size = 1
+    vr = VideoReader(vis_path)
+    total_frame_num = len(vr)
+    fps = vr.get_avg_fps()
+    total_time = total_frame_num / fps
+
+    if len(scene_sep) == 0:
+        num_clip = total_time / num_frm
+        num_clip = int(block_size*np.round(num_clip/block_size)) if num_clip > block_size else int(np.round(num_clip))
+        num_clip = max(num_clip, 5)
+        num_clip = min(num_clip, max_clip)
+        total_num_frm = num_frm * num_clip
+        start_frame = 0
+        frame_idx = get_seq_frames(total_frame_num, total_num_frm)
+    else:
+        num_clip = max(len(scene_sep), 5)
+        num_clip = min(num_clip, max_clip)
+        total_num_frm = num_frm * num_clip
+        start_frame = 0
+        frame_idx = []
+        if len(scene_sep) < 5:
+            diff = calculate_diff(scene_sep, start_frame)
+            new_sep = max(diff) / (5-len(scene_sep)+1)
+            max_idx = np.argmax(diff)
+            if max_idx == 0:
+                scene_sep = [int(start_frame+new_sep*i) for i in range(1, 5-len(scene_sep)+1)] + scene_sep
+            else:
+                scene_sep = scene_sep[:max_idx]+[int(scene_sep[max_idx-1]+i*new_sep) for i in range(1, 5-len(scene_sep)+1)] + scene_sep[max_idx:]
+        elif len(scene_sep) > max_clip:
+            diff = calculate_diff(scene_sep, start_frame)
+            min_idx = np.argsort(diff[:-1])[:len(scene_sep)-max_clip] ##minimum diff to remove
+            for i in np.sort(min_idx)[::-1]:
+                del scene_sep[i]
+
+        start_ = start_frame
+        for end_frame in scene_sep:
+            idx_list = np.linspace(start_, end_frame, num=num_frm, endpoint=False)
+            frame_idx.extend([int(id) for id in idx_list])
+            start_ = end_frame
+
+        time_idx = get_seq_time(vr, frame_idx, num_clip)
+        img_array = vr.get_batch(frame_idx).asnumpy()  # (n_clips*num_frm, H, W, 3)
+
+    a, H, W, _ = img_array.shape
+    h, w = 224, 224
+    if img_array.shape[-3] != h or img_array.shape[-2] != w:
+        img_array = torch.from_numpy(img_array).permute(0, 3, 1, 2).float()
+        img_array = torch.nn.functional.interpolate(img_array, size=(h, w))
+        img_array = img_array.permute(0, 2, 3, 1).to(torch.uint8).numpy()
+    img_array = img_array.reshape((1, total_num_frm, img_array.shape[-3], img_array.shape[-2], img_array.shape[-1]))
+
+    clip_imgs = []
+    for j in range(total_num_frm):
+        clip_imgs.append(Image.fromarray(img_array[0, j]))
+
+    return clip_imgs, time_idx, num_clip
+
+
+def preprocess_time(time, num_clip, tokenizer):
+    time = time.reshape(2, num_clip)
+    seq = []
+
+    block_size = 1
+    for i in range(num_clip):
+        start, end = time[:, i]
+        start = int(np.round(start))
+        end = int(np.round(end))
+        if (i+1) % block_size == 0:
+            history_end = end
+        sentence = 'This contains a clip sampled in %d to %d seconds' % (start, end) + DEFAULT_IMAGE_TOKEN
+        sentence = tokenizer_image_token(sentence, tokenizer, return_tensors='pt')
+        seq.append(sentence)
+    return seq
+
+
+def preprocess_question(questions, tokenizer):
+    seq = []
+    for q in questions:
+        sentence = tokenizer_image_token(q, tokenizer, return_tensors='pt')
+        seq.append(sentence)
+    
+    return seq
+
+
+
+def eval_dataset(args):
+    disable_torch_init()
+    model_path = os.path.expanduser(args.model_path)
+    model_name = get_model_name_from_path(model_path)
+
+    device = 'cuda'
+    kwargs = {"device_map": 'auto'}
+    kwargs['torch_dtype'] = torch.float16
+
+    tokenizer = AutoTokenizer.from_pretrained(model_path, use_fast=False)
+    model = GroundQwenForCausalLM.from_pretrained(model_path, low_cpu_mem_usage=True, **kwargs)
+    mm_use_im_start_end = getattr(model.config, "mm_use_im_start_end", False)
+    mm_use_im_patch_token = getattr(model.config, "mm_use_im_patch_token", True)
+    if mm_use_im_patch_token:
+        tokenizer.add_tokens([DEFAULT_IMAGE_PATCH_TOKEN], special_tokens=True)
+    if mm_use_im_start_end:
+        tokenizer.add_tokens([DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN], special_tokens=True)
+    model.resize_token_embeddings(len(tokenizer))
+
+    vision_tower = model.get_vision_tower()
+    if not vision_tower.is_loaded:
+        vision_tower.load_model()
+    vision_tower.to(device=device, dtype=torch.float16)
+    image_processor = vision_tower.image_processor
+
+    if hasattr(model.config, "max_sequence_length"):
+        context_len = model.config.max_sequence_length
+    else:
+        context_len = 2048
+
+    video_path = '/mnt/hwfile/mllm/qianrui/test_video/air.mp4'
+    question = ['How many pilots are shown in the video?', 'What airlines are shown in the video?', 'How is the decoration of the airport?']
+    scene_sep = json.load(open('/mnt/hwfile/mllm/qianrui/test_video/air.json', 'r'))['scene_sep']
+    frames, time_idx, num_clips = load_video(video_path, scene_sep, num_frm=16, max_clip=32)
+    video = image_processor.preprocess(frames, return_tensors='pt')['pixel_values']
+    video = video.view(num_clips, 16, *video.shape[1:])
+    seqs = preprocess_time(time_idx, num_clips, tokenizer)
+    seqs = torch.nn.utils.rnn.pad_sequence(
+        seqs, 
+        batch_first=True,
+        padding_value=tokenizer.pad_token_id)
+    compress_mask = seqs.ne(tokenizer.pad_token_id)
+    question = preprocess_question(question, tokenizer)
+    question = torch.nn.utils.rnn.pad_sequence(
+        question, 
+        batch_first=True,
+        padding_value=tokenizer.pad_token_id)
+    qs_mask = question.ne(tokenizer.pad_token_id)
+
+    with torch.inference_mode():
+        similarity = model.forward_grounding(
+            input_ids=seqs.to(device='cuda', non_blocking=True),
+            attention_mask=compress_mask.to(device='cuda', non_blocking=True),
+            images=video.to(dtype=torch.float16, device='cuda', non_blocking=True),
+            qs_ids=question.to(device='cuda', non_blocking=True),
+            qs_mask=qs_mask.to(device='cuda', non_blocking=True))
+    
+    print(similarity.shape, similarity)
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--model-path", type=str, default="facebook/opt-350m")
+    parser.add_argument("--conv-mode", type=str, default="llava_v1")
+    args = parser.parse_args()
+
+    eval_dataset(args)
diff --git a/memory/modeling_flash_attention_utils.py b/memory/modeling_flash_attention_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..5ca13a6333f7e2a48c1a91c231fb54555d6dc4fc
--- /dev/null
+++ b/memory/modeling_flash_attention_utils.py
@@ -0,0 +1,300 @@
+# coding=utf-8
+# Copyright 2024 The Fairseq Authors and the HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import inspect
+import os
+from typing import Optional, Tuple
+
+import torch
+import torch.nn.functional as F
+
+from transformers.utils import is_flash_attn_2_available
+
+
+if is_flash_attn_2_available():
+    from flash_attn.bert_padding import index_first_axis, pad_input, unpad_input  # noqa
+    from flash_attn import flash_attn_func, flash_attn_varlen_func
+
+    _flash_supports_window_size = "window_size" in list(inspect.signature(flash_attn_func).parameters)
+
+
+def _get_unpad_data(attention_mask: torch.Tensor) -> Tuple[torch.Tensor, torch.Tensor, int]:
+    """
+    Retrieves indexing data required to repad unpadded (ragged) tensors.
+
+    Arguments:
+        attention_mask (`torch.Tensor`):
+            Boolean or int tensor of shape (batch_size, sequence_length), 1 means valid and 0 means not valid.
+
+    Return:
+        indices (`torch.Tensor):
+            The indices of non-masked tokens from the flattened input sequence.
+        cu_seqlens (`torch.Tensor`):
+            The cumulative sequence lengths, used to index into ragged (unpadded) tensors. `cu_seqlens` shape is (batch_size + 1,).
+        max_seqlen_in_batch (`int`):
+            Maximum sequence length in batch.
+    """
+    seqlens_in_batch = attention_mask.sum(dim=-1, dtype=torch.int32)
+    indices = torch.nonzero(attention_mask.flatten(), as_tuple=False).flatten()
+    max_seqlen_in_batch = seqlens_in_batch.max().item()
+    cu_seqlens = F.pad(torch.cumsum(seqlens_in_batch, dim=0, dtype=torch.int32), (1, 0))
+    return (
+        indices,
+        cu_seqlens,
+        max_seqlen_in_batch,
+    )
+
+
+def _upad_input(
+    query_layer: torch.Tensor,
+    key_layer: torch.Tensor,
+    value_layer: torch.Tensor,
+    attention_mask: torch.Tensor,
+    query_length: int,
+):
+    """
+    Unpads query, key, and values tensors, using a single dimension for all tokens even though they belong to different batches.
+
+    This function is used instead of `flash_attn.bert_padding.unpad_input` in order to avoid the recomputation of the same intermediary
+    tensors for query, key, value tensors.
+
+    Arguments:
+        query_layer (`torch.Tensor`):
+            Query state with padding. Shape: (batch_size, query_length, num_heads, head_dim).
+        key_layer (`torch.Tensor`):
+            Key state with padding. Shape: (batch_size, kv_seq_len, num_key_value_heads, head_dim).
+        value_layer (`torch.Tensor`):
+            Value state with padding. Shape: (batch_size, kv_seq_len, num_key_value_heads, head_dim).
+        attention_mask (`torch.Tensor`):
+            Boolean or int tensor of shape (batch_size, sequence_length), 1 means valid and 0 means not valid.
+        query_length (`int`):
+            Target length.
+
+    Return:
+        query_layer (`torch.Tensor):
+            Query state without padding. Shape: (total_target_length, num_heads, head_dim).
+        key_layer (`torch.Tensor`):
+            Key state with padding. Shape: (total_source_length, num_key_value_heads, head_dim).
+        value_layer (`torch.Tensor`):
+            Value state with padding. Shape: (total_source_length, num_key_value_heads, head_dim).
+        indices_q (`torch.Tensor`):
+            The indices of non-masked tokens from the flattened input target sequence.
+        (cu_seqlens_q, cu_seqlens_k) (`Tuple[int]`):
+            The cumulative sequence lengths for the target (query) and source (key, value), used to index into ragged (unpadded) tensors. `cu_seqlens` shape is (batch_size + 1,).
+        (max_seqlen_in_batch_q, max_seqlen_in_batch_k) (`Tuple[int]`):
+            Maximum sequence length in batch (`max_seqlen_in_batch_q` for the target sequence i.e. query, `max_seqlen_in_batch_k` for the source sequence i.e. key/value).
+    """
+    indices_k, cu_seqlens_k, max_seqlen_in_batch_k = _get_unpad_data(attention_mask)
+    batch_size, kv_seq_len, num_key_value_heads, head_dim = key_layer.shape
+
+    key_layer = index_first_axis(key_layer.reshape(batch_size * kv_seq_len, num_key_value_heads, head_dim), indices_k)
+    value_layer = index_first_axis(
+        value_layer.reshape(batch_size * kv_seq_len, num_key_value_heads, head_dim), indices_k
+    )
+    if query_length == kv_seq_len:
+        query_layer = index_first_axis(query_layer.reshape(batch_size * kv_seq_len, -1, head_dim), indices_k)
+        cu_seqlens_q = cu_seqlens_k
+        max_seqlen_in_batch_q = max_seqlen_in_batch_k
+        indices_q = indices_k
+    elif query_length == 1:
+        max_seqlen_in_batch_q = 1
+        cu_seqlens_q = torch.arange(
+            batch_size + 1, dtype=torch.int32, device=query_layer.device
+        )  # There is a memcpy here, that is very bad.
+        indices_q = cu_seqlens_q[:-1]
+        query_layer = query_layer.squeeze(1)
+    else:
+        # The -q_len: slice assumes left padding.
+        attention_mask = attention_mask[:, -query_length:]
+        query_layer, indices_q, cu_seqlens_q, max_seqlen_in_batch_q = unpad_input(query_layer, attention_mask)
+
+    return (
+        query_layer,
+        key_layer,
+        value_layer,
+        indices_q,
+        (cu_seqlens_q, cu_seqlens_k),
+        (max_seqlen_in_batch_q, max_seqlen_in_batch_k),
+    )
+
+
+def prepare_fa2_from_position_ids(query, key, value, position_ids):
+    """
+    This function returns necessary arguments to call `flash_attn_varlen_func`.
+    All three query, key, value states will be flattened.
+    Cummulative lengths of each examples in the batch will be extracted from position_ids.
+
+    NOTE: ideally cummulative lengths should be prepared at the data collator stage
+
+    Arguments:
+        query (`torch.Tensor`):
+            Query state with padding. Shape: (batch_size, query_length, num_heads, head_dim).
+        key (`torch.Tensor`):
+            Key state with padding. Shape: (batch_size, kv_seq_len, num_key_value_heads, head_dim).
+        value (`torch.Tensor`):
+            Value state with padding. Shape: (batch_size, kv_seq_len, num_key_value_heads, head_dim).
+        position_ids (`torch.Tensor`):
+            Boolean or int tensor of shape (batch_size, sequence_length), 1 means valid and 0 means not valid.
+
+    Return:
+        query (`torch.Tensor):
+            Query state without padding. Shape: (total_target_length, num_heads, head_dim).
+        key (`torch.Tensor`):
+            Key state with padding. Shape: (total_source_length, num_key_value_heads, head_dim).
+        value (`torch.Tensor`):
+            Value state with padding. Shape: (total_source_length, num_key_value_heads, head_dim).
+        indices_q (`torch.Tensor`):
+            The indices of non-masked tokens from the flattened input target sequence.
+        (cu_seqlens_q, cu_seqlens_k) (`Tuple[int]`):
+            The cumulative sequence lengths for the target (query) and source (key, value), used to index into ragged (unpadded) tensors. `cu_seqlens` shape is (batch_size + 1,).
+        (max_seqlen_in_batch_q, max_seqlen_in_batch_k) (`Tuple[int]`):
+            Maximum sequence length in batch (`max_seqlen_in_batch_q` for the target sequence i.e. query, `max_seqlen_in_batch_k` for the source sequence i.e. key/value).
+    """
+    query = query.view(-1, query.size(-2), query.size(-1))
+    key = key.view(-1, key.size(-2), key.size(-1))
+    value = value.view(-1, value.size(-2), value.size(-1))
+    position_ids = position_ids.flatten()
+    indices_q = torch.arange(position_ids.size(0), device=position_ids.device, dtype=torch.int32)
+
+    cu_seq_lens = torch.cat(
+        (
+            indices_q[position_ids == 0],
+            torch.tensor(position_ids.size(), device=position_ids.device, dtype=torch.int32),
+        )
+    )
+
+    max_length = position_ids.max() + 1
+
+    return (query, key, value, indices_q, (cu_seq_lens, cu_seq_lens), (max_length, max_length))
+
+
+def _flash_attention_forward(
+    query_states: torch.Tensor,
+    key_states: torch.Tensor,
+    value_states: torch.Tensor,
+    attention_mask: torch.Tensor,
+    query_length: int,
+    is_causal: bool,
+    dropout: float = 0.0,
+    position_ids: Optional[torch.Tensor] = None,
+    softmax_scale: Optional[float] = None,
+    sliding_window: Optional[int] = None,
+    use_top_left_mask: bool = False,
+    softcap: Optional[float] = None,
+    deterministic: bool = None,
+):
+    """
+    Calls the forward method of Flash Attention - if the input hidden states contain at least one padding token
+    first unpad the input, then computes the attention scores and pad the final attention scores.
+
+    Args:
+        query_states (`torch.Tensor`):
+            Input query states to be passed to Flash Attention API
+        key_states (`torch.Tensor`):
+            Input key states to be passed to Flash Attention API
+        value_states (`torch.Tensor`):
+            Input value states to be passed to Flash Attention API
+        attention_mask (`torch.Tensor`):
+            The padding mask - corresponds to a tensor of size `(batch_size, seq_len)` where 0 stands for the
+            position of padding tokens and 1 for the position of non-padding tokens.
+        dropout (`float`):
+            Attention dropout
+        softmax_scale (`float`, *optional*):
+            The scaling of QK^T before applying softmax. Default to 1 / sqrt(head_dim)
+        use_top_left_mask (`bool`, defaults to `False`):
+            flash_attn<2.1 generates top-left aligned causal mask, while what is needed here is bottom-right alignement, that was made default for flash_attn>=2.1. This attribute is used to handle this difference.
+        softcap (`float`, *optional*):
+            Softcap for the attention logits, used e.g. in gemma2.
+        deterministic (`bool`, *optional*):
+            Determines if the deterministic option introduced in flash_attn>=2.4.1 is enabled.
+    """
+    if not use_top_left_mask:
+        causal = is_causal
+    else:
+        # TODO: Remove the `query_length != 1` check once Flash Attention for RoCm is bumped to 2.1. For details, please see the comment in transformers.models.llama.modeling_llama.LlamaFlashAttention2.__init__.
+        causal = is_causal and query_length != 1
+
+    # Assuming 4D tensors, key_states.shape[1] is the key/value sequence length (source length).
+    use_sliding_windows = (
+        _flash_supports_window_size and sliding_window is not None and key_states.shape[1] > sliding_window
+    )
+    flash_kwargs = {"window_size": (sliding_window, sliding_window)} if use_sliding_windows else {}
+
+    if deterministic is None:
+        deterministic = os.environ.get("FLASH_ATTENTION_DETERMINISTIC", "0") == "1"
+    flash_kwargs["deterministic"] = deterministic
+
+    if softcap is not None:
+        flash_kwargs["softcap"] = softcap
+
+    # Contains at least one padding token in the sequence
+    if attention_mask is not None:
+        batch_size = query_states.shape[0]
+        query_states, key_states, value_states, indices_q, cu_seq_lens, max_seq_lens = _upad_input(
+            query_states, key_states, value_states, attention_mask, query_length
+        )
+        cu_seqlens_q, cu_seqlens_k = cu_seq_lens
+        max_seqlen_in_batch_q, max_seqlen_in_batch_k = max_seq_lens
+
+        attn_output_unpad = flash_attn_varlen_func(
+            query_states,
+            key_states,
+            value_states,
+            cu_seqlens_q=cu_seqlens_q,
+            cu_seqlens_k=cu_seqlens_k,
+            max_seqlen_q=max_seqlen_in_batch_q,
+            max_seqlen_k=max_seqlen_in_batch_k,
+            dropout_p=dropout,
+            softmax_scale=softmax_scale,
+            causal=causal,
+            **flash_kwargs,
+        )
+        attn_output = pad_input(attn_output_unpad, indices_q, batch_size, query_length)
+
+    # if position_ids is provided and check not all examples (row) contain only 1 sequence, and is in pre-fill/training stage
+    # then use `flash_attn_varlen_func` to prevent cross-example attention and also allow padding free approach
+    elif (
+        position_ids is not None and not (position_ids[:, -1] == position_ids.size(1) - 1).all() and query_length != 1
+    ):
+        batch_size = query_states.size(0)
+        query_states, key_states, value_states, indices_q, cu_seq_lens, max_seq_lens = prepare_fa2_from_position_ids(
+            query_states, key_states, value_states, position_ids
+        )
+
+        cu_seqlens_q, cu_seqlens_k = cu_seq_lens
+        max_seqlen_in_batch_q, max_seqlen_in_batch_k = max_seq_lens
+
+        attn_output = flash_attn_varlen_func(
+            query_states,
+            key_states,
+            value_states,
+            cu_seqlens_q=cu_seqlens_q,
+            cu_seqlens_k=cu_seqlens_k,
+            max_seqlen_q=max_seqlen_in_batch_q,
+            max_seqlen_k=max_seqlen_in_batch_k,
+            dropout_p=dropout,
+            softmax_scale=softmax_scale,
+            causal=causal,
+            **flash_kwargs,
+        )
+
+        attn_output = attn_output.view(batch_size, -1, attn_output.size(-2), attn_output.size(-1))
+
+    else:
+        attn_output = flash_attn_func(
+            query_states, key_states, value_states, dropout, softmax_scale=softmax_scale, causal=causal, **flash_kwargs
+        )
+
+    return attn_output
\ No newline at end of file
diff --git a/memory/modeling_qwen.py b/memory/modeling_qwen.py
new file mode 100644
index 0000000000000000000000000000000000000000..7065262d9d104f7e20a32f63af61aa34c1f7c102
--- /dev/null
+++ b/memory/modeling_qwen.py
@@ -0,0 +1,1773 @@
+# coding=utf-8
+# Copyright 2024 The Qwen team, Alibaba Group and the HuggingFace Inc. team. All rights reserved.
+#
+# This code is based on EleutherAI's GPT-NeoX library and the GPT-NeoX
+# and OPT implementations in this library. It has been modified from its
+# original forms to accommodate minor architectural differences compared
+# to GPT-NeoX and OPT used by the Meta AI team that trained the model.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""PyTorch Qwen2 model."""
+
+import math
+from typing import List, Optional, Tuple, Union
+
+import torch
+import torch.utils.checkpoint
+from torch import nn
+from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
+
+from transformers.activations import ACT2FN
+from transformers.cache_utils import Cache, DynamicCache, StaticCache
+from transformers.modeling_attn_mask_utils import (
+    AttentionMaskConverter,
+)
+from transformers.modeling_outputs import (
+    BaseModelOutputWithPast,
+    CausalLMOutputWithPast,
+    SequenceClassifierOutputWithPast,
+    TokenClassifierOutput,
+)
+from transformers.modeling_utils import PreTrainedModel
+from transformers.utils import (
+    add_start_docstrings,
+    add_start_docstrings_to_model_forward,
+    is_flash_attn_2_available,
+    is_flash_attn_greater_or_equal_2_10,
+    logging,
+    replace_return_docstrings,
+)
+from configuration_qwen import Qwen2Config
+
+
+if is_flash_attn_2_available():
+    from modeling_flash_attention_utils import _flash_attention_forward
+
+
+logger = logging.get_logger(__name__)
+
+
+_CHECKPOINT_FOR_DOC = "Qwen/Qwen2-7B-beta"
+_CONFIG_FOR_DOC = "Qwen2Config"
+
+
+# Copied from transformers.models.llama.modeling_llama.LlamaRMSNorm with Llama->Qwen2
+class Qwen2RMSNorm(nn.Module):
+    def __init__(self, hidden_size, eps=1e-6):
+        """
+        Qwen2RMSNorm is equivalent to T5LayerNorm
+        """
+        super().__init__()
+        self.weight = nn.Parameter(torch.ones(hidden_size))
+        self.variance_epsilon = eps
+
+    def forward(self, hidden_states):
+        input_dtype = hidden_states.dtype
+        hidden_states = hidden_states.to(torch.float32)
+        variance = hidden_states.pow(2).mean(-1, keepdim=True)
+        hidden_states = hidden_states * torch.rsqrt(variance + self.variance_epsilon)
+        return self.weight * hidden_states.to(input_dtype)
+
+    def extra_repr(self):
+        return f"{tuple(self.weight.shape)}, eps={self.variance_epsilon}"
+
+
+# Copied from transformers.models.mixtral.modeling_mixtral.MixtralRotaryEmbedding with Mixtral->Qwen2
+class Qwen2RotaryEmbedding(nn.Module):
+    def __init__(self, dim, max_position_embeddings=2048, base=10000, device=None):
+        super().__init__()
+
+        self.dim = dim
+        self.max_position_embeddings = max_position_embeddings
+        self.base = base
+        inv_freq = 1.0 / (self.base ** (torch.arange(0, self.dim, 2, dtype=torch.int64).float().to(device) / self.dim))
+        self.register_buffer("inv_freq", inv_freq, persistent=False)
+
+        # Build here to make `torch.jit.trace` work.
+        self._set_cos_sin_cache(
+            seq_len=max_position_embeddings, device=self.inv_freq.device, dtype=torch.get_default_dtype()
+        )
+
+    def _set_cos_sin_cache(self, seq_len, device, dtype):
+        self.max_seq_len_cached = seq_len
+        t = torch.arange(self.max_seq_len_cached, device=device, dtype=torch.int64).type_as(self.inv_freq)
+
+        freqs = torch.outer(t, self.inv_freq)
+        # Different from paper, but it uses a different permutation in order to obtain the same calculation
+        emb = torch.cat((freqs, freqs), dim=-1)
+        self.register_buffer("cos_cached", emb.cos().to(dtype), persistent=False)
+        self.register_buffer("sin_cached", emb.sin().to(dtype), persistent=False)
+
+    def forward(self, x, seq_len=None):
+        # x: [bs, num_attention_heads, seq_len, head_size]
+        if seq_len > self.max_seq_len_cached:
+            self._set_cos_sin_cache(seq_len=seq_len, device=x.device, dtype=x.dtype)
+
+        return (
+            self.cos_cached[:seq_len].to(dtype=x.dtype),
+            self.sin_cached[:seq_len].to(dtype=x.dtype),
+        )
+
+
+# Copied from transformers.models.llama.modeling_llama.rotate_half
+def rotate_half(x):
+    """Rotates half the hidden dims of the input."""
+    x1 = x[..., : x.shape[-1] // 2]
+    x2 = x[..., x.shape[-1] // 2 :]
+    return torch.cat((-x2, x1), dim=-1)
+
+
+# Copied from transformers.models.mixtral.modeling_mixtral.apply_rotary_pos_emb
+def apply_rotary_pos_emb(q, k, cos, sin, position_ids, unsqueeze_dim=1):
+    """Applies Rotary Position Embedding to the query and key tensors.
+
+    Args:
+        q (`torch.Tensor`): The query tensor.
+        k (`torch.Tensor`): The key tensor.
+        cos (`torch.Tensor`): The cosine part of the rotary embedding.
+        sin (`torch.Tensor`): The sine part of the rotary embedding.
+        position_ids (`torch.Tensor`):
+            The position indices of the tokens corresponding to the query and key tensors. For example, this can be
+            used to pass offsetted position ids when working with a KV-cache.
+        unsqueeze_dim (`int`, *optional*, defaults to 1):
+            The 'unsqueeze_dim' argument specifies the dimension along which to unsqueeze cos[position_ids] and
+            sin[position_ids] so that they can be properly broadcasted to the dimensions of q and k. For example, note
+            that cos[position_ids] and sin[position_ids] have the shape [batch_size, seq_len, head_dim]. Then, if q and
+            k have the shape [batch_size, heads, seq_len, head_dim], then setting unsqueeze_dim=1 makes
+            cos[position_ids] and sin[position_ids] broadcastable to the shapes of q and k. Similarly, if q and k have
+            the shape [batch_size, seq_len, heads, head_dim], then set unsqueeze_dim=2.
+    Returns:
+        `tuple(torch.Tensor)` comprising of the query and key tensors rotated using the Rotary Position Embedding.
+    """
+    cos = cos[position_ids].unsqueeze(unsqueeze_dim)
+    sin = sin[position_ids].unsqueeze(unsqueeze_dim)
+    q_embed = (q * cos) + (rotate_half(q) * sin)
+    k_embed = (k * cos) + (rotate_half(k) * sin)
+    return q_embed, k_embed
+
+
+# Copied from transformers.models.mistral.modeling_mistral.MistralMLP with Mistral->Qwen2
+class Qwen2MLP(nn.Module):
+    def __init__(self, config):
+        super().__init__()
+        self.hidden_size = config.hidden_size
+        self.intermediate_size = config.intermediate_size
+        self.gate_proj = nn.Linear(self.hidden_size, self.intermediate_size, bias=False)
+        self.up_proj = nn.Linear(self.hidden_size, self.intermediate_size, bias=False)
+        self.down_proj = nn.Linear(self.intermediate_size, self.hidden_size, bias=False)
+        self.act_fn = ACT2FN[config.hidden_act]
+
+    def forward(self, hidden_state):
+        return self.down_proj(self.act_fn(self.gate_proj(hidden_state)) * self.up_proj(hidden_state))
+
+
+# Copied from transformers.models.llama.modeling_llama.repeat_kv
+def repeat_kv(hidden_states: torch.Tensor, n_rep: int) -> torch.Tensor:
+    """
+    This is the equivalent of torch.repeat_interleave(x, dim=1, repeats=n_rep). The hidden states go from (batch,
+    num_key_value_heads, seqlen, head_dim) to (batch, num_attention_heads, seqlen, head_dim)
+    """
+    batch, num_key_value_heads, slen, head_dim = hidden_states.shape
+    if n_rep == 1:
+        return hidden_states
+    hidden_states = hidden_states[:, :, None, :, :].expand(batch, num_key_value_heads, n_rep, slen, head_dim)
+    return hidden_states.reshape(batch, num_key_value_heads * n_rep, slen, head_dim)
+
+
+class Qwen2Attention(nn.Module):
+    """
+    Multi-headed attention from 'Attention Is All You Need' paper. Modified to use sliding window attention: Longformer
+    and "Generating Long Sequences with Sparse Transformers".
+    """
+
+    def __init__(self, config: Qwen2Config, layer_idx: Optional[int] = None):
+        super().__init__()
+        self.config = config
+        self.layer_idx = layer_idx
+        if layer_idx is None:
+            logger.warning_once(
+                f"Instantiating {self.__class__.__name__} without passing `layer_idx` is not recommended and will "
+                "to errors during the forward call, if caching is used. Please make sure to provide a `layer_idx` "
+                "when creating this class."
+            )
+
+        self.hidden_size = config.hidden_size
+        self.num_heads = config.num_attention_heads
+        self.head_dim = self.hidden_size // self.num_heads
+        self.num_key_value_heads = config.num_key_value_heads
+        self.num_key_value_groups = self.num_heads // self.num_key_value_heads
+        self.max_position_embeddings = config.max_position_embeddings
+        self.rope_theta = config.rope_theta
+        self.is_causal = True
+        self.attention_dropout = config.attention_dropout
+
+        if (self.head_dim * self.num_heads) != self.hidden_size:
+            raise ValueError(
+                f"hidden_size must be divisible by num_heads (got `hidden_size`: {self.hidden_size}"
+                f" and `num_heads`: {self.num_heads})."
+            )
+        self.q_proj = nn.Linear(self.hidden_size, self.num_heads * self.head_dim, bias=True)
+        self.k_proj = nn.Linear(self.hidden_size, self.num_key_value_heads * self.head_dim, bias=True)
+        self.v_proj = nn.Linear(self.hidden_size, self.num_key_value_heads * self.head_dim, bias=True)
+        self.o_proj = nn.Linear(self.num_heads * self.head_dim, self.hidden_size, bias=False)
+
+        self.rotary_emb = Qwen2RotaryEmbedding(
+            self.head_dim,
+            max_position_embeddings=self.max_position_embeddings,
+            base=self.rope_theta,
+        )
+
+    def forward(
+        self,
+        hidden_states: torch.Tensor,
+        attention_mask: Optional[torch.Tensor] = None,
+        position_ids: Optional[torch.LongTensor] = None,
+        past_key_value: Optional[Cache] = None,
+        output_attentions: bool = False,
+        use_cache: bool = False,
+        cache_position: Optional[torch.LongTensor] = None,
+    ) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[Tuple[torch.Tensor]]]:
+        bsz, q_len, _ = hidden_states.size()
+
+        query_states = self.q_proj(hidden_states)
+        key_states = self.k_proj(hidden_states)
+        value_states = self.v_proj(hidden_states)
+
+        query_states = query_states.view(bsz, q_len, self.num_heads, self.head_dim).transpose(1, 2)
+        key_states = key_states.view(bsz, q_len, self.num_key_value_heads, self.head_dim).transpose(1, 2)
+        value_states = value_states.view(bsz, q_len, self.num_key_value_heads, self.head_dim).transpose(1, 2)
+
+        kv_seq_len = key_states.shape[-2]
+        if past_key_value is not None:
+            if self.layer_idx is None:
+                raise ValueError(
+                    f"The cache structure has changed since version v4.36. If you are using {self.__class__.__name__} "
+                    "for auto-regressive decoding with k/v caching, please make sure to initialize the attention class "
+                    "with a layer index."
+                )
+            kv_seq_len += past_key_value.get_usable_length(kv_seq_len, self.layer_idx)
+        cos, sin = self.rotary_emb(value_states, seq_len=kv_seq_len)
+        query_states, key_states = apply_rotary_pos_emb(query_states, key_states, cos, sin, position_ids)
+
+        if past_key_value is not None:
+            cache_kwargs = {"sin": sin, "cos": cos, "cache_position": cache_position}  # Specific to RoPE models
+            key_states, value_states = past_key_value.update(key_states, value_states, self.layer_idx, cache_kwargs)
+
+        # repeat k/v heads if n_kv_heads < n_heads
+        key_states = repeat_kv(key_states, self.num_key_value_groups)
+        value_states = repeat_kv(value_states, self.num_key_value_groups)
+
+        attn_weights = torch.matmul(query_states, key_states.transpose(2, 3)) / math.sqrt(self.head_dim)
+
+        if attn_weights.size() != (bsz, self.num_heads, q_len, kv_seq_len):
+            raise ValueError(
+                f"Attention weights should be of size {(bsz, self.num_heads, q_len, kv_seq_len)}, but is"
+                f" {attn_weights.size()}"
+            )
+
+        if attention_mask is not None:  # no matter the length, we just slice it
+            causal_mask = attention_mask[:, :, :, : key_states.shape[-2]]
+            attn_weights = attn_weights + causal_mask
+
+        # upcast attention to fp32
+        attn_weights = nn.functional.softmax(attn_weights, dim=-1, dtype=torch.float32).to(query_states.dtype)
+        attn_weights = nn.functional.dropout(attn_weights, p=self.attention_dropout, training=self.training)
+        attn_output = torch.matmul(attn_weights, value_states)
+
+        if attn_output.size() != (bsz, self.num_heads, q_len, self.head_dim):
+            raise ValueError(
+                f"`attn_output` should be of size {(bsz, self.num_heads, q_len, self.head_dim)}, but is"
+                f" {attn_output.size()}"
+            )
+
+        attn_output = attn_output.transpose(1, 2).contiguous()
+        attn_output = attn_output.reshape(bsz, q_len, self.hidden_size)
+
+        attn_output = self.o_proj(attn_output)
+
+        if not output_attentions:
+            attn_weights = None
+
+        return attn_output, attn_weights, past_key_value
+
+
+class Qwen2FlashAttention2(Qwen2Attention):
+    """
+    Qwen2 flash attention module, following Qwen2 attention module. This module inherits from `Qwen2Attention`
+    as the weights of the module stays untouched. The only required change would be on the forward pass
+    where it needs to correctly call the public API of flash attention and deal with padding tokens
+    in case the input contains any of them. Additionally, for sliding window attention, we apply SWA only to the bottom
+    config.max_window_layers layers.
+    """
+
+    # Copied from transformers.models.llama.modeling_llama.LlamaFlashAttention2.__init__
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+
+        # TODO: Should be removed once Flash Attention for RoCm is bumped to 2.1.
+        # flash_attn<2.1 generates top-left aligned causal mask, while what is needed here is bottom-right alignement, that was made default for flash_attn>=2.1. This attribute is used to handle this difference. Reference: https://github.com/Dao-AILab/flash-attention/releases/tag/v2.1.0.
+        # Beware that with flash_attn<2.1, using q_seqlen != k_seqlen (except for the case q_seqlen == 1) produces a wrong mask (top-left).
+        self._flash_attn_uses_top_left_mask = not is_flash_attn_greater_or_equal_2_10()
+
+    def forward(
+        self,
+        hidden_states: torch.Tensor,
+        attention_mask: Optional[torch.Tensor] = None,
+        position_ids: Optional[torch.LongTensor] = None,
+        past_key_value: Optional[Cache] = None,
+        indicators: Optional[torch.LongTensor] = None,
+        output_attentions: bool = False,
+        use_cache: bool = False,
+        cache_position: Optional[torch.LongTensor] = None,
+    ):
+        bsz, q_len, _ = hidden_states.size()
+
+        query_states = self.q_proj(hidden_states)
+        key_states = self.k_proj(hidden_states)
+        value_states = self.v_proj(hidden_states)
+
+        query_states = query_states.view(bsz, q_len, self.num_heads, self.head_dim).transpose(1, 2)
+        key_states = key_states.view(bsz, q_len, self.num_key_value_heads, self.head_dim).transpose(1, 2)
+        value_states = value_states.view(bsz, q_len, self.num_key_value_heads, self.head_dim).transpose(1, 2)
+
+        kv_seq_len = key_states.shape[-2]
+        if past_key_value is not None:
+            if self.layer_idx is None:
+                raise ValueError(
+                    f"The cache structure has changed since version v4.36. If you are using {self.__class__.__name__} "
+                    "for auto-regressive decoding with k/v caching, please make sure to initialize the attention class "
+                    "with a layer index."
+                )
+            kv_seq_len += past_key_value.get_usable_length(kv_seq_len, self.layer_idx)
+
+        # Because the input can be padded, the absolute sequence length depends on the max position id.
+        rotary_seq_len = max(kv_seq_len, position_ids[:, -1].max().item()) + 1
+        cos, sin = self.rotary_emb(value_states, seq_len=rotary_seq_len)
+
+        query_states, key_states = apply_rotary_pos_emb(query_states, key_states, cos, sin, position_ids)
+
+        if past_key_value is not None:
+            # Activate slicing cache only if the config has a value `sliding_windows` attribute
+            cache_has_contents = past_key_value.get_seq_length(self.layer_idx) > 0
+            if (
+                getattr(self.config, "sliding_window", None) is not None
+                and kv_seq_len > self.config.sliding_window
+                and cache_has_contents
+            ):
+                slicing_tokens = 1 - self.config.sliding_window
+
+                past_key = past_key_value[self.layer_idx][0]
+                past_value = past_key_value[self.layer_idx][1]
+
+                past_key = past_key[:, :, slicing_tokens:, :].contiguous()
+                past_value = past_value[:, :, slicing_tokens:, :].contiguous()
+
+                if past_key.shape[-2] != self.config.sliding_window - 1:
+                    raise ValueError(
+                        f"past key must have a shape of (`batch_size, num_heads, self.config.sliding_window-1, head_dim`), got"
+                        f" {past_key.shape}"
+                    )
+
+                if attention_mask is not None:
+                    attention_mask = attention_mask[:, slicing_tokens:]
+                    attention_mask = torch.cat([attention_mask, torch.ones_like(attention_mask[:, -1:])], dim=-1)
+
+            cache_kwargs = {"sin": sin, "cos": cos, "cache_position": cache_position}  # Specific to RoPE models
+            key_states, value_states = past_key_value.update(key_states, value_states, self.layer_idx, cache_kwargs)
+
+        # repeat k/v heads if n_kv_heads < n_heads
+        key_states = repeat_kv(key_states, self.num_key_value_groups)
+        value_states = repeat_kv(value_states, self.num_key_value_groups)
+        dropout_rate = 0.0 if not self.training else self.attention_dropout
+
+        # In PEFT, usually we cast the layer norms in float32 for training stability reasons
+        # therefore the input hidden states gets silently casted in float32. Hence, we need
+        # cast them back in float16 just to be sure everything works as expected.
+        input_dtype = query_states.dtype
+        if input_dtype == torch.float32:
+            if torch.is_autocast_enabled():
+                target_dtype = torch.get_autocast_gpu_dtype()
+            # Handle the case where the model is quantized
+            elif hasattr(self.config, "_pre_quantization_dtype"):
+                target_dtype = self.config._pre_quantization_dtype
+            else:
+                target_dtype = self.q_proj.weight.dtype
+
+            logger.warning_once(
+                f"The input hidden states seems to be silently casted in float32, this might be related to"
+                f" the fact you have upcasted embedding or layer norm layers in float32. We will cast back the input in"
+                f" {target_dtype}."
+            )
+
+            query_states = query_states.to(target_dtype)
+            key_states = key_states.to(target_dtype)
+            value_states = value_states.to(target_dtype)
+
+        # Reashape to the expected shape for Flash Attention
+        query_states = query_states.transpose(1, 2)
+        key_states = key_states.transpose(1, 2)
+        value_states = value_states.transpose(1, 2)
+
+        if (
+            self.config.use_sliding_window
+            and getattr(self.config, "sliding_window", None) is not None
+            and self.layer_idx >= self.config.max_window_layers
+        ):
+            sliding_window = self.config.sliding_window
+        else:
+            sliding_window = None
+
+        attn_output = _flash_attention_forward(
+            query_states,
+            key_states,
+            value_states,
+            attention_mask,
+            q_len,
+            position_ids=position_ids,
+            dropout=dropout_rate,
+            sliding_window=sliding_window,
+            is_causal=self.is_causal,
+            use_top_left_mask=self._flash_attn_uses_top_left_mask,
+        )
+
+        attn_output = attn_output.reshape(bsz, q_len, self.hidden_size).contiguous()
+        attn_output = self.o_proj(attn_output)
+
+        if not output_attentions:
+            attn_weights = None
+
+        return attn_output, attn_weights, past_key_value
+
+
+# Copied from transformers.models.mixtral.modeling_mixtral.MixtralSdpaAttention with Mixtral->Qwen2
+class Qwen2SdpaAttention(Qwen2Attention):
+    """
+    Qwen2 attention module using torch.nn.functional.scaled_dot_product_attention. This module inherits from
+    `Qwen2Attention` as the weights of the module stays untouched. The only changes are on the forward pass to adapt to
+    SDPA API.
+    """
+
+    # Adapted from Qwen2Attention.forward
+    def forward(
+        self,
+        hidden_states: torch.Tensor,
+        attention_mask: Optional[torch.Tensor] = None,
+        position_ids: Optional[torch.LongTensor] = None,
+        past_key_value: Optional[Cache] = None,
+        indicators: Optional[torch.LongTensor] = None,
+        output_attentions: bool = False,
+        use_cache: bool = False,
+        cache_position: Optional[torch.LongTensor] = None,
+    ) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[Tuple[torch.Tensor]]]:
+        if output_attentions:
+            # TODO: Improve this warning with e.g. `model.config.attn_implementation = "manual"` once this is implemented.
+            logger.warning_once(
+                "Qwen2Model is using Qwen2SdpaAttention, but `torch.nn.functional.scaled_dot_product_attention` does not support `output_attentions=True`. Falling back to the manual attention implementation, "
+                'but specifying the manual implementation will be required from Transformers version v5.0.0 onwards. This warning can be removed using the argument `attn_implementation="eager"` when loading the model.'
+            )
+            return super().forward(
+                hidden_states=hidden_states,
+                attention_mask=attention_mask,
+                position_ids=position_ids,
+                past_key_value=past_key_value,
+                output_attentions=output_attentions,
+                use_cache=use_cache,
+            )
+
+        bsz, q_len, _ = hidden_states.size()
+
+        query_states = self.q_proj(hidden_states)
+        key_states = self.k_proj(hidden_states)
+        value_states = self.v_proj(hidden_states)
+
+        query_states = query_states.view(bsz, q_len, self.num_heads, self.head_dim).transpose(1, 2)
+        key_states = key_states.view(bsz, q_len, self.num_key_value_heads, self.head_dim).transpose(1, 2)
+        value_states = value_states.view(bsz, q_len, self.num_key_value_heads, self.head_dim).transpose(1, 2)
+
+        kv_seq_len = key_states.shape[-2]
+        if past_key_value is not None:
+            kv_seq_len += past_key_value.get_usable_length(kv_seq_len, self.layer_idx)
+        cos, sin = self.rotary_emb(value_states, seq_len=kv_seq_len)
+
+        query_states, key_states = apply_rotary_pos_emb(query_states, key_states, cos, sin, position_ids)
+
+        if past_key_value is not None:
+            cache_kwargs = {"sin": sin, "cos": cos, "cache_position": cache_position}  # Specific to RoPE models
+            key_states, value_states = past_key_value.update(key_states, value_states, self.layer_idx, cache_kwargs)
+
+        key_states = repeat_kv(key_states, self.num_key_value_groups)
+        value_states = repeat_kv(value_states, self.num_key_value_groups)
+
+        causal_mask = attention_mask
+        if attention_mask is not None:  # no matter the length, we just slice it
+            causal_mask = attention_mask[:, :, :, : key_states.shape[-2]]
+
+        # SDPA with memory-efficient backend is currently (torch==2.1.2) bugged with non-contiguous inputs with custom attn_mask,
+        # Reference: https://github.com/pytorch/pytorch/issues/112577.
+        if query_states.device.type == "cuda" and attention_mask is not None:
+            query_states = query_states.contiguous()
+            key_states = key_states.contiguous()
+            value_states = value_states.contiguous()
+        
+        # stage 1 processing
+        # q k v batch head len channel
+        # indicators batch len
+        
+        # with torch.no_grad():
+        #     if causal_mask is None:
+        #         causal_mask = torch.ones(query_states.shape[-2], key_states.shape[-2], device=query_states.device)
+        #         causal_mask = torch.tril(causal_mask).unsqueeze(0).repeat([indicators.shape[0], 1, 1])
+        #         for batch_idx in range(indicators.shape[0]):
+        #             query_index = torch.where(indicators[batch_idx]==100)[0]
+        #             if len(query_index) == 0:
+        #                 continue
+        #             causal_mask[batch_idx, query_index[-1]+1:, :query_index[0]] = 0
+        #         causal_mask = causal_mask.unsqueeze(1).bool()
+        #     else:
+        #         # causal_mask batch 1 len len
+        #         causal_mask = torch.clone(causal_mask)
+        #         min_val = torch.min(causal_mask)
+        #         for batch_idx in range(indicators.shape[0]):
+        #             query_index = torch.where(indicators[batch_idx]==100)[0]
+        #             if len(query_index) == 0:
+        #                 continue
+        #             causal_mask[batch_idx, 0, query_index[-1]+1:, :query_index[0]] = min_val
+
+        # We dispatch to SDPA's Flash Attention or Efficient kernels via this `is_causal` if statement instead of an inline conditional assignment
+        # in SDPA to support both torch.compile's dynamic shapes and full graph options. An inline conditional prevents dynamic shapes from compiling.
+        # The q_len > 1 is necessary to match with AttentionMaskConverter.to_causal_4d that does not create a causal mask in case q_len == 1.
+        is_causal = True if causal_mask is None and q_len > 1 else False
+
+        attn_output = torch.nn.functional.scaled_dot_product_attention(
+            query_states,
+            key_states,
+            value_states,
+            attn_mask=causal_mask,
+            dropout_p=self.attention_dropout if self.training else 0.0,
+            is_causal=is_causal,
+        )
+
+        attn_output = attn_output.transpose(1, 2).contiguous()
+        attn_output = attn_output.view(bsz, q_len, self.hidden_size)
+
+        attn_output = self.o_proj(attn_output)
+
+        return attn_output, None, past_key_value
+
+
+QWEN2_ATTENTION_CLASSES = {
+    "eager": Qwen2Attention,
+    "flash_attention_2": Qwen2FlashAttention2,
+    "sdpa": Qwen2SdpaAttention,
+}
+
+
+class Qwen2DecoderLayer(nn.Module):
+    def __init__(self, config: Qwen2Config, layer_idx: int):
+        super().__init__()
+        self.hidden_size = config.hidden_size
+
+        # config._attn_implementation = 'flash_attention_2' # stage 2
+        if config.sliding_window and config._attn_implementation != "flash_attention_2":
+            logger.warning_once(
+                f"Sliding Window Attention is enabled but not implemented for `{config._attn_implementation}`; "
+                "unexpected results may be encountered."
+            )
+        self.self_attn = QWEN2_ATTENTION_CLASSES[config._attn_implementation](config, layer_idx)
+
+        self.mlp = Qwen2MLP(config)
+        self.input_layernorm = Qwen2RMSNorm(config.hidden_size, eps=config.rms_norm_eps)
+        self.post_attention_layernorm = Qwen2RMSNorm(config.hidden_size, eps=config.rms_norm_eps)
+
+    def forward(
+        self,
+        hidden_states: torch.Tensor,
+        attention_mask: Optional[torch.Tensor] = None,
+        position_ids: Optional[torch.LongTensor] = None,
+        past_key_value: Optional[Tuple[torch.Tensor]] = None,
+        indicators: Optional[torch.LongTensor] = None,
+        output_attentions: Optional[bool] = False,
+        use_cache: Optional[bool] = False,
+        cache_position: Optional[torch.LongTensor] = None,
+        **kwargs,
+    ) -> Tuple[torch.FloatTensor, Optional[Tuple[torch.FloatTensor, torch.FloatTensor]]]:
+        """
+        Args:
+            hidden_states (`torch.FloatTensor`): input to the layer of shape `(batch, seq_len, embed_dim)`
+            attention_mask (`torch.FloatTensor`, *optional*): attention mask of size
+                `(batch, sequence_length)` where padding elements are indicated by 0.
+            output_attentions (`bool`, *optional*):
+                Whether or not to return the attentions tensors of all attention layers. See `attentions` under
+                returned tensors for more detail.
+            use_cache (`bool`, *optional*):
+                If set to `True`, `past_key_values` key value states are returned and can be used to speed up decoding
+                (see `past_key_values`).
+            past_key_value (`Tuple(torch.FloatTensor)`, *optional*): cached past key and value projection states
+            cache_position (`torch.LongTensor` of shape `(sequence_length)`, *optional*):
+                Indices depicting the position of the input sequence tokens in the sequence.
+            kwargs (`dict`, *optional*):
+                Arbitrary kwargs to be ignored, used for FSDP and other methods that injects code
+                into the model
+        """
+
+        residual = hidden_states
+
+        hidden_states = self.input_layernorm(hidden_states)
+
+        # Self Attention
+        hidden_states, self_attn_weights, present_key_value = self.self_attn(
+            hidden_states=hidden_states,
+            attention_mask=attention_mask,
+            position_ids=position_ids,
+            past_key_value=past_key_value,
+            indicators=indicators,
+            output_attentions=output_attentions,
+            use_cache=use_cache,
+            cache_position=cache_position,
+        )
+        hidden_states = residual + hidden_states
+
+        # Fully Connected
+        residual = hidden_states
+        hidden_states = self.post_attention_layernorm(hidden_states)
+        hidden_states = self.mlp(hidden_states)
+        hidden_states = residual + hidden_states
+
+        outputs = (hidden_states,)
+
+        if output_attentions:
+            outputs += (self_attn_weights,)
+
+        if use_cache:
+            outputs += (present_key_value,)
+
+        return outputs
+
+
+QWEN2_START_DOCSTRING = r"""
+    This model inherits from [`PreTrainedModel`]. Check the superclass documentation for the generic methods the
+    library implements for all its model (such as downloading or saving, resizing the input embeddings, pruning heads
+    etc.)
+
+    This model is also a PyTorch [torch.nn.Module](https://pytorch.org/docs/stable/nn.html#torch.nn.Module) subclass.
+    Use it as a regular PyTorch Module and refer to the PyTorch documentation for all matter related to general usage
+    and behavior.
+
+    Parameters:
+        config ([`Qwen2Config`]):
+            Model configuration class with all the parameters of the model. Initializing with a config file does not
+            load the weights associated with the model, only the configuration. Check out the
+            [`~PreTrainedModel.from_pretrained`] method to load the model weights.
+"""
+
+
+@add_start_docstrings(
+    "The bare Qwen2 Model outputting raw hidden-states without any specific head on top.",
+    QWEN2_START_DOCSTRING,
+)
+class Qwen2PreTrainedModel(PreTrainedModel):
+    config_class = Qwen2Config
+    base_model_prefix = "model"
+    supports_gradient_checkpointing = True
+    _no_split_modules = ["Qwen2DecoderLayer"]
+    _skip_keys_device_placement = "past_key_values"
+    _supports_flash_attn_2 = True
+    _supports_sdpa = True
+    _supports_cache_class = True
+
+    def _init_weights(self, module):
+        std = self.config.initializer_range
+        if isinstance(module, nn.Linear):
+            module.weight.data.normal_(mean=0.0, std=std)
+            if module.bias is not None:
+                module.bias.data.zero_()
+        elif isinstance(module, nn.Embedding):
+            module.weight.data.normal_(mean=0.0, std=std)
+            if module.padding_idx is not None:
+                module.weight.data[module.padding_idx].zero_()
+
+
+QWEN2_INPUTS_DOCSTRING = r"""
+    Args:
+        input_ids (`torch.LongTensor` of shape `(batch_size, sequence_length)`):
+            Indices of input sequence tokens in the vocabulary. Padding will be ignored by default should you provide
+            it.
+
+            Indices can be obtained using [`AutoTokenizer`]. See [`PreTrainedTokenizer.encode`] and
+            [`PreTrainedTokenizer.__call__`] for details.
+
+            [What are input IDs?](../glossary#input-ids)
+        attention_mask (`torch.Tensor` of shape `(batch_size, sequence_length)`, *optional*):
+            Mask to avoid performing attention on padding token indices. Mask values selected in `[0, 1]`:
+
+            - 1 for tokens that are **not masked**,
+            - 0 for tokens that are **masked**.
+
+            [What are attention masks?](../glossary#attention-mask)
+
+            Indices can be obtained using [`AutoTokenizer`]. See [`PreTrainedTokenizer.encode`] and
+            [`PreTrainedTokenizer.__call__`] for details.
+
+            If `past_key_values` is used, optionally only the last `decoder_input_ids` have to be input (see
+            `past_key_values`).
+
+            If you want to change padding behavior, you should read [`modeling_opt._prepare_decoder_attention_mask`]
+            and modify to your needs. See diagram 1 in [the paper](https://arxiv.org/abs/1910.13461) for more
+            information on the default strategy.
+
+            - 1 indicates the head is **not masked**,
+            - 0 indicates the head is **masked**.
+        position_ids (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*):
+            Indices of positions of each input sequence tokens in the position embeddings. Selected in the range `[0,
+            config.n_positions - 1]`.
+
+            [What are position IDs?](../glossary#position-ids)
+        past_key_values (`Cache` or `tuple(tuple(torch.FloatTensor))`, *optional*):
+            Pre-computed hidden-states (key and values in the self-attention blocks and in the cross-attention
+            blocks) that can be used to speed up sequential decoding. This typically consists in the `past_key_values`
+            returned by the model at a previous stage of decoding, when `use_cache=True` or `config.use_cache=True`.
+
+            Two formats are allowed:
+            - a [`~cache_utils.Cache`] instance;
+            - Tuple of `tuple(torch.FloatTensor)` of length `config.n_layers`, with each tuple having 2 tensors of
+            shape `(batch_size, num_heads, sequence_length, embed_size_per_head)`). This is also known as the legacy
+            cache format.
+
+            The model will output the same cache format that is fed as input. If no `past_key_values` are passed, the
+            legacy cache format will be returned.
+
+            If `past_key_values` are used, the user can optionally input only the last `input_ids` (those that don't
+            have their past key value states given to this model) of shape `(batch_size, 1)` instead of all `input_ids`
+            of shape `(batch_size, sequence_length)`.
+        inputs_embeds (`torch.FloatTensor` of shape `(batch_size, sequence_length, hidden_size)`, *optional*):
+            Optionally, instead of passing `input_ids` you can choose to directly pass an embedded representation. This
+            is useful if you want more control over how to convert `input_ids` indices into associated vectors than the
+            model's internal embedding lookup matrix.
+        use_cache (`bool`, *optional*):
+            If set to `True`, `past_key_values` key value states are returned and can be used to speed up decoding (see
+            `past_key_values`).
+        output_attentions (`bool`, *optional*):
+            Whether or not to return the attentions tensors of all attention layers. See `attentions` under returned
+            tensors for more detail.
+        output_hidden_states (`bool`, *optional*):
+            Whether or not to return the hidden states of all layers. See `hidden_states` under returned tensors for
+            more detail.
+        return_dict (`bool`, *optional*):
+            Whether or not to return a [`~utils.ModelOutput`] instead of a plain tuple.
+        cache_position (`torch.LongTensor` of shape `(sequence_length)`, *optional*):
+            Indices depicting the position of the input sequence tokens in the sequence. Contrarily to `position_ids`,
+            this tensor is not affected by padding. It is used to update the cache in the correct position and to infer
+            the complete sequence length.
+"""
+
+
+@add_start_docstrings(
+    "The bare Qwen2 Model outputting raw hidden-states without any specific head on top.",
+    QWEN2_START_DOCSTRING,
+)
+class Qwen2Model(Qwen2PreTrainedModel):
+    """
+    Transformer decoder consisting of *config.num_hidden_layers* layers. Each layer is a [`Qwen2DecoderLayer`]
+
+    Args:
+        config: Qwen2Config
+    """
+
+    def __init__(self, config: Qwen2Config):
+        super().__init__(config)
+        self.padding_idx = config.pad_token_id
+        self.vocab_size = config.vocab_size
+
+        self.embed_tokens = nn.Embedding(config.vocab_size, config.hidden_size, self.padding_idx)
+        self.layers = nn.ModuleList(
+            [Qwen2DecoderLayer(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]
+        )
+        self._attn_implementation = config._attn_implementation
+        self.norm = Qwen2RMSNorm(config.hidden_size, eps=config.rms_norm_eps)
+
+        self.gradient_checkpointing = False
+        # Initialize weights and apply final processing
+        self.post_init()
+
+    def get_input_embeddings(self):
+        return self.embed_tokens
+
+    def set_input_embeddings(self, value):
+        self.embed_tokens = value
+
+    @add_start_docstrings_to_model_forward(QWEN2_INPUTS_DOCSTRING)
+    def forward(
+        self,
+        input_ids: torch.LongTensor = None,
+        attention_mask: Optional[torch.Tensor] = None,
+        position_ids: Optional[torch.LongTensor] = None,
+        past_key_values: Optional[List[torch.FloatTensor]] = None,
+        inputs_embeds: Optional[torch.FloatTensor] = None,
+        indicators: Optional[torch.LongTensor] = None,
+        use_cache: Optional[bool] = None,
+        output_attentions: Optional[bool] = None,
+        output_hidden_states: Optional[bool] = None,
+        return_dict: Optional[bool] = None,
+        cache_position: Optional[torch.LongTensor] = None,
+        select_layer: Optional[int] = None,
+    ) -> Union[Tuple, BaseModelOutputWithPast]:
+        output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions
+        output_hidden_states = (
+            output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
+        )
+        use_cache = use_cache if use_cache is not None else self.config.use_cache
+
+        return_dict = return_dict if return_dict is not None else self.config.use_return_dict
+
+        if (input_ids is None) ^ (inputs_embeds is not None):
+            raise ValueError(
+                "You cannot specify both input_ids and inputs_embeds at the same time, and must specify either one"
+            )
+
+        if self.gradient_checkpointing and self.training:
+            if use_cache:
+                logger.warning_once(
+                    "`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`..."
+                )
+                use_cache = False
+
+        use_legacy_cache = False
+        if use_cache and not isinstance(past_key_values, Cache) and not self.training:
+            use_legacy_cache = True
+            past_key_values = DynamicCache.from_legacy_cache(past_key_values)
+            logger.warning_once(
+                "We detected that you are passing `past_key_values` as a tuple and this is deprecated and will be removed in v4.43. "
+                "Please use an appropriate `Cache` class (https://huggingface.co/docs/transformers/v4.41.3/en/internal/generation_utils#transformers.Cache)"
+            )
+
+        if inputs_embeds is None:
+            inputs_embeds = self.embed_tokens(input_ids)
+
+        if cache_position is None:
+            past_seen_tokens = past_key_values.get_seq_length() if past_key_values is not None else 0
+            cache_position = torch.arange(
+                past_seen_tokens, past_seen_tokens + inputs_embeds.shape[1], device=inputs_embeds.device
+            )
+        if position_ids is None:
+            position_ids = cache_position.unsqueeze(0)
+
+        causal_mask = self._update_causal_mask(
+            attention_mask, inputs_embeds, cache_position, past_key_values, output_attentions
+        )
+
+        hidden_states = inputs_embeds
+
+        # decoder layers
+        all_hidden_states = () if output_hidden_states else None
+        all_self_attns = () if output_attentions else None
+        next_decoder_cache = None
+
+        for i, decoder_layer in enumerate(self.layers):
+            if output_hidden_states:
+                all_hidden_states += (hidden_states,)
+
+            if self.gradient_checkpointing and self.training:
+                layer_outputs = self._gradient_checkpointing_func(
+                    decoder_layer.__call__,
+                    hidden_states,
+                    causal_mask,
+                    position_ids,
+                    past_key_values,
+                    indicators,
+                    output_attentions,
+                    use_cache,
+                    cache_position,
+                )
+            else:
+                layer_outputs = decoder_layer(
+                    hidden_states,
+                    attention_mask=causal_mask,
+                    position_ids=position_ids,
+                    past_key_value=past_key_values,
+                    indicators=indicators,
+                    output_attentions=output_attentions,
+                    use_cache=use_cache,
+                    cache_position=cache_position,
+                )
+
+            hidden_states = layer_outputs[0]
+
+            if use_cache:
+                next_decoder_cache = layer_outputs[2 if output_attentions else 1]
+
+            if output_attentions:
+                all_self_attns += (layer_outputs[1],)
+
+            if select_layer is not None:
+                if i == select_layer:
+                    break
+
+        hidden_states = self.norm(hidden_states)
+
+        # add hidden states from the last decoder layer
+        if output_hidden_states:
+            all_hidden_states += (hidden_states,)
+
+        next_cache = None
+        if use_cache:
+            next_cache = next_decoder_cache.to_legacy_cache() if use_legacy_cache else next_decoder_cache
+
+        if not return_dict:
+            return tuple(v for v in [hidden_states, next_cache, all_hidden_states, all_self_attns] if v is not None)
+        return BaseModelOutputWithPast(
+            last_hidden_state=hidden_states,
+            past_key_values=next_cache,
+            hidden_states=all_hidden_states,
+            attentions=all_self_attns,
+        )
+
+    # Copied from transformers.models.llama.modeling_llama.LlamaModel._update_causal_mask
+    def _update_causal_mask(
+        self,
+        attention_mask: torch.Tensor,
+        input_tensor: torch.Tensor,
+        cache_position: torch.Tensor,
+        past_key_values: Cache,
+        output_attentions: bool,
+    ):
+        # TODO: As of torch==2.2.0, the `attention_mask` passed to the model in `generate` is 2D and of dynamic length even when the static
+        # KV cache is used. This is an issue for torch.compile which then recaptures cudagraphs at each decode steps due to the dynamic shapes.
+        # (`recording cudagraph tree for symint key 13`, etc.), which is VERY slow. A workaround is `@torch.compiler.disable`, but this prevents using
+        # `fullgraph=True`. See more context in https://github.com/huggingface/transformers/pull/29114
+
+        if self.config._attn_implementation == "flash_attention_2":
+            if attention_mask is not None and 0.0 in attention_mask:
+                return attention_mask
+            return None
+
+        # For SDPA, when possible, we will rely on its `is_causal` argument instead of its `attn_mask` argument, in
+        # order to dispatch on Flash Attention 2. This feature is not compatible with static cache, as SDPA will fail
+        # to infer the attention mask.
+        past_seen_tokens = past_key_values.get_seq_length() if past_key_values is not None else 0
+        using_static_cache = isinstance(past_key_values, StaticCache)
+
+        # When output attentions is True, sdpa implementation's forward method calls the eager implementation's forward
+        if self.config._attn_implementation == "sdpa" and not using_static_cache and not output_attentions:
+            if AttentionMaskConverter._ignore_causal_mask_sdpa(
+                attention_mask,
+                inputs_embeds=input_tensor,
+                past_key_values_length=past_seen_tokens,
+                is_training=self.training,
+            ):
+                return None
+
+        dtype, device = input_tensor.dtype, input_tensor.device
+        min_dtype = torch.finfo(dtype).min
+        sequence_length = input_tensor.shape[1]
+        if using_static_cache:
+            target_length = past_key_values.get_max_length()
+        else:
+            target_length = (
+                attention_mask.shape[-1]
+                if isinstance(attention_mask, torch.Tensor)
+                else past_seen_tokens + sequence_length + 1
+            )
+
+        if attention_mask is not None and attention_mask.dim() == 4:
+            # in this case we assume that the mask comes already in inverted form and requires no inversion or slicing
+            if attention_mask.max() != 0:
+                raise ValueError("Custom 4D attention mask should be passed in inverted form with max==0`")
+            causal_mask = attention_mask
+        else:
+            causal_mask = torch.full(
+                (sequence_length, target_length), fill_value=min_dtype, dtype=dtype, device=device
+            )
+            if sequence_length != 1:
+                causal_mask = torch.triu(causal_mask, diagonal=1)
+            causal_mask *= torch.arange(target_length, device=device) > cache_position.reshape(-1, 1)
+            causal_mask = causal_mask[None, None, :, :].expand(input_tensor.shape[0], 1, -1, -1)
+            if attention_mask is not None:
+                causal_mask = causal_mask.clone()  # copy to contiguous memory for in-place edit
+                mask_length = attention_mask.shape[-1]
+                padding_mask = causal_mask[:, :, :, :mask_length] + attention_mask[:, None, None, :]
+                padding_mask = padding_mask == 0
+                causal_mask[:, :, :, :mask_length] = causal_mask[:, :, :, :mask_length].masked_fill(
+                    padding_mask, min_dtype
+                )
+        if (
+            self.config._attn_implementation == "sdpa"
+            and attention_mask is not None
+            and attention_mask.device.type == "cuda"
+            and not output_attentions
+        ):
+            # Attend to all tokens in fully masked rows in the causal_mask, for example the relevant first rows when
+            # using left padding. This is required by F.scaled_dot_product_attention memory-efficient attention path.
+            # Details: https://github.com/pytorch/pytorch/issues/110213
+            causal_mask = AttentionMaskConverter._unmask_unattended(causal_mask, min_dtype)
+
+        return causal_mask
+
+
+class Qwen2ForCausalLM(Qwen2PreTrainedModel):
+    _tied_weights_keys = ["lm_head.weight"]
+
+    def __init__(self, config):
+        super().__init__(config)
+        self.model = Qwen2Model(config)
+        self.vocab_size = config.vocab_size
+        self.lm_head = nn.Linear(config.hidden_size, config.vocab_size, bias=False)
+
+        # Initialize weights and apply final processing
+        self.post_init()
+
+    def get_input_embeddings(self):
+        return self.model.embed_tokens
+
+    def set_input_embeddings(self, value):
+        self.model.embed_tokens = value
+
+    def get_output_embeddings(self):
+        return self.lm_head
+
+    def set_output_embeddings(self, new_embeddings):
+        self.lm_head = new_embeddings
+
+    def set_decoder(self, decoder):
+        self.model = decoder
+
+    def get_decoder(self):
+        return self.model
+
+    def forward_grounding_hm(
+        self,
+        input_ids: torch.LongTensor,
+        past_key_values: Optional[List[torch.FloatTensor]] = None,
+        inputs_embeds: Optional[torch.FloatTensor] = None,
+        clip_embeds: Optional[torch.FloatTensor] = None,
+        attention_mask: Optional[torch.BoolTensor] = None,
+        qs_embeds: Optional[torch.FloatTensor] = None,
+        qs_mask: Optional[torch.BoolTensor] = None,
+        labels: Optional[torch.LongTensor] = None,
+        time_labels: Optional[torch.FloatTensor] = None,
+        indicators: Optional[torch.LongTensor] = None,
+        return_simi: Optional[bool] = False,
+        select_layer: Optional[int] = None,
+        **kwargs,
+    ) -> torch.FloatTensor:
+        block_size = 1
+        n_seq = inputs_embeds.shape[0]
+
+        global_embeds = []
+        global_masks = []
+        global_indicators = []
+        global_embeds.append(inputs_embeds)
+        global_masks.append(attention_mask)
+        global_indicators.append(indicators)
+        with torch.no_grad():
+            outputs = self.model(input_ids, inputs_embeds=inputs_embeds, past_key_values=past_key_values, attention_mask=attention_mask, indicators=indicators, select_layer=select_layer)
+            hidden_states = outputs[0]
+            clip_memory = hidden_states[indicators==100]
+            full_time = hidden_states[indicators==200]
+        with torch.no_grad():
+            memory_embeds = torch.cat([clip_memory, full_time], dim=0).unsqueeze(0)
+            memory_mask = torch.ones_like(memory_embeds[:, :, 0])
+            memory_indicator = torch.ones_like(memory_embeds[:, :, 0])
+            outputs = self.model(input_ids, inputs_embeds=memory_embeds, attention_mask=memory_mask, indicators=memory_indicator, select_layer=select_layer)
+            hidden_states = outputs[0]
+            global_memory = hidden_states[0, -full_time.shape[0]:]
+
+        n_qs = qs_embeds.shape[0]
+        new_embeds = []
+        new_masks = []
+        new_indicators = []
+        for batch_idx in range(qs_embeds.shape[0]):
+            new_embeds.append(torch.cat([global_memory, qs_embeds[batch_idx]], dim=0)) # n+k c
+            new_mask = torch.cat([torch.ones(global_memory.shape[0], dtype=qs_mask.dtype, device=qs_mask.device), qs_mask[batch_idx]], dim=0)
+            indicator = torch.zeros_like(new_mask)
+            indicator[torch.where(new_mask==1)[0][-1]] = 1
+            new_masks.append(new_mask)
+            new_indicators.append(indicator)
+        current_embeds = torch.stack(new_embeds, dim=0)
+        current_mask = torch.stack(new_masks, dim=0)
+        current_indicators = torch.stack(new_indicators, dim=0)
+        global_embeds.append(current_embeds)
+        global_masks.append(current_mask)
+        global_indicators.append(current_indicators)
+
+        max_len = max(x.shape[1] for x in global_embeds)
+        for i in range(len(global_embeds)):
+            embed_padded = torch.zeros(
+                (global_embeds[i].shape[0], max_len-global_embeds[i].shape[1], global_embeds[i].shape[-1]),
+                dtype=global_embeds[i].dtype,
+                device=global_embeds[i].device
+            )
+            global_embeds[i] = torch.cat([global_embeds[i], embed_padded], dim=1)
+            mask_padded = torch.zeros(
+                (global_masks[i].shape[0], max_len-global_masks[i].shape[1]),
+                dtype=global_masks[i].dtype,
+                device=global_masks[i].device
+            )
+            global_masks[i] = torch.cat([global_masks[i], mask_padded], dim=1)
+            indicator_padded = torch.zeros(
+                (global_indicators[i].shape[0], max_len-global_indicators[i].shape[1]),
+                dtype=global_indicators[i].dtype,
+                device=global_indicators[i].device
+            )
+            global_indicators[i] = torch.cat([global_indicators[i], indicator_padded], dim=1)
+        global_embeds = torch.cat(global_embeds, dim=0) # nv+nq k c
+        global_masks = torch.cat(global_masks, dim=0)
+        global_indicators = torch.cat(global_indicators, dim=0)
+        outputs = self.model(input_ids, inputs_embeds=global_embeds, attention_mask=global_masks, indicators=global_indicators, select_layer=select_layer)
+        final_states = outputs[0]
+
+        full_time = []
+        full_qs = []
+        for i in range(n_seq):
+            time = final_states[i][global_indicators[i]==200]
+            full_time.append(time)
+        for i in range(n_qs):
+            qs_token = final_states[i+n_seq][global_indicators[i+n_seq]==1]
+            full_qs.append(qs_token)
+        full_time = torch.cat(full_time, dim=0) # nv c
+        full_qs = torch.cat(full_qs, dim=0) # nq c
+        # print(full_time.shape, full_qs.shape)
+        full_time = torch.nn.functional.normalize(full_time, dim=1, p=2)
+        full_qs = torch.nn.functional.normalize(full_qs, dim=1, p=2)
+        similarity = torch.einsum('qc,nc->qn', full_qs, full_time) # q n
+        if return_simi:
+            return 0.0, similarity, global_memory, clip_memory
+        similarity = torch.softmax(similarity/0.1, dim=-1)
+        loss = - torch.sum(time_labels*torch.log(similarity+1e-4), dim=-1).mean() - 0.01*torch.sum(similarity*torch.log(similarity+1e-4), dim=-1).mean() if time_labels is not None else 0*(-torch.sum(similarity*torch.log(similarity+1e-4), dim=-1).mean())
+
+        return loss, similarity, global_memory, clip_memory
+
+    def forward_token(
+        self,
+        input_ids: torch.LongTensor,
+        past_key_values: Optional[List[torch.FloatTensor]] = None,
+        inputs_embeds: Optional[torch.FloatTensor] = None,
+        clip_embeds: Optional[torch.FloatTensor] = None,
+        attention_mask: Optional[torch.BoolTensor] = None,
+        qs_embeds: Optional[torch.FloatTensor] = None,
+        qs_mask: Optional[torch.BoolTensor] = None,
+        labels: Optional[torch.LongTensor] = None,
+        time_labels: Optional[torch.FloatTensor] = None,
+        indicators: Optional[torch.LongTensor] = None,
+        select_layer: Optional[int] = None,
+        **kwargs,
+    ) -> torch.FloatTensor:
+
+        if self.training and qs_embeds is None: # caption only
+            block_size = 1
+            n_seq = inputs_embeds.shape[0]
+            global_embeds = []
+            global_masks = []
+            global_indicators = []
+            global_embeds.append(inputs_embeds)
+            global_masks.append(attention_mask)
+            global_indicators.append(indicators)
+            with torch.no_grad():
+                outputs = self.model(input_ids, inputs_embeds=inputs_embeds, past_key_values=past_key_values, attention_mask=attention_mask, indicators=indicators, select_layer=select_layer)
+                hidden_states = outputs[0]
+                clip_memory = hidden_states[indicators==100] # nseq*k c
+                full_time = hidden_states[indicators==200] # nseq c
+            with torch.no_grad():
+                memory_embeds = torch.cat([clip_memory, full_time], dim=0).unsqueeze(0)
+                memory_mask = torch.ones_like(memory_embeds[:, :, 0])
+                memory_indicator = torch.ones_like(memory_embeds[:, :, 0])
+                memory_indicator[:, -full_time.shape[0]:] = 150
+                global_embeds.append(memory_embeds)
+                global_indicators.append(memory_indicator)
+                global_masks.append(memory_mask)
+            
+            max_len = max(x.shape[1] for x in global_embeds)
+            for i in range(len(global_embeds)):
+                embed_padded = torch.zeros(
+                    (global_embeds[i].shape[0], max_len-global_embeds[i].shape[1], global_embeds[i].shape[-1]),
+                    dtype=global_embeds[i].dtype,
+                    device=global_embeds[i].device
+                )
+                global_embeds[i] = torch.cat([global_embeds[i], embed_padded], dim=1)
+                mask_padded = torch.zeros(
+                    (global_masks[i].shape[0], max_len-global_masks[i].shape[1]),
+                    dtype=global_masks[i].dtype,
+                    device=global_masks[i].device
+                )
+                global_masks[i] = torch.cat([global_masks[i], mask_padded], dim=1)
+                indicator_padded = torch.zeros(
+                    (global_indicators[i].shape[0], max_len-global_indicators[i].shape[1]),
+                    dtype=global_indicators[i].dtype,
+                    device=global_indicators[i].device
+                )
+                global_indicators[i] = torch.cat([global_indicators[i], indicator_padded], dim=1)
+            global_embeds = torch.cat(global_embeds, dim=0) # nv k c
+            global_masks = torch.cat(global_masks, dim=0)
+            global_indicators = torch.cat(global_indicators, dim=0)
+
+            outputs = self.model(input_ids, inputs_embeds=global_embeds, attention_mask=global_masks, indicators=global_indicators, select_layer=select_layer)
+            final_states = outputs[0]
+            full_memory = []
+            full_time = []
+            for i in range(n_seq):
+                memory = final_states[i][global_indicators[i]==100] # k c
+                time = final_states[i][global_indicators[i]==200]
+                full_memory.append(memory)
+                full_time.append(time)
+            global_memory = final_states[n_seq][global_indicators[n_seq]==150] # nseq c
+            full_memory = torch.stack(full_memory, dim=0) # nv k c
+            select_memory = full_memory[-4:] # 4 k c
+            select_clip = clip_embeds[-4:]
+            select_memory = select_memory.unsqueeze(0) # 1 4 k c
+            select_clip = select_clip.unsqueeze(0)
+            global_memory = global_memory.unsqueeze(0) # 1 nseq c
+            return select_memory, select_clip, global_memory, 0, 0
+        elif self.training and False: # caption and grounding
+            block_size = 1
+            n_seq = inputs_embeds.shape[0]
+            global_embeds = []
+            global_masks = []
+            global_indicators = []
+            global_embeds.append(inputs_embeds)
+            global_masks.append(attention_mask)
+            global_indicators.append(indicators)
+            with torch.no_grad():
+                outputs = self.model(input_ids, inputs_embeds=inputs_embeds, past_key_values=past_key_values, attention_mask=attention_mask, indicators=indicators, select_layer=select_layer)
+                hidden_states = outputs[0]
+                clip_memory = hidden_states[indicators==100] # nseq*k c
+                full_time = hidden_states[indicators==200] # nseq c
+            with torch.no_grad():
+                memory_embeds = torch.cat([clip_memory, full_time], dim=0).unsqueeze(0)
+                memory_mask = torch.ones_like(memory_embeds[:, :, 0])
+                memory_indicator = torch.ones_like(memory_embeds[:, :, 0])
+                memory_indicator[:, -full_time.shape[0]:] = 150
+                global_embeds.append(memory_embeds)
+                global_indicators.append(memory_indicator)
+                global_masks.append(memory_mask)
+                outputs = self.model(input_ids, inputs_embeds=memory_embeds, attention_mask=memory_mask, indicators=memory_indicator, select_layer=select_layer)
+                hidden_states = outputs[0]
+                global_memory = hidden_states[0, -full_time.shape[0]:] # nseq c
+
+            n_qs = qs_embeds.shape[0]
+            new_embeds = []
+            new_masks = []
+            new_indicators = []
+            for batch_idx in range(qs_embeds.shape[0]):
+                new_embeds.append(torch.cat([global_memory, qs_embeds[batch_idx]], dim=0)) # n+k c
+                new_mask = torch.cat([torch.ones(global_memory.shape[0], dtype=qs_mask.dtype, device=qs_mask.device), qs_mask[batch_idx]], dim=0)
+                indicator = torch.zeros_like(new_mask)
+                indicator[torch.where(new_mask==1)[0][-1]] = 1
+                new_masks.append(new_mask)
+                new_indicators.append(indicator)
+            current_embeds = torch.stack(new_embeds, dim=0)
+            current_mask = torch.stack(new_masks, dim=0)
+            current_indicators = torch.stack(new_indicators, dim=0)
+            global_embeds.append(current_embeds)
+            global_masks.append(current_mask)
+            global_indicators.append(current_indicators)
+            max_len = max(x.shape[1] for x in global_embeds)
+            for i in range(len(global_embeds)):
+                embed_padded = torch.zeros(
+                    (global_embeds[i].shape[0], max_len-global_embeds[i].shape[1], global_embeds[i].shape[-1]),
+                    dtype=global_embeds[i].dtype,
+                    device=global_embeds[i].device
+                )
+                global_embeds[i] = torch.cat([global_embeds[i], embed_padded], dim=1)
+                mask_padded = torch.zeros(
+                    (global_masks[i].shape[0], max_len-global_masks[i].shape[1]),
+                    dtype=global_masks[i].dtype,
+                    device=global_masks[i].device
+                )
+                global_masks[i] = torch.cat([global_masks[i], mask_padded], dim=1)
+                indicator_padded = torch.zeros(
+                    (global_indicators[i].shape[0], max_len-global_indicators[i].shape[1]),
+                    dtype=global_indicators[i].dtype,
+                    device=global_indicators[i].device
+                )
+                global_indicators[i] = torch.cat([global_indicators[i], indicator_padded], dim=1)
+            global_embeds = torch.cat(global_embeds, dim=0) # nv+1+nq k c
+            global_masks = torch.cat(global_masks, dim=0)
+            global_indicators = torch.cat(global_indicators, dim=0)
+            outputs = self.model(input_ids, inputs_embeds=global_embeds, attention_mask=global_masks, indicators=global_indicators, select_layer=select_layer)
+            final_states = outputs[0]
+            full_memory = []
+            full_time = []
+            full_qs = []
+            for i in range(n_seq):
+                memory = final_states[i][global_indicators[i]==100] # k c
+                time = final_states[i][global_indicators[i]==200]
+                full_memory.append(memory)
+                full_time.append(time)
+            global_memory = final_states[n_seq][global_indicators[n_seq]==150] # nseq c
+            for i in range(n_qs):
+                qs_token = final_states[i+n_seq+1][global_indicators[i+n_seq+1]==1]
+                full_qs.append(qs_token)
+            full_memory = torch.stack(full_memory, dim=0) # nv k c
+            full_time = torch.cat(full_time, dim=0) # nv c
+            full_qs = torch.cat(full_qs, dim=0) # nq c
+            full_time = torch.nn.functional.normalize(full_time, dim=1, p=2)
+            full_qs = torch.nn.functional.normalize(full_qs, dim=1, p=2)
+            similarity = torch.einsum('qc,nc->qn', full_qs, full_time) # q n
+            similarity = torch.softmax(similarity/0.1, dim=-1)
+            loss = - torch.sum(time_labels*torch.log(similarity+1e-4), dim=-1).mean() - 0.01*torch.sum(similarity*torch.log(similarity+1e-4), dim=-1).mean() if time_labels is not None else 0*(-torch.sum(similarity*torch.log(similarity+1e-4), dim=-1).mean())
+            select_index = torch.topk(similarity, dim=-1, k=min(4, full_time.shape[0]))[1] # q k
+            select_index = select_index.sort(dim=-1)[0]
+            # print(similarity, time_labels, select_index, loss)
+            select_memory = full_memory[-4:] # 4 k c
+            select_clip = clip_embeds[-4:]
+            select_memory = select_memory.unsqueeze(0) # 1 4 k c
+            select_clip = select_clip.unsqueeze(0)
+            global_memory = global_memory.unsqueeze(0)
+            return select_memory, select_clip, global_memory, loss, similarity
+        elif self.training and True: # video qa only train llm
+            block_size = 1
+            n_seq = inputs_embeds.shape[0]
+            outputs = self.model(input_ids, inputs_embeds=inputs_embeds, past_key_values=past_key_values, attention_mask=attention_mask, indicators=indicators, select_layer=select_layer)
+            hidden_states = outputs[0]
+            clip_memory = hidden_states[indicators==100] # nseq*k c
+            full_memory = clip_memory.view(n_seq, -1, hidden_states.shape[-1]) # nseq k c
+            full_time = hidden_states[indicators==200].view(n_seq, hidden_states.shape[-1]) # nseq c
+            memory_embeds = torch.cat([clip_memory, full_time], dim=0).unsqueeze(0)
+            memory_mask = torch.ones_like(memory_embeds[:, :, 0])
+            memory_indicator = torch.ones_like(memory_embeds[:, :, 0])
+            outputs = self.model(input_ids, inputs_embeds=memory_embeds, attention_mask=memory_mask, indicators=memory_indicator, select_layer=select_layer)
+            hidden_states = outputs[0]
+            global_memory = hidden_states[0, -full_time.shape[0]:] # nseq c
+
+            n_qs = qs_embeds.shape[0]
+            new_embeds = []
+            new_masks = []
+            new_indicators = []
+            for batch_idx in range(qs_embeds.shape[0]):
+                new_embeds.append(torch.cat([global_memory, qs_embeds[batch_idx]], dim=0)) # n+k c
+                new_mask = torch.cat([torch.ones(global_memory.shape[0], dtype=qs_mask.dtype, device=qs_mask.device), qs_mask[batch_idx]], dim=0)
+                indicator = torch.zeros_like(new_mask)
+                indicator[torch.where(new_mask==1)[0][-1]] = 1
+                new_masks.append(new_mask)
+                new_indicators.append(indicator)
+            current_embeds = torch.stack(new_embeds, dim=0)
+            current_mask = torch.stack(new_masks, dim=0)
+            current_indicators = torch.stack(new_indicators, dim=0)
+            outputs = self.model(input_ids, inputs_embeds=current_embeds, attention_mask=current_mask, indicators=current_indicators, select_layer=select_layer)
+            current_states = outputs[0]
+            full_qs = current_states[current_indicators==1] # q c
+            # print(full_memory.shape, full_time.shape, full_qs.shape)
+
+            full_time = torch.nn.functional.normalize(full_time, dim=1, p=2)
+            full_qs = torch.nn.functional.normalize(full_qs, dim=1, p=2)
+            similarity = torch.einsum('qc,nc->qn', full_qs, full_time) # q n
+            similarity = torch.softmax(similarity/0.1, dim=-1)
+            select_index = torch.topk(similarity, dim=-1, k=min(4, full_time.shape[0]))[1] # q k
+            select_index = select_index.sort(dim=-1)[0]
+            select_memory = []
+            select_clip = []
+            for batch_idx in range(n_qs):
+                memory = full_memory[select_index[batch_idx]] # k k c
+                clip = clip_embeds[select_index[batch_idx]]
+                select_clip.append(clip)
+                select_memory.append(memory)
+            select_memory = torch.stack(select_memory, dim=0) # q k n c
+            select_clip = torch.stack(select_clip, dim=0)
+            global_memory = global_memory.unsqueeze(0).repeat([n_qs, 1, 1])
+            return select_memory, select_clip, global_memory, 0, similarity
+        else: # inference
+            block_size = 1
+            n_seq = inputs_embeds.shape[0]
+            outputs = self.model(input_ids, inputs_embeds=inputs_embeds, past_key_values=past_key_values, attention_mask=attention_mask, indicators=indicators, select_layer=select_layer)
+            hidden_states = outputs[0]
+            clip_memory = hidden_states[indicators==100] # nseq*k c
+            full_memory = clip_memory.view(n_seq, -1, hidden_states.shape[-1]) # nseq k c
+            full_time = hidden_states[indicators==200].view(n_seq, hidden_states.shape[-1]) # nseq c
+            memory_embeds = torch.cat([clip_memory, full_time], dim=0).unsqueeze(0)
+            memory_mask = torch.ones_like(memory_embeds[:, :, 0])
+            memory_indicator = torch.ones_like(memory_embeds[:, :, 0])
+            outputs = self.model(input_ids, inputs_embeds=memory_embeds, attention_mask=memory_mask, indicators=memory_indicator, select_layer=select_layer)
+            hidden_states = outputs[0]
+            global_memory = hidden_states[0, -full_time.shape[0]:] # nseq c
+
+            n_qs = qs_embeds.shape[0]
+            new_embeds = []
+            new_masks = []
+            new_indicators = []
+            for batch_idx in range(qs_embeds.shape[0]):
+                new_embeds.append(torch.cat([global_memory, qs_embeds[batch_idx]], dim=0)) # n+k c
+                new_mask = torch.cat([torch.ones(global_memory.shape[0], dtype=qs_mask.dtype, device=qs_mask.device), qs_mask[batch_idx]], dim=0)
+                indicator = torch.zeros_like(new_mask)
+                indicator[torch.where(new_mask==1)[0][-1]] = 1
+                new_masks.append(new_mask)
+                new_indicators.append(indicator)
+            current_embeds = torch.stack(new_embeds, dim=0)
+            current_mask = torch.stack(new_masks, dim=0)
+            current_indicators = torch.stack(new_indicators, dim=0)
+            outputs = self.model(input_ids, inputs_embeds=current_embeds, attention_mask=current_mask, indicators=current_indicators, select_layer=select_layer)
+            current_states = outputs[0]
+            full_qs = current_states[current_indicators==1] # q c
+            # print(full_memory.shape, full_time.shape, full_qs.shape)
+
+            full_time = torch.nn.functional.normalize(full_time, dim=1, p=2)
+            full_qs = torch.nn.functional.normalize(full_qs, dim=1, p=2)
+            similarity = torch.einsum('qc,nc->qn', full_qs, full_time) # q n
+            similarity = torch.softmax(similarity/0.1, dim=-1)
+            select_index = torch.topk(similarity, dim=-1, k=min(4, full_time.shape[0]))[1] # q k
+            select_index = select_index.sort(dim=-1)[0]
+            select_memory = []
+            select_clip = []
+            for batch_idx in range(n_qs):
+                memory = full_memory[select_index[batch_idx]] # k k c
+                clip = clip_embeds[select_index[batch_idx]]
+                select_clip.append(clip)
+                select_memory.append(memory)
+            select_memory = torch.stack(select_memory, dim=0) # q k n c
+            select_clip = torch.stack(select_clip, dim=0)
+            global_memory = global_memory.unsqueeze(0).repeat([n_qs, 1, 1])
+            return select_memory, select_clip, global_memory, 0, similarity
+
+    @add_start_docstrings_to_model_forward(QWEN2_INPUTS_DOCSTRING)
+    @replace_return_docstrings(output_type=CausalLMOutputWithPast, config_class=_CONFIG_FOR_DOC)
+    def forward(
+        self,
+        input_ids: torch.LongTensor = None,
+        attention_mask: Optional[torch.Tensor] = None,
+        position_ids: Optional[torch.LongTensor] = None,
+        past_key_values: Optional[List[torch.FloatTensor]] = None,
+        inputs_embeds: Optional[torch.FloatTensor] = None,
+        labels: Optional[torch.LongTensor] = None,
+        indicators: Optional[torch.LongTensor] = None,
+        use_cache: Optional[bool] = None,
+        output_attentions: Optional[bool] = None,
+        output_hidden_states: Optional[bool] = None,
+        return_dict: Optional[bool] = None,
+        cache_position: Optional[torch.LongTensor] = None,
+    ) -> Union[Tuple, CausalLMOutputWithPast]:
+        r"""
+        Args:
+            labels (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*):
+                Labels for computing the masked language modeling loss. Indices should either be in `[0, ...,
+                config.vocab_size]` or -100 (see `input_ids` docstring). Tokens with indices set to `-100` are ignored
+                (masked), the loss is only computed for the tokens with labels in `[0, ..., config.vocab_size]`.
+
+        Returns:
+
+        Example:
+
+        ```python
+        >>> from transformers import AutoTokenizer, Qwen2ForCausalLM
+
+        >>> model = Qwen2ForCausalLM.from_pretrained(PATH_TO_CONVERTED_WEIGHTS)
+        >>> tokenizer = AutoTokenizer.from_pretrained(PATH_TO_CONVERTED_TOKENIZER)
+
+        >>> prompt = "Hey, are you conscious? Can you talk to me?"
+        >>> inputs = tokenizer(prompt, return_tensors="pt")
+
+        >>> # Generate
+        >>> generate_ids = model.generate(inputs.input_ids, max_length=30)
+        >>> tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
+        "Hey, are you conscious? Can you talk to me?\nI'm not conscious, but I can talk to you."
+        ```"""
+
+        output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions
+        output_hidden_states = (
+            output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
+        )
+        return_dict = return_dict if return_dict is not None else self.config.use_return_dict
+
+        # decoder outputs consists of (dec_features, layer_state, dec_hidden, dec_attn)
+        outputs = self.model(
+            input_ids=input_ids,
+            attention_mask=attention_mask,
+            position_ids=position_ids,
+            past_key_values=past_key_values,
+            inputs_embeds=inputs_embeds,
+            indicators=indicators,
+            use_cache=use_cache,
+            output_attentions=output_attentions,
+            output_hidden_states=output_hidden_states,
+            return_dict=return_dict,
+            cache_position=cache_position,
+        )
+
+        hidden_states = outputs[0]
+        logits = self.lm_head(hidden_states)
+        logits = logits.float()
+
+        loss = None
+        if labels is not None:
+            # Shift so that tokens < n predict n
+            shift_logits = logits[..., :-1, :].contiguous()
+            shift_labels = labels[..., 1:].contiguous()
+            # Flatten the tokens
+            loss_fct = CrossEntropyLoss()
+            shift_logits = shift_logits.view(-1, self.config.vocab_size)
+            shift_labels = shift_labels.view(-1)
+            # Enable model parallelism
+            shift_labels = shift_labels.to(shift_logits.device)
+            loss = loss_fct(shift_logits, shift_labels)
+
+        if not return_dict:
+            output = (logits,) + outputs[1:]
+            return (loss,) + output if loss is not None else output
+
+        return CausalLMOutputWithPast(
+            loss=loss,
+            logits=logits,
+            past_key_values=outputs.past_key_values,
+            hidden_states=outputs.hidden_states,
+            attentions=outputs.attentions,
+        )
+
+    # Copied from transformers.models.llama.modeling_llama.LlamaForCausalLM.prepare_inputs_for_generation
+    def prepare_inputs_for_generation(
+        self,
+        input_ids,
+        past_key_values=None,
+        attention_mask=None,
+        inputs_embeds=None,
+        cache_position=None,
+        position_ids=None,
+        use_cache=True,
+        **kwargs,
+    ):
+        # If we have cache: let's slice `input_ids` through `cache_position`, to keep only the unprocessed tokens
+        # Exception 1: when passing input_embeds, input_ids may be missing entries
+        # Exception 2: some generation methods do special slicing of input_ids, so we don't need to do it here
+        if past_key_values is not None:
+            if inputs_embeds is not None:  # Exception 1
+                input_ids = input_ids[:, -cache_position.shape[0] :]
+            elif input_ids.shape[1] != cache_position.shape[0]:  # Default case (the "else", a no op, is Exception 2)
+                input_ids = input_ids[:, cache_position]
+
+        if attention_mask is not None and position_ids is None:
+            # create position_ids on the fly for batch generation
+            position_ids = attention_mask.long().cumsum(-1) - 1
+            position_ids.masked_fill_(attention_mask == 0, 1)
+            if past_key_values:
+                position_ids = position_ids[:, -input_ids.shape[1] :]
+
+        # if `inputs_embeds` are passed, we only want to use them in the 1st generation step
+        if inputs_embeds is not None and cache_position[0] == 0:
+            model_inputs = {"inputs_embeds": inputs_embeds}
+        else:
+            model_inputs = {"input_ids": input_ids.contiguous()}  # `contiguous()` needed for compilation use cases
+
+        model_inputs.update(
+            {
+                "position_ids": position_ids,
+                "cache_position": cache_position,
+                "past_key_values": past_key_values,
+                "use_cache": use_cache,
+                "attention_mask": attention_mask,
+            }
+        )
+        return model_inputs
+
+
+@add_start_docstrings(
+    """
+    The Qwen2 Model transformer with a sequence classification head on top (linear layer).
+
+    [`Qwen2ForSequenceClassification`] uses the last token in order to do the classification, as other causal models
+    (e.g. GPT-2) do.
+
+    Since it does classification on the last token, it requires to know the position of the last token. If a
+    `pad_token_id` is defined in the configuration, it finds the last token that is not a padding token in each row. If
+    no `pad_token_id` is defined, it simply takes the last value in each row of the batch. Since it cannot guess the
+    padding tokens when `inputs_embeds` are passed instead of `input_ids`, it does the same (take the last value in
+    each row of the batch).
+    """,
+    QWEN2_START_DOCSTRING,
+)
+class Qwen2ForSequenceClassification(Qwen2PreTrainedModel):
+    def __init__(self, config):
+        super().__init__(config)
+        self.num_labels = config.num_labels
+        self.model = Qwen2Model(config)
+        self.score = nn.Linear(config.hidden_size, self.num_labels, bias=False)
+
+        # Initialize weights and apply final processing
+        self.post_init()
+
+    def get_input_embeddings(self):
+        return self.model.embed_tokens
+
+    def set_input_embeddings(self, value):
+        self.model.embed_tokens = value
+
+    @add_start_docstrings_to_model_forward(QWEN2_INPUTS_DOCSTRING)
+    def forward(
+        self,
+        input_ids: torch.LongTensor = None,
+        attention_mask: Optional[torch.Tensor] = None,
+        position_ids: Optional[torch.LongTensor] = None,
+        past_key_values: Optional[List[torch.FloatTensor]] = None,
+        inputs_embeds: Optional[torch.FloatTensor] = None,
+        labels: Optional[torch.LongTensor] = None,
+        use_cache: Optional[bool] = None,
+        output_attentions: Optional[bool] = None,
+        output_hidden_states: Optional[bool] = None,
+        return_dict: Optional[bool] = None,
+    ) -> Union[Tuple, SequenceClassifierOutputWithPast]:
+        r"""
+        labels (`torch.LongTensor` of shape `(batch_size,)`, *optional*):
+            Labels for computing the sequence classification/regression loss. Indices should be in `[0, ...,
+            config.num_labels - 1]`. If `config.num_labels == 1` a regression loss is computed (Mean-Square loss), If
+            `config.num_labels > 1` a classification loss is computed (Cross-Entropy).
+        """
+        return_dict = return_dict if return_dict is not None else self.config.use_return_dict
+
+        transformer_outputs = self.model(
+            input_ids,
+            attention_mask=attention_mask,
+            position_ids=position_ids,
+            past_key_values=past_key_values,
+            inputs_embeds=inputs_embeds,
+            use_cache=use_cache,
+            output_attentions=output_attentions,
+            output_hidden_states=output_hidden_states,
+            return_dict=return_dict,
+        )
+        hidden_states = transformer_outputs[0]
+        logits = self.score(hidden_states)
+
+        if input_ids is not None:
+            batch_size = input_ids.shape[0]
+        else:
+            batch_size = inputs_embeds.shape[0]
+
+        if self.config.pad_token_id is None and batch_size != 1:
+            raise ValueError("Cannot handle batch sizes > 1 if no padding token is defined.")
+        if self.config.pad_token_id is None:
+            sequence_lengths = -1
+        else:
+            if input_ids is not None:
+                # if no pad token found, use modulo instead of reverse indexing for ONNX compatibility
+                sequence_lengths = torch.eq(input_ids, self.config.pad_token_id).int().argmax(-1) - 1
+                sequence_lengths = sequence_lengths % input_ids.shape[-1]
+                sequence_lengths = sequence_lengths.to(logits.device)
+            else:
+                sequence_lengths = -1
+
+        pooled_logits = logits[torch.arange(batch_size, device=logits.device), sequence_lengths]
+
+        loss = None
+        if labels is not None:
+            labels = labels.to(logits.device)
+            if self.config.problem_type is None:
+                if self.num_labels == 1:
+                    self.config.problem_type = "regression"
+                elif self.num_labels > 1 and (labels.dtype == torch.long or labels.dtype == torch.int):
+                    self.config.problem_type = "single_label_classification"
+                else:
+                    self.config.problem_type = "multi_label_classification"
+
+            if self.config.problem_type == "regression":
+                loss_fct = MSELoss()
+                if self.num_labels == 1:
+                    loss = loss_fct(pooled_logits.squeeze(), labels.squeeze())
+                else:
+                    loss = loss_fct(pooled_logits, labels)
+            elif self.config.problem_type == "single_label_classification":
+                loss_fct = CrossEntropyLoss()
+                loss = loss_fct(pooled_logits.view(-1, self.num_labels), labels.view(-1))
+            elif self.config.problem_type == "multi_label_classification":
+                loss_fct = BCEWithLogitsLoss()
+                loss = loss_fct(pooled_logits, labels)
+        if not return_dict:
+            output = (pooled_logits,) + transformer_outputs[1:]
+            return ((loss,) + output) if loss is not None else output
+
+        return SequenceClassifierOutputWithPast(
+            loss=loss,
+            logits=pooled_logits,
+            past_key_values=transformer_outputs.past_key_values,
+            hidden_states=transformer_outputs.hidden_states,
+            attentions=transformer_outputs.attentions,
+        )
+
+
+@add_start_docstrings(
+    """
+    The Qwen2 Model transformer with a token classification head on top (a linear layer on top of the hidden-states
+    output) e.g. for Named-Entity-Recognition (NER) tasks.
+    """,
+    QWEN2_START_DOCSTRING,
+)
+# Copied from transformers.models.llama.modeling_llama.LlamaForTokenClassification with Llama->Qwen2, LLAMA->QWEN2
+class Qwen2ForTokenClassification(Qwen2PreTrainedModel):
+    def __init__(self, config):
+        super().__init__(config)
+        self.num_labels = config.num_labels
+        self.model = Qwen2Model(config)
+        if getattr(config, "classifier_dropout", None) is not None:
+            classifier_dropout = config.classifier_dropout
+        elif getattr(config, "hidden_dropout", None) is not None:
+            classifier_dropout = config.hidden_dropout
+        else:
+            classifier_dropout = 0.1
+        self.dropout = nn.Dropout(classifier_dropout)
+        self.score = nn.Linear(config.hidden_size, config.num_labels)
+
+        # Initialize weights and apply final processing
+        self.post_init()
+
+    def get_input_embeddings(self):
+        return self.model.embed_tokens
+
+    def set_input_embeddings(self, value):
+        self.model.embed_tokens = value
+
+    @add_start_docstrings_to_model_forward(QWEN2_INPUTS_DOCSTRING)
+    def forward(
+        self,
+        input_ids: Optional[torch.LongTensor] = None,
+        attention_mask: Optional[torch.Tensor] = None,
+        position_ids: Optional[torch.LongTensor] = None,
+        past_key_values: Optional[List[torch.FloatTensor]] = None,
+        inputs_embeds: Optional[torch.FloatTensor] = None,
+        labels: Optional[torch.LongTensor] = None,
+        use_cache: Optional[bool] = None,
+        output_attentions: Optional[bool] = None,
+        output_hidden_states: Optional[bool] = None,
+        return_dict: Optional[bool] = None,
+    ) -> Union[Tuple, TokenClassifierOutput]:
+        r"""
+        labels (`torch.LongTensor` of shape `(batch_size,)`, *optional*):
+            Labels for computing the sequence classification/regression loss. Indices should be in `[0, ...,
+            config.num_labels - 1]`. If `config.num_labels == 1` a regression loss is computed (Mean-Square loss), If
+            `config.num_labels > 1` a classification loss is computed (Cross-Entropy).
+        """
+        return_dict = return_dict if return_dict is not None else self.config.use_return_dict
+
+        outputs = self.model(
+            input_ids,
+            attention_mask=attention_mask,
+            position_ids=position_ids,
+            past_key_values=past_key_values,
+            inputs_embeds=inputs_embeds,
+            use_cache=use_cache,
+            output_attentions=output_attentions,
+            output_hidden_states=output_hidden_states,
+            return_dict=return_dict,
+        )
+        sequence_output = outputs[0]
+        sequence_output = self.dropout(sequence_output)
+        logits = self.score(sequence_output)
+
+        loss = None
+        if labels is not None:
+            loss_fct = CrossEntropyLoss()
+            loss = loss_fct(logits.view(-1, self.num_labels), labels.view(-1))
+
+        if not return_dict:
+            output = (logits,) + outputs[2:]
+            return ((loss,) + output) if loss is not None else output
+
+        return TokenClassifierOutput(
+            loss=loss,
+            logits=logits,
+            hidden_states=outputs.hidden_states,
+            attentions=outputs.attentions,
+        )
diff --git a/memory/special_tokens_map.json b/memory/special_tokens_map.json
new file mode 100644
index 0000000000000000000000000000000000000000..2c53454aff27c6d22873cc28c884c2b2d5d07693
--- /dev/null
+++ b/memory/special_tokens_map.json
@@ -0,0 +1,20 @@
+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>"
+  ],
+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}
diff --git a/memory/tokenizer_config.json b/memory/tokenizer_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8811f5d71f3b123506d8c1f47b2bdeb28f87deef
--- /dev/null
+++ b/memory/tokenizer_config.json
@@ -0,0 +1,44 @@
+{
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>"
+  ],
+  "bos_token": null,
+  "chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n' }}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "model_max_length": 32768,
+  "pad_token": "<|endoftext|>",
+  "padding_side": "right",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}
diff --git a/memory/utils.py b/memory/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..4006cf917e26c365080b0844c56fab78c48457c0
--- /dev/null
+++ b/memory/utils.py
@@ -0,0 +1,126 @@
+import datetime
+import logging
+import logging.handlers
+import os
+import sys
+
+import requests
+
+from llava.constants import LOGDIR
+
+server_error_msg = "**NETWORK ERROR DUE TO HIGH TRAFFIC. PLEASE REGENERATE OR REFRESH THIS PAGE.**"
+moderation_msg = "YOUR INPUT VIOLATES OUR CONTENT MODERATION GUIDELINES. PLEASE TRY AGAIN."
+
+handler = None
+
+
+def build_logger(logger_name, logger_filename):
+    global handler
+
+    formatter = logging.Formatter(
+        fmt="%(asctime)s | %(levelname)s | %(name)s | %(message)s",
+        datefmt="%Y-%m-%d %H:%M:%S",
+    )
+
+    # Set the format of root handlers
+    if not logging.getLogger().handlers:
+        logging.basicConfig(level=logging.INFO)
+    logging.getLogger().handlers[0].setFormatter(formatter)
+
+    # Redirect stdout and stderr to loggers
+    stdout_logger = logging.getLogger("stdout")
+    stdout_logger.setLevel(logging.INFO)
+    sl = StreamToLogger(stdout_logger, logging.INFO)
+    sys.stdout = sl
+
+    stderr_logger = logging.getLogger("stderr")
+    stderr_logger.setLevel(logging.ERROR)
+    sl = StreamToLogger(stderr_logger, logging.ERROR)
+    sys.stderr = sl
+
+    # Get logger
+    logger = logging.getLogger(logger_name)
+    logger.setLevel(logging.INFO)
+
+    # Add a file handler for all loggers
+    if handler is None:
+        os.makedirs(LOGDIR, exist_ok=True)
+        filename = os.path.join(LOGDIR, logger_filename)
+        handler = logging.handlers.TimedRotatingFileHandler(
+            filename, when='D', utc=True, encoding='UTF-8')
+        handler.setFormatter(formatter)
+
+        for name, item in logging.root.manager.loggerDict.items():
+            if isinstance(item, logging.Logger):
+                item.addHandler(handler)
+
+    return logger
+
+
+class StreamToLogger(object):
+    """
+    Fake file-like stream object that redirects writes to a logger instance.
+    """
+    def __init__(self, logger, log_level=logging.INFO):
+        self.terminal = sys.stdout
+        self.logger = logger
+        self.log_level = log_level
+        self.linebuf = ''
+
+    def __getattr__(self, attr):
+        return getattr(self.terminal, attr)
+
+    def write(self, buf):
+        temp_linebuf = self.linebuf + buf
+        self.linebuf = ''
+        for line in temp_linebuf.splitlines(True):
+            # From the io.TextIOWrapper docs:
+            #   On output, if newline is None, any '\n' characters written
+            #   are translated to the system default line separator.
+            # By default sys.stdout.write() expects '\n' newlines and then
+            # translates them so this is still cross platform.
+            if line[-1] == '\n':
+                self.logger.log(self.log_level, line.rstrip())
+            else:
+                self.linebuf += line
+
+    def flush(self):
+        if self.linebuf != '':
+            self.logger.log(self.log_level, self.linebuf.rstrip())
+        self.linebuf = ''
+
+
+def disable_torch_init():
+    """
+    Disable the redundant torch default initialization to accelerate model creation.
+    """
+    import torch
+    setattr(torch.nn.Linear, "reset_parameters", lambda self: None)
+    setattr(torch.nn.LayerNorm, "reset_parameters", lambda self: None)
+
+
+def violates_moderation(text):
+    """
+    Check whether the text violates OpenAI moderation API.
+    """
+    url = "https://api.openai.com/v1/moderations"
+    headers = {"Content-Type": "application/json",
+               "Authorization": "Bearer " + os.environ["OPENAI_API_KEY"]}
+    text = text.replace("\n", "")
+    data = "{" + '"input": ' + f'"{text}"' + "}"
+    data = data.encode("utf-8")
+    try:
+        ret = requests.post(url, headers=headers, data=data, timeout=5)
+        flagged = ret.json()["results"][0]["flagged"]
+    except requests.exceptions.RequestException as e:
+        flagged = False
+    except KeyError as e:
+        flagged = False
+
+    return flagged
+
+
+def pretty_print_semaphore(semaphore):
+    if semaphore is None:
+        return "None"
+    return f"Semaphore(value={semaphore._value}, locked={semaphore.locked()})"
diff --git a/memory/vocab.json b/memory/vocab.json
new file mode 100644
index 0000000000000000000000000000000000000000..6bce3a0a3866c4791a74d83d78f6824c3af64ec3
--- /dev/null
+++ b/memory/vocab.json
@@ -0,0 +1,151645 @@
+{
+  "!": 0,
+  "!!": 2928,
+  "!!!": 12069,
+  "!!!!": 17085,
+  "!!!!!": 69800,
+  "!!!!!!!!": 50667,
+  "!!!!ĊĊ": 81392,
+  "!!!Ċ": 79295,
+  "!!!ĊĊ": 32057,
+  "!!\");Ċ": 98164,
+  "!!)Ċ": 85892,
+  "!!,": 93687,
+  "!!.": 24426,
+  "!!Ċ": 50347,
+  "!!ĊĊ": 24796,
+  "!\"": 8958,
+  "!\")": 88783,
+  "!\");": 85540,
+  "!\");Ċ": 11142,
+  "!\");ĊĊ": 57073,
+  "!\");čĊ": 42012,
+  "!\")Ċ": 22988,
+  "!\")ĊĊ": 66506,
+  "!\")čĊ": 93896,
+  "!\",": 18789,
+  "!\",Ċ": 33436,
+  "!\".": 92993,
+  "!\";Ċ": 26782,
+  "!\";čĊ": 93397,
+  "!\"Ċ": 24734,
+  "!\"ĊĊ": 17199,
+  "!'": 31383,
+  "!');Ċ": 25490,
+  "!')Ċ": 36180,
+  "!')ĊĊ": 98973,
+  "!',": 38692,
+  "!',Ċ": 36260,
+  "!';Ċ": 49174,
+  "!'Ċ": 48727,
+  "!(": 10297,
+  "!(\"": 17223,
+  "!(\"{": 88928,
+  "!(\"{}\",": 79878,
+  "!(:": 49116,
+  "!(Ċ": 33673,
+  "!)": 16315,
+  "!),": 48643,
+  "!).": 42392,
+  "!).ĊĊ": 86779,
+  "!)Ċ": 27584,
+  "!)ĊĊ": 35786,
+  "!*": 68222,
+  "!*\\Ċ": 90237,
+  "!,": 17142,
+  "!,Ċ": 72589,
+  "!--": 2495,
+  "!.": 15365,
+  "!.ĊĊ": 98527,
+  "!/": 87980,
+  "!:": 35575,
+  "!;Ċ": 85318,
+  "!<": 86932,
+  "!</": 18685,
+  "!=": 5824,
+  "!=\"": 32299,
+  "!='": 25005,
+  "!=(": 58291,
+  "!=-": 62212,
+  "!==": 49014,
+  "!?": 57390,
+  "!I": 90497,
+  "![": 20703,
+  "![Ċ": 90515,
+  "!\\": 14771,
+  "!]": 68034,
+  "!important": 73171,
+  "!âĢĻ": 71334,
+  "!âĢĿ": 17839,
+  "!âĢĿĊĊ": 24727,
+  "!Ċ": 4894,
+  "!ĊĊ": 2219,
+  "!ĊĊĊ": 27901,
+  "!ĊĊĊĊ": 14333,
+  "!ĊĊĊĊĊĊ": 55957,
+  "!čĊ": 45626,
+  "\"": 1,
+  "\"\"": 3014,
+  "\"\"\"": 12599,
+  "\"\"\"),Ċ": 93188,
+  "\"\"\")Ċ": 95323,
+  "\"\"\",Ċ": 74734,
+  "\"\"\".": 87930,
+  "\"\"\"Ċ": 7129,
+  "\"\"\"ĊĊ": 15075,
+  "\"\"\"ĊĊĊ": 53505,
+  "\"\"\"čĊ": 36825,
+  "\"\"\"čĊčĊ": 75583,
+  "\"\",": 56323,
+  "\"\",Ċ": 39680,
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+  "\"\":": 28796,
+  "\"\"Ċ": 89262,
+  "\"#": 57676,
+  "\"$": 33732,
+  "\"${": 74013,
+  "\"%": 31391,
+  "\"%(": 57439,
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+  "\"';Ċ": 84576,
+  "\"'Ċ": 87628,
+  "\"(": 29209,
+  "\")": 899,
+  "\")!=": 98398,
+  "\")(": 34600,
+  "\"))": 2761,
+  "\")))": 38459,
+  "\"))))Ċ": 77978,
+  "\")));": 71471,
+  "\")));Ċ": 17621,
+  "\")));ĊĊ": 74385,
+  "\")));čĊ": 58337,
+  "\")))Ċ": 29836,
+  "\")),": 35674,
+  "\")),Ċ": 30154,
+  "\")).": 15197,
+  "\"));": 32596,
+  "\"));Ċ": 4010,
+  "\"));ĊĊ": 14929,
+  "\"));čĊ": 15397,
+  "\"));čĊčĊ": 69938,
+  "\")){Ċ": 21865,
+  "\")){čĊ": 72208,
+  "\"))Ċ": 5455,
+  "\"))ĊĊ": 28075,
+  "\"))čĊ": 26043,
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+  "\"),Ċ": 4461,
+  "\"),ĊĊ": 65974,
+  "\"),čĊ": 28978,
+  "\")->": 24011,
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+  "\").Ċ": 38609,
+  "\").ĊĊ": 80984,
+  "\"):": 37051,
+  "\"):Ċ": 15146,
+  "\"):čĊ": 74199,
+  "\");": 5038,
+  "\");//": 40919,
+  "\");}Ċ": 90118,
+  "\");Ċ": 797,
+  "\");ĊĊ": 3071,
+  "\");ĊĊĊ": 32636,
+  "\");čĊ": 2815,
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+  "\")]čĊ": 25731,
+  "\"){": 47189,
+  "\"){Ċ": 14818,
+  "\"){čĊ": 50938,
+  "\")}": 67455,
+  "\")},Ċ": 79583,
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