NghiemAbe commited on
Commit
5242783
1 Parent(s): 0395778

Add new SentenceTransformer model

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1_Pooling/config.json ADDED
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+ {
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+ "word_embedding_dimension": 768,
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+ "pooling_mode_cls_token": false,
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+ "pooling_mode_mean_tokens": true,
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+ "pooling_mode_max_tokens": false,
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+ "pooling_mode_mean_sqrt_len_tokens": false,
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+ "pooling_mode_weightedmean_tokens": false,
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+ "pooling_mode_lasttoken": false,
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+ "include_prompt": true
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+ }
README.md ADDED
The diff for this file is too large to render. See raw diff
 
config.json ADDED
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+ {
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+ "_name_or_path": "outputs/gte-v1/checkpoint-4100",
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+ "architectures": [
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+ "NewModel"
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+ ],
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+ "attention_probs_dropout_prob": 0.0,
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+ "auto_map": {
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+ "AutoConfig": "configuration.NewConfig",
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+ "AutoModel": "Alibaba-NLP/new-impl--modeling.NewModel",
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+ "AutoModelForMaskedLM": "Alibaba-NLP/new-impl--modeling.NewForMaskedLM",
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+ "AutoModelForMultipleChoice": "Alibaba-NLP/new-impl--modeling.NewForMultipleChoice",
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+ "AutoModelForQuestionAnswering": "Alibaba-NLP/new-impl--modeling.NewForQuestionAnswering",
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+ "AutoModelForSequenceClassification": "Alibaba-NLP/new-impl--modeling.NewForSequenceClassification",
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+ "AutoModelForTokenClassification": "Alibaba-NLP/new-impl--modeling.NewForTokenClassification"
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+ },
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+ "classifier_dropout": 0.0,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "LABEL_0"
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+ },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "label2id": {
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+ "LABEL_0": 0
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "layer_norm_type": "layer_norm",
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+ "logn_attention_clip1": false,
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+ "logn_attention_scale": false,
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+ "max_position_embeddings": 8192,
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+ "model_type": "new",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pack_qkv": true,
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+ "pad_token_id": 1,
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+ "position_embedding_type": "rope",
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+ "rope_scaling": {
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+ "factor": 8.0,
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+ "type": "ntk"
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+ },
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+ "rope_theta": 20000,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.45.2",
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+ "type_vocab_size": 1,
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+ "unpad_inputs": false,
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+ "use_memory_efficient_attention": false,
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+ "vocab_size": 16456,
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+ "vocabtrimmer": {
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+ "mining_config": {
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+ "dataset": "Turbo-AI/data-corpus",
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+ "dataset_column": "text",
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+ "dataset_name": null,
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+ "dataset_split": "train",
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+ "language": "vi",
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+ "min_frequency": 2,
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+ "target_vocab_size": null
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+ },
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+ "stats": {
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+ "compression_rate_embedding": 6.581136421807013,
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+ "compression_rate_full": 41.25171334079449,
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+ "parameter_size_embedding/raw": 192036864,
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+ "parameter_size_embedding/trimmed": 12638208,
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+ "parameter_size_full/raw": 305368320,
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+ "parameter_size_full/trimmed": 125969664,
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+ "vocab_size/raw": 250048,
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+ "vocab_size/trimmed": 16456
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+ }
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+ }
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+ }
config_sentence_transformers.json ADDED
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+ {
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+ "__version__": {
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+ "sentence_transformers": "3.3.0.dev0",
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+ "transformers": "4.45.2",
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+ "pytorch": "2.4.1+cu118"
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+ },
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+ "prompts": {},
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+ "default_prompt_name": null,
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+ "similarity_fn_name": null
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+ }
configuration.py ADDED
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+ # coding=utf-8
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+ # Copyright 2024 The GTE Team Authors and Alibaba Group.
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+ # Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
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+ #
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+ # Licensed under the Apache License, Version 2.0 (the "License");
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+ # you may not use this file except in compliance with the License.
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+ # You may obtain a copy of the License at
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+ #
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+ # http://www.apache.org/licenses/LICENSE-2.0
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+ #
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+ # Unless required by applicable law or agreed to in writing, software
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+ # distributed under the License is distributed on an "AS IS" BASIS,
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+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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+ # See the License for the specific language governing permissions and
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+ # limitations under the License.
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+ """ NEW model configuration"""
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+ from transformers.configuration_utils import PretrainedConfig
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+ from transformers.utils import logging
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+
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+ logger = logging.get_logger(__name__)
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+
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+
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+ class NewConfig(PretrainedConfig):
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+ r"""
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+ This is the configuration class to store the configuration of a [`NewModel`] or a [`TFNewModel`]. It is used to
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+ instantiate a NEW model according to the specified arguments, defining the model architecture. Instantiating a
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+ configuration with the defaults will yield a similar configuration to that of the NEW
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+ [izhx/new-base-en](https://huggingface.co/izhx/new-base-en) architecture.
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+
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+ Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
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+ documentation from [`PretrainedConfig`] for more information.
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+
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+
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+ Args:
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+ vocab_size (`int`, *optional*, defaults to 30522):
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+ Vocabulary size of the NEW model. Defines the number of different tokens that can be represented by the
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+ `inputs_ids` passed when calling [`NewModel`] or [`TFNewModel`].
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+ hidden_size (`int`, *optional*, defaults to 768):
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+ Dimensionality of the encoder layers and the pooler layer.
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+ num_hidden_layers (`int`, *optional*, defaults to 12):
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+ Number of hidden layers in the Transformer encoder.
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+ num_attention_heads (`int`, *optional*, defaults to 12):
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+ Number of attention heads for each attention layer in the Transformer encoder.
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+ intermediate_size (`int`, *optional*, defaults to 3072):
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+ Dimensionality of the "intermediate" (often named feed-forward) layer in the Transformer encoder.
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+ hidden_act (`str` or `Callable`, *optional*, defaults to `"gelu"`):
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+ The non-linear activation function (function or string) in the encoder and pooler. If string, `"gelu"`,
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+ `"relu"`, `"silu"` and `"gelu_new"` are supported.
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+ hidden_dropout_prob (`float`, *optional*, defaults to 0.1):
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+ The dropout probability for all fully connected layers in the embeddings, encoder, and pooler.
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+ attention_probs_dropout_prob (`float`, *optional*, defaults to 0.1):
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+ The dropout ratio for the attention probabilities.
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+ max_position_embeddings (`int`, *optional*, defaults to 512):
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+ The maximum sequence length that this model might ever be used with. Typically set this to something large
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+ just in case (e.g., 512 or 1024 or 2048).
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+ type_vocab_size (`int`, *optional*, defaults to 2):
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+ The vocabulary size of the `token_type_ids` passed when calling [`NewModel`] or [`TFNewModel`].
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+ initializer_range (`float`, *optional*, defaults to 0.02):
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+ The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
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+ layer_norm_eps (`float`, *optional*, defaults to 1e-12):
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+ The epsilon used by the layer normalization layers.
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+ position_embedding_type (`str`, *optional*, defaults to `"rope"`):
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+ Type of position embedding. Choose one of `"absolute"`, `"rope"`.
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+ rope_theta (`float`, *optional*, defaults to 10000.0):
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+ The base period of the RoPE embeddings.
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+ rope_scaling (`Dict`, *optional*):
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+ Dictionary containing the scaling configuration for the RoPE embeddings. Currently supports two scaling
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+ strategies: linear and dynamic. Their scaling factor must be a float greater than 1. The expected format is
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+ `{"type": strategy name, "factor": scaling factor}`. When using this flag, don't update
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+ `max_position_embeddings` to the expected new maximum. See the following thread for more information on how
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+ these scaling strategies behave:
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+ https://www.reddit.com/r/LocalLLaMA/comments/14mrgpr/dynamically_scaled_rope_further_increases/. This is an
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+ experimental feature, subject to breaking API changes in future versions.
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+ classifier_dropout (`float`, *optional*):
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+ The dropout ratio for the classification head.
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+
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+ Examples:
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+
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+ ```python
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+ >>> from transformers import NewConfig, NewModel
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+
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+ >>> # Initializing a NEW izhx/new-base-en style configuration
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+ >>> configuration = NewConfig()
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+
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+ >>> # Initializing a model (with random weights) from the izhx/new-base-en style configuration
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+ >>> model = NewModel(configuration)
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+
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+ >>> # Accessing the model configuration
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+ >>> configuration = model.config
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+ ```"""
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+
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+ model_type = "new"
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+
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+ def __init__(
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+ self,
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+ vocab_size=30528,
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+ hidden_size=768,
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+ num_hidden_layers=12,
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+ num_attention_heads=12,
100
+ intermediate_size=3072,
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+ hidden_act="gelu",
102
+ hidden_dropout_prob=0.1,
103
+ attention_probs_dropout_prob=0.0,
104
+ max_position_embeddings=2048,
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+ type_vocab_size=1,
106
+ initializer_range=0.02,
107
+ layer_norm_type='layer_norm',
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+ layer_norm_eps=1e-12,
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+ # pad_token_id=0,
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+ position_embedding_type="rope",
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+ rope_theta=10000.0,
112
+ rope_scaling=None,
113
+ classifier_dropout=None,
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+ pack_qkv=True,
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+ unpad_inputs=False,
116
+ use_memory_efficient_attention=False,
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+ logn_attention_scale=False,
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+ logn_attention_clip1=False,
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+ **kwargs,
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+ ):
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+ super().__init__(**kwargs)
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+
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+ self.vocab_size = vocab_size
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+ self.hidden_size = hidden_size
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+ self.num_hidden_layers = num_hidden_layers
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+ self.num_attention_heads = num_attention_heads
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+ self.hidden_act = hidden_act
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+ self.intermediate_size = intermediate_size
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+ self.hidden_dropout_prob = hidden_dropout_prob
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+ self.attention_probs_dropout_prob = attention_probs_dropout_prob
131
+ self.max_position_embeddings = max_position_embeddings
132
+ self.type_vocab_size = type_vocab_size
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+ self.initializer_range = initializer_range
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+ self.layer_norm_type = layer_norm_type
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+ self.layer_norm_eps = layer_norm_eps
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+ self.position_embedding_type = position_embedding_type
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+ self.rope_theta = rope_theta
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+ self.rope_scaling = rope_scaling
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+ self.classifier_dropout = classifier_dropout
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+
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+ self.pack_qkv = pack_qkv
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+ self.unpad_inputs = unpad_inputs
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+ self.use_memory_efficient_attention = use_memory_efficient_attention
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+ self.logn_attention_scale = logn_attention_scale
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+ self.logn_attention_clip1 = logn_attention_clip1
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modules.json ADDED
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+ [
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+ {
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+ "name": "0",
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+ "path": "",
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+ "type": "sentence_transformers.models.Transformer"
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+ },
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+ {
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+ "idx": 1,
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+ "name": "1",
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+ "path": "1_Pooling",
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+ "type": "sentence_transformers.models.Pooling"
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+ }
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+ ]
sentence_bert_config.json ADDED
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+ {
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+ "max_seq_length": 1024,
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+ "do_lower_case": false
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+ }
special_tokens_map.json ADDED
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tokenizer.json ADDED
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tokenizer_config.json ADDED
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