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Upload June 2024 update ONNX models
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- config.json +138 -137
- configuration_phi3.py +227 -213
- cpu_and_mobile/cpu-int4-awq-block-128/added_tokens.json +13 -0
- cpu_and_mobile/cpu-int4-awq-block-128/config.json +138 -0
- cpu_and_mobile/cpu-int4-awq-block-128/configuration_phi3.py +227 -0
- cpu_and_mobile/cpu-int4-awq-block-128/genai_config.json +53 -0
- cpu_and_mobile/cpu-int4-awq-block-128/phi3-mini-128k-instruct-cpu-int4-awq-block-128.onnx +3 -0
- cpu_and_mobile/cpu-int4-awq-block-128/phi3-mini-128k-instruct-cpu-int4-awq-block-128.onnx.data +3 -0
- cpu_and_mobile/cpu-int4-awq-block-128/special_tokens_map.json +30 -0
- cpu_and_mobile/cpu-int4-awq-block-128/tokenizer.json +0 -0
- cpu_and_mobile/cpu-int4-awq-block-128/tokenizer.model +3 -0
- cpu_and_mobile/cpu-int4-awq-block-128/tokenizer_config.json +130 -0
- cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/added_tokens.json +13 -13
- cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/config.json +138 -137
- cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/configuration_phi3.py +227 -213
- cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/phi3-mini-128k-instruct-cpu-int4-rtn-block-32-acc-level-4.onnx +1 -1
- cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/phi3-mini-128k-instruct-cpu-int4-rtn-block-32-acc-level-4.onnx.data +1 -1
- cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/special_tokens_map.json +30 -30
- cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/tokenizer.json +0 -0
- cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/tokenizer_config.json +130 -130
- cpu_and_mobile/cpu-int4-rtn-block-32/added_tokens.json +13 -13
- cpu_and_mobile/cpu-int4-rtn-block-32/config.json +138 -137
- cpu_and_mobile/cpu-int4-rtn-block-32/configuration_phi3.py +227 -213
- cpu_and_mobile/cpu-int4-rtn-block-32/phi3-mini-128k-instruct-cpu-int4-rtn-block-32.onnx +1 -1
- cpu_and_mobile/cpu-int4-rtn-block-32/phi3-mini-128k-instruct-cpu-int4-rtn-block-32.onnx.data +1 -1
- cpu_and_mobile/cpu-int4-rtn-block-32/special_tokens_map.json +30 -30
- cpu_and_mobile/cpu-int4-rtn-block-32/tokenizer.json +0 -0
- cpu_and_mobile/cpu-int4-rtn-block-32/tokenizer_config.json +130 -130
- cuda/cuda-fp16/added_tokens.json +13 -13
- cuda/cuda-fp16/config.json +138 -137
- cuda/cuda-fp16/configuration_phi3.py +227 -213
- cuda/cuda-fp16/genai_config.json +1 -1
- cuda/cuda-fp16/phi3-mini-128k-instruct-cuda-fp16.onnx +1 -1
- cuda/cuda-fp16/phi3-mini-128k-instruct-cuda-fp16.onnx.data +1 -1
- cuda/cuda-fp16/special_tokens_map.json +30 -30
- cuda/cuda-fp16/tokenizer.json +0 -0
- cuda/cuda-fp16/tokenizer_config.json +130 -130
- cuda/cuda-int4-awq-block-32/added_tokens.json +13 -0
- cuda/cuda-int4-awq-block-32/config.json +138 -0
- cuda/cuda-int4-awq-block-32/configuration_phi3.py +227 -0
- cuda/cuda-int4-awq-block-32/genai_config.json +59 -0
- cuda/cuda-int4-awq-block-32/phi3-mini-128k-instruct-cuda-int4-awq-block-128.onnx +3 -0
- cuda/cuda-int4-awq-block-32/phi3-mini-128k-instruct-cuda-int4-awq-block-128.onnx.data +3 -0
- cuda/cuda-int4-awq-block-32/special_tokens_map.json +30 -0
- cuda/cuda-int4-awq-block-32/tokenizer.json +0 -0
- cuda/cuda-int4-awq-block-32/tokenizer.model +3 -0
- cuda/cuda-int4-awq-block-32/tokenizer_config.json +130 -0
- cuda/cuda-int4-rtn-block-32/added_tokens.json +13 -13
- cuda/cuda-int4-rtn-block-32/config.json +138 -137
- cuda/cuda-int4-rtn-block-32/configuration_phi3.py +227 -213
config.json
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{
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"_name_or_path": "
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"architectures": [
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"Phi3ForCausalLM"
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],
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"attention_dropout": 0.0,
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"auto_map": {
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"AutoConfig": "configuration_phi3.Phi3Config",
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"AutoModelForCausalLM": "modeling_phi3.Phi3ForCausalLM"
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},
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"bos_token_id": 1,
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"embd_pdrop": 0.0,
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"eos_token_id": 32000,
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"hidden_act": "silu",
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"hidden_size": 3072,
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"initializer_range": 0.02,
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"intermediate_size": 8192,
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"max_position_embeddings": 131072,
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"model_type": "phi3",
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"num_attention_heads": 32,
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}
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configuration_phi3.py
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# coding=utf-8
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# Copyright 2024 Microsoft and the HuggingFace Inc. team. 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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""" Phi-3 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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logger = logging.get_logger(__name__)
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PHI3_PRETRAINED_CONFIG_ARCHIVE_MAP = {
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"microsoft/Phi-3-mini-4k-instruct": "https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/resolve/main/config.json",
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"microsoft/Phi-3-mini-128k-instruct": "https://huggingface.co/microsoft/Phi-3-mini-128k-instruct/resolve/main/config.json",
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}
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class Phi3Config(PretrainedConfig):
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r"""
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This is the configuration class to store the configuration of a [`Phi3Model`]. It is used to instantiate a Phi-3
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model according to the specified arguments, defining the model architecture. Instantiating a configuration with the
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defaults will yield a similar configuration to that of the
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[microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct).
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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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Args:
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vocab_size (`int`, *optional*, defaults to 32064):
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Vocabulary size of the Phi-3 model. Defines the number of different tokens that can be represented by the
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`inputs_ids` passed when calling [`Phi3Model`].
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hidden_size (`int`, *optional*, defaults to 3072):
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Dimension of the hidden representations.
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intermediate_size (`int`, *optional*, defaults to 8192):
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Dimension of the MLP representations.
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num_hidden_layers (`int`, *optional*, defaults to 32):
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Number of hidden layers in the Transformer decoder.
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num_attention_heads (`int`, *optional*, defaults to 32):
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Number of attention heads for each attention layer in the Transformer decoder.
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num_key_value_heads (`int`, *optional*):
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This is the number of key_value heads that should be used to implement Grouped Query Attention. If
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`num_key_value_heads=num_attention_heads`, the model will use Multi Head Attention (MHA), if
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| 56 |
-
`num_key_value_heads=1 the model will use Multi Query Attention (MQA) otherwise GQA is used. When
|
| 57 |
-
converting a multi-head checkpoint to a GQA checkpoint, each group key and value head should be constructed
|
| 58 |
-
by meanpooling all the original heads within that group. For more details checkout [this
|
| 59 |
-
paper](https://arxiv.org/pdf/2305.13245.pdf). If it is not specified, will default to
|
| 60 |
-
`num_attention_heads`.
|
| 61 |
-
resid_pdrop (`float`, *optional*, defaults to 0.0):
|
| 62 |
-
Dropout probability for mlp outputs.
|
| 63 |
-
embd_pdrop (`int`, *optional*, defaults to 0.0):
|
| 64 |
-
The dropout ratio for the embeddings.
|
| 65 |
-
attention_dropout (`float`, *optional*, defaults to 0.0):
|
| 66 |
-
The dropout ratio after computing the attention scores.
|
| 67 |
-
hidden_act (`str` or `function`, *optional*, defaults to `"silu"`):
|
| 68 |
-
The non-linear activation function (function or string) in the decoder.
|
| 69 |
-
max_position_embeddings (`int`, *optional*, defaults to 4096):
|
| 70 |
-
The maximum sequence length that this model might ever be used with.
|
| 71 |
-
original_max_position_embeddings (`int`, *optional*, defaults to 4096):
|
| 72 |
-
The maximum sequence length that this model was trained with. This is used to determine the size of the
|
| 73 |
-
original RoPE embeddings when using long scaling.
|
| 74 |
-
initializer_range (`float`, *optional*, defaults to 0.02):
|
| 75 |
-
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
|
| 76 |
-
rms_norm_eps (`float`, *optional*, defaults to 1e-05):
|
| 77 |
-
The epsilon value used for the RMSNorm.
|
| 78 |
-
use_cache (`bool`, *optional*, defaults to `True`):
|
| 79 |
-
Whether or not the model should return the last key/values attentions (not used by all models). Only
|
| 80 |
-
relevant if `config.is_decoder=True`. Whether to tie weight embeddings or not.
|
| 81 |
-
tie_word_embeddings (`bool`, *optional*, defaults to `False`):
|
| 82 |
-
Whether to tie weight embeddings
|
| 83 |
-
rope_theta (`float`, *optional*, defaults to 10000.0):
|
| 84 |
-
The base period of the RoPE embeddings.
|
| 85 |
-
rope_scaling (`dict`, *optional*):
|
| 86 |
-
The scaling strategy for the RoPE embeddings. If `None`, no scaling is applied. If a dictionary, it must
|
| 87 |
-
contain the following keys: `type`, `short_factor` and `long_factor`. The `type` must be
|
| 88 |
-
the `short_factor` and `long_factor` must be lists of numbers with the same length as the hidden size
|
| 89 |
-
divided by the number of attention heads divided by 2.
|
| 90 |
-
bos_token_id (`int`, *optional*, defaults to 1):
|
| 91 |
-
The id of the "beginning-of-sequence" token.
|
| 92 |
-
eos_token_id (`int`, *optional*, defaults to 32000):
|
| 93 |
-
The id of the "end-of-sequence" token.
|
| 94 |
-
pad_token_id (`int`, *optional*, defaults to 32000):
|
| 95 |
-
The id of the padding token.
|
| 96 |
-
sliding_window (`int`, *optional*):
|
| 97 |
-
Sliding window attention window size. If `None`, no sliding window is applied.
|
| 98 |
-
|
| 99 |
-
Example:
|
| 100 |
-
|
| 101 |
-
```python
|
| 102 |
-
>>> from transformers import Phi3Model, Phi3Config
|
| 103 |
-
|
| 104 |
-
>>> # Initializing a Phi-3 style configuration
|
| 105 |
-
>>> configuration = Phi3Config.from_pretrained("microsoft/Phi-3-mini-4k-instruct")
|
| 106 |
-
|
| 107 |
-
>>> # Initializing a model from the configuration
|
| 108 |
-
>>> model = Phi3Model(configuration)
|
| 109 |
-
|
| 110 |
-
>>> # Accessing the model configuration
|
| 111 |
-
>>> configuration = model.config
|
| 112 |
-
```"""
|
| 113 |
-
|
| 114 |
-
model_type = "phi3"
|
| 115 |
-
keys_to_ignore_at_inference = ["past_key_values"]
|
| 116 |
-
|
| 117 |
-
def __init__(
|
| 118 |
-
self,
|
| 119 |
-
vocab_size=32064,
|
| 120 |
-
hidden_size=3072,
|
| 121 |
-
intermediate_size=8192,
|
| 122 |
-
num_hidden_layers=32,
|
| 123 |
-
num_attention_heads=32,
|
| 124 |
-
num_key_value_heads=None,
|
| 125 |
-
resid_pdrop=0.0,
|
| 126 |
-
embd_pdrop=0.0,
|
| 127 |
-
attention_dropout=0.0,
|
| 128 |
-
hidden_act="silu",
|
| 129 |
-
max_position_embeddings=4096,
|
| 130 |
-
original_max_position_embeddings=4096,
|
| 131 |
-
initializer_range=0.02,
|
| 132 |
-
rms_norm_eps=1e-5,
|
| 133 |
-
use_cache=True,
|
| 134 |
-
tie_word_embeddings=False,
|
| 135 |
-
rope_theta=10000.0,
|
| 136 |
-
rope_scaling=None,
|
| 137 |
-
bos_token_id=1,
|
| 138 |
-
eos_token_id=32000,
|
| 139 |
-
pad_token_id=32000,
|
| 140 |
-
sliding_window=None,
|
| 141 |
-
**kwargs,
|
| 142 |
-
):
|
| 143 |
-
self.vocab_size = vocab_size
|
| 144 |
-
self.hidden_size = hidden_size
|
| 145 |
-
self.intermediate_size = intermediate_size
|
| 146 |
-
self.num_hidden_layers = num_hidden_layers
|
| 147 |
-
self.num_attention_heads = num_attention_heads
|
| 148 |
-
|
| 149 |
-
if num_key_value_heads is None:
|
| 150 |
-
num_key_value_heads = num_attention_heads
|
| 151 |
-
|
| 152 |
-
self.num_key_value_heads = num_key_value_heads
|
| 153 |
-
self.resid_pdrop = resid_pdrop
|
| 154 |
-
self.embd_pdrop = embd_pdrop
|
| 155 |
-
self.attention_dropout = attention_dropout
|
| 156 |
-
self.hidden_act = hidden_act
|
| 157 |
-
self.max_position_embeddings = max_position_embeddings
|
| 158 |
-
self.original_max_position_embeddings = original_max_position_embeddings
|
| 159 |
-
self.initializer_range = initializer_range
|
| 160 |
-
self.rms_norm_eps = rms_norm_eps
|
| 161 |
-
self.use_cache = use_cache
|
| 162 |
-
self.rope_theta = rope_theta
|
| 163 |
-
self.rope_scaling = rope_scaling
|
| 164 |
-
self.
|
| 165 |
-
self.
|
| 166 |
-
|
| 167 |
-
|
| 168 |
-
|
| 169 |
-
|
| 170 |
-
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| 171 |
-
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-
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-
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-
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-
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-
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-
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| 178 |
-
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| 179 |
-
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| 180 |
-
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| 181 |
-
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| 182 |
-
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| 183 |
-
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| 184 |
-
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| 185 |
-
|
| 186 |
-
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| 187 |
-
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| 188 |
-
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| 189 |
-
|
| 190 |
-
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| 191 |
-
|
| 192 |
-
|
| 193 |
-
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| 194 |
-
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| 195 |
-
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| 196 |
-
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| 197 |
-
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| 198 |
-
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-
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| 200 |
-
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-
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-
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-
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-
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-
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-
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-
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-
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-
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|
|
| 1 |
+
# coding=utf-8
|
| 2 |
+
# Copyright 2024 Microsoft and the HuggingFace Inc. team. All rights reserved.
|
| 3 |
+
#
|
| 4 |
+
# Licensed under the Apache License, Version 2.0 (the "License");
|
| 5 |
+
# you may not use this file except in compliance with the License.
|
| 6 |
+
# You may obtain a copy of the License at
|
| 7 |
+
#
|
| 8 |
+
# http://www.apache.org/licenses/LICENSE-2.0
|
| 9 |
+
#
|
| 10 |
+
# Unless required by applicable law or agreed to in writing, software
|
| 11 |
+
# distributed under the License is distributed on an "AS IS" BASIS,
|
| 12 |
+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
| 13 |
+
# See the License for the specific language governing permissions and
|
| 14 |
+
# limitations under the License.
|
| 15 |
+
|
| 16 |
+
""" Phi-3 model configuration"""
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
from transformers.configuration_utils import PretrainedConfig
|
| 20 |
+
from transformers.utils import logging
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
logger = logging.get_logger(__name__)
|
| 24 |
+
|
| 25 |
+
PHI3_PRETRAINED_CONFIG_ARCHIVE_MAP = {
|
| 26 |
+
"microsoft/Phi-3-mini-4k-instruct": "https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/resolve/main/config.json",
|
| 27 |
+
"microsoft/Phi-3-mini-128k-instruct": "https://huggingface.co/microsoft/Phi-3-mini-128k-instruct/resolve/main/config.json",
|
| 28 |
+
}
|
| 29 |
+
|
| 30 |
+
|
| 31 |
+
class Phi3Config(PretrainedConfig):
|
| 32 |
+
r"""
|
| 33 |
+
This is the configuration class to store the configuration of a [`Phi3Model`]. It is used to instantiate a Phi-3
|
| 34 |
+
model according to the specified arguments, defining the model architecture. Instantiating a configuration with the
|
| 35 |
+
defaults will yield a similar configuration to that of the
|
| 36 |
+
[microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct).
|
| 37 |
+
|
| 38 |
+
Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
|
| 39 |
+
documentation from [`PretrainedConfig`] for more information.
|
| 40 |
+
|
| 41 |
+
Args:
|
| 42 |
+
vocab_size (`int`, *optional*, defaults to 32064):
|
| 43 |
+
Vocabulary size of the Phi-3 model. Defines the number of different tokens that can be represented by the
|
| 44 |
+
`inputs_ids` passed when calling [`Phi3Model`].
|
| 45 |
+
hidden_size (`int`, *optional*, defaults to 3072):
|
| 46 |
+
Dimension of the hidden representations.
|
| 47 |
+
intermediate_size (`int`, *optional*, defaults to 8192):
|
| 48 |
+
Dimension of the MLP representations.
|
| 49 |
+
num_hidden_layers (`int`, *optional*, defaults to 32):
|
| 50 |
+
Number of hidden layers in the Transformer decoder.
|
| 51 |
+
num_attention_heads (`int`, *optional*, defaults to 32):
|
| 52 |
+
Number of attention heads for each attention layer in the Transformer decoder.
|
| 53 |
+
num_key_value_heads (`int`, *optional*):
|
| 54 |
+
This is the number of key_value heads that should be used to implement Grouped Query Attention. If
|
| 55 |
+
`num_key_value_heads=num_attention_heads`, the model will use Multi Head Attention (MHA), if
|
| 56 |
+
`num_key_value_heads=1 the model will use Multi Query Attention (MQA) otherwise GQA is used. When
|
| 57 |
+
converting a multi-head checkpoint to a GQA checkpoint, each group key and value head should be constructed
|
| 58 |
+
by meanpooling all the original heads within that group. For more details checkout [this
|
| 59 |
+
paper](https://arxiv.org/pdf/2305.13245.pdf). If it is not specified, will default to
|
| 60 |
+
`num_attention_heads`.
|
| 61 |
+
resid_pdrop (`float`, *optional*, defaults to 0.0):
|
| 62 |
+
Dropout probability for mlp outputs.
|
| 63 |
+
embd_pdrop (`int`, *optional*, defaults to 0.0):
|
| 64 |
+
The dropout ratio for the embeddings.
|
| 65 |
+
attention_dropout (`float`, *optional*, defaults to 0.0):
|
| 66 |
+
The dropout ratio after computing the attention scores.
|
| 67 |
+
hidden_act (`str` or `function`, *optional*, defaults to `"silu"`):
|
| 68 |
+
The non-linear activation function (function or string) in the decoder.
|
| 69 |
+
max_position_embeddings (`int`, *optional*, defaults to 4096):
|
| 70 |
+
The maximum sequence length that this model might ever be used with.
|
| 71 |
+
original_max_position_embeddings (`int`, *optional*, defaults to 4096):
|
| 72 |
+
The maximum sequence length that this model was trained with. This is used to determine the size of the
|
| 73 |
+
original RoPE embeddings when using long scaling.
|
| 74 |
+
initializer_range (`float`, *optional*, defaults to 0.02):
|
| 75 |
+
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
|
| 76 |
+
rms_norm_eps (`float`, *optional*, defaults to 1e-05):
|
| 77 |
+
The epsilon value used for the RMSNorm.
|
| 78 |
+
use_cache (`bool`, *optional*, defaults to `True`):
|
| 79 |
+
Whether or not the model should return the last key/values attentions (not used by all models). Only
|
| 80 |
+
relevant if `config.is_decoder=True`. Whether to tie weight embeddings or not.
|
| 81 |
+
tie_word_embeddings (`bool`, *optional*, defaults to `False`):
|
| 82 |
+
Whether to tie weight embeddings
|
| 83 |
+
rope_theta (`float`, *optional*, defaults to 10000.0):
|
| 84 |
+
The base period of the RoPE embeddings.
|
| 85 |
+
rope_scaling (`dict`, *optional*):
|
| 86 |
+
The scaling strategy for the RoPE embeddings. If `None`, no scaling is applied. If a dictionary, it must
|
| 87 |
+
contain the following keys: `type`, `short_factor` and `long_factor`. The `type` must be `longrope` and
|
| 88 |
+
the `short_factor` and `long_factor` must be lists of numbers with the same length as the hidden size
|
| 89 |
+
divided by the number of attention heads divided by 2.
|
| 90 |
+
bos_token_id (`int`, *optional*, defaults to 1):
|
| 91 |
+
The id of the "beginning-of-sequence" token.
|
| 92 |
+
eos_token_id (`int`, *optional*, defaults to 32000):
|
| 93 |
+
The id of the "end-of-sequence" token.
|
| 94 |
+
pad_token_id (`int`, *optional*, defaults to 32000):
|
| 95 |
+
The id of the padding token.
|
| 96 |
+
sliding_window (`int`, *optional*):
|
| 97 |
+
Sliding window attention window size. If `None`, no sliding window is applied.
|
| 98 |
+
|
| 99 |
+
Example:
|
| 100 |
+
|
| 101 |
+
```python
|
| 102 |
+
>>> from transformers import Phi3Model, Phi3Config
|
| 103 |
+
|
| 104 |
+
>>> # Initializing a Phi-3 style configuration
|
| 105 |
+
>>> configuration = Phi3Config.from_pretrained("microsoft/Phi-3-mini-4k-instruct")
|
| 106 |
+
|
| 107 |
+
>>> # Initializing a model from the configuration
|
| 108 |
+
>>> model = Phi3Model(configuration)
|
| 109 |
+
|
| 110 |
+
>>> # Accessing the model configuration
|
| 111 |
+
>>> configuration = model.config
|
| 112 |
+
```"""
|
| 113 |
+
|
| 114 |
+
model_type = "phi3"
|
| 115 |
+
keys_to_ignore_at_inference = ["past_key_values"]
|
| 116 |
+
|
| 117 |
+
def __init__(
|
| 118 |
+
self,
|
| 119 |
+
vocab_size=32064,
|
| 120 |
+
hidden_size=3072,
|
| 121 |
+
intermediate_size=8192,
|
| 122 |
+
num_hidden_layers=32,
|
| 123 |
+
num_attention_heads=32,
|
| 124 |
+
num_key_value_heads=None,
|
| 125 |
+
resid_pdrop=0.0,
|
| 126 |
+
embd_pdrop=0.0,
|
| 127 |
+
attention_dropout=0.0,
|
| 128 |
+
hidden_act="silu",
|
| 129 |
+
max_position_embeddings=4096,
|
| 130 |
+
original_max_position_embeddings=4096,
|
| 131 |
+
initializer_range=0.02,
|
| 132 |
+
rms_norm_eps=1e-5,
|
| 133 |
+
use_cache=True,
|
| 134 |
+
tie_word_embeddings=False,
|
| 135 |
+
rope_theta=10000.0,
|
| 136 |
+
rope_scaling=None,
|
| 137 |
+
bos_token_id=1,
|
| 138 |
+
eos_token_id=32000,
|
| 139 |
+
pad_token_id=32000,
|
| 140 |
+
sliding_window=None,
|
| 141 |
+
**kwargs,
|
| 142 |
+
):
|
| 143 |
+
self.vocab_size = vocab_size
|
| 144 |
+
self.hidden_size = hidden_size
|
| 145 |
+
self.intermediate_size = intermediate_size
|
| 146 |
+
self.num_hidden_layers = num_hidden_layers
|
| 147 |
+
self.num_attention_heads = num_attention_heads
|
| 148 |
+
|
| 149 |
+
if num_key_value_heads is None:
|
| 150 |
+
num_key_value_heads = num_attention_heads
|
| 151 |
+
|
| 152 |
+
self.num_key_value_heads = num_key_value_heads
|
| 153 |
+
self.resid_pdrop = resid_pdrop
|
| 154 |
+
self.embd_pdrop = embd_pdrop
|
| 155 |
+
self.attention_dropout = attention_dropout
|
| 156 |
+
self.hidden_act = hidden_act
|
| 157 |
+
self.max_position_embeddings = max_position_embeddings
|
| 158 |
+
self.original_max_position_embeddings = original_max_position_embeddings
|
| 159 |
+
self.initializer_range = initializer_range
|
| 160 |
+
self.rms_norm_eps = rms_norm_eps
|
| 161 |
+
self.use_cache = use_cache
|
| 162 |
+
self.rope_theta = rope_theta
|
| 163 |
+
self.rope_scaling = rope_scaling
|
| 164 |
+
self._rope_scaling_adjustment()
|
| 165 |
+
self._rope_scaling_validation()
|
| 166 |
+
self.sliding_window = sliding_window
|
| 167 |
+
|
| 168 |
+
super().__init__(
|
| 169 |
+
bos_token_id=bos_token_id,
|
| 170 |
+
eos_token_id=eos_token_id,
|
| 171 |
+
pad_token_id=pad_token_id,
|
| 172 |
+
tie_word_embeddings=tie_word_embeddings,
|
| 173 |
+
**kwargs,
|
| 174 |
+
)
|
| 175 |
+
|
| 176 |
+
def _rope_scaling_adjustment(self):
|
| 177 |
+
"""
|
| 178 |
+
Adjust the `type` of the `rope_scaling` configuration for backward compatibility.
|
| 179 |
+
"""
|
| 180 |
+
if self.rope_scaling is None:
|
| 181 |
+
return
|
| 182 |
+
|
| 183 |
+
rope_scaling_type = self.rope_scaling.get("type", None)
|
| 184 |
+
|
| 185 |
+
# For backward compatibility if previous version used "su" or "yarn"
|
| 186 |
+
if rope_scaling_type is not None and rope_scaling_type in ["su", "yarn"]:
|
| 187 |
+
self.rope_scaling["type"] = "longrope"
|
| 188 |
+
|
| 189 |
+
def _rope_scaling_validation(self):
|
| 190 |
+
"""
|
| 191 |
+
Validate the `rope_scaling` configuration.
|
| 192 |
+
"""
|
| 193 |
+
if self.rope_scaling is None:
|
| 194 |
+
return
|
| 195 |
+
|
| 196 |
+
if not isinstance(self.rope_scaling, dict) or len(self.rope_scaling) != 3:
|
| 197 |
+
raise ValueError(
|
| 198 |
+
"`rope_scaling` must be a dictionary with three fields, `type`, `short_factor` and `long_factor`, "
|
| 199 |
+
f"got {self.rope_scaling}"
|
| 200 |
+
)
|
| 201 |
+
rope_scaling_type = self.rope_scaling.get("type", None)
|
| 202 |
+
rope_scaling_short_factor = self.rope_scaling.get("short_factor", None)
|
| 203 |
+
rope_scaling_long_factor = self.rope_scaling.get("long_factor", None)
|
| 204 |
+
if rope_scaling_type is None or rope_scaling_type not in ["longrope"]:
|
| 205 |
+
raise ValueError(f"`rope_scaling`'s type field must be one of ['longrope'], got {rope_scaling_type}")
|
| 206 |
+
if not (
|
| 207 |
+
isinstance(rope_scaling_short_factor, list)
|
| 208 |
+
and all(isinstance(x, (int, float)) for x in rope_scaling_short_factor)
|
| 209 |
+
):
|
| 210 |
+
raise ValueError(
|
| 211 |
+
f"`rope_scaling`'s short_factor field must be a list of numbers, got {rope_scaling_short_factor}"
|
| 212 |
+
)
|
| 213 |
+
if not len(rope_scaling_short_factor) == self.hidden_size // self.num_attention_heads // 2:
|
| 214 |
+
raise ValueError(
|
| 215 |
+
f"`rope_scaling`'s short_factor field must have length {self.hidden_size // self.num_attention_heads // 2}, got {len(rope_scaling_short_factor)}"
|
| 216 |
+
)
|
| 217 |
+
if not (
|
| 218 |
+
isinstance(rope_scaling_long_factor, list)
|
| 219 |
+
and all(isinstance(x, (int, float)) for x in rope_scaling_long_factor)
|
| 220 |
+
):
|
| 221 |
+
raise ValueError(
|
| 222 |
+
f"`rope_scaling`'s long_factor field must be a list of numbers, got {rope_scaling_long_factor}"
|
| 223 |
+
)
|
| 224 |
+
if not len(rope_scaling_long_factor) == self.hidden_size // self.num_attention_heads // 2:
|
| 225 |
+
raise ValueError(
|
| 226 |
+
f"`rope_scaling`'s long_factor field must have length {self.hidden_size // self.num_attention_heads // 2}, got {len(rope_scaling_long_factor)}"
|
| 227 |
+
)
|
cpu_and_mobile/cpu-int4-awq-block-128/added_tokens.json
ADDED
|
@@ -0,0 +1,13 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"<|endoftext|>": 32000,
|
| 3 |
+
"<|assistant|>": 32001,
|
| 4 |
+
"<|placeholder1|>": 32002,
|
| 5 |
+
"<|placeholder2|>": 32003,
|
| 6 |
+
"<|placeholder3|>": 32004,
|
| 7 |
+
"<|placeholder4|>": 32005,
|
| 8 |
+
"<|system|>": 32006,
|
| 9 |
+
"<|end|>": 32007,
|
| 10 |
+
"<|placeholder5|>": 32008,
|
| 11 |
+
"<|placeholder6|>": 32009,
|
| 12 |
+
"<|user|>": 32010
|
| 13 |
+
}
|
cpu_and_mobile/cpu-int4-awq-block-128/config.json
ADDED
|
@@ -0,0 +1,138 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_name_or_path": "Phi-3-mini-128k-instruct",
|
| 3 |
+
"architectures": [
|
| 4 |
+
"Phi3ForCausalLM"
|
| 5 |
+
],
|
| 6 |
+
"attention_dropout": 0.0,
|
| 7 |
+
"auto_map": {
|
| 8 |
+
"AutoConfig": "configuration_phi3.Phi3Config",
|
| 9 |
+
"AutoModelForCausalLM": "modeling_phi3.Phi3ForCausalLM"
|
| 10 |
+
},
|
| 11 |
+
"bos_token_id": 1,
|
| 12 |
+
"embd_pdrop": 0.0,
|
| 13 |
+
"eos_token_id": 32000,
|
| 14 |
+
"hidden_act": "silu",
|
| 15 |
+
"hidden_size": 3072,
|
| 16 |
+
"initializer_range": 0.02,
|
| 17 |
+
"intermediate_size": 8192,
|
| 18 |
+
"max_position_embeddings": 131072,
|
| 19 |
+
"model_type": "phi3",
|
| 20 |
+
"num_attention_heads": 32,
|
| 21 |
+
"num_hidden_layers": 32,
|
| 22 |
+
"num_key_value_heads": 32,
|
| 23 |
+
"original_max_position_embeddings": 4096,
|
| 24 |
+
"pad_token_id": 32000,
|
| 25 |
+
"resid_pdrop": 0.0,
|
| 26 |
+
"rms_norm_eps": 1e-05,
|
| 27 |
+
"rope_scaling": {
|
| 28 |
+
"long_factor": [
|
| 29 |
+
1.0700000524520874,
|
| 30 |
+
1.1200000047683716,
|
| 31 |
+
1.149999976158142,
|
| 32 |
+
1.4199999570846558,
|
| 33 |
+
1.5699999332427979,
|
| 34 |
+
1.7999999523162842,
|
| 35 |
+
2.129999876022339,
|
| 36 |
+
2.129999876022339,
|
| 37 |
+
3.009999990463257,
|
| 38 |
+
5.910000324249268,
|
| 39 |
+
6.950000286102295,
|
| 40 |
+
9.070000648498535,
|
| 41 |
+
9.930000305175781,
|
| 42 |
+
10.710000038146973,
|
| 43 |
+
11.130000114440918,
|
| 44 |
+
14.609999656677246,
|
| 45 |
+
15.409998893737793,
|
| 46 |
+
19.809999465942383,
|
| 47 |
+
37.279998779296875,
|
| 48 |
+
38.279998779296875,
|
| 49 |
+
38.599998474121094,
|
| 50 |
+
40.12000274658203,
|
| 51 |
+
46.20000457763672,
|
| 52 |
+
50.940006256103516,
|
| 53 |
+
53.66000747680664,
|
| 54 |
+
54.9373893737793,
|
| 55 |
+
56.89738845825195,
|
| 56 |
+
57.28738784790039,
|
| 57 |
+
59.98738479614258,
|
| 58 |
+
60.86738586425781,
|
| 59 |
+
60.887386322021484,
|
| 60 |
+
61.71739196777344,
|
| 61 |
+
62.91739273071289,
|
| 62 |
+
62.957393646240234,
|
| 63 |
+
63.41739273071289,
|
| 64 |
+
63.8173942565918,
|
| 65 |
+
63.83739471435547,
|
| 66 |
+
63.897396087646484,
|
| 67 |
+
63.93739700317383,
|
| 68 |
+
64.06739807128906,
|
| 69 |
+
64.11434936523438,
|
| 70 |
+
64.12435150146484,
|
| 71 |
+
64.15435028076172,
|
| 72 |
+
64.19435119628906,
|
| 73 |
+
64.24435424804688,
|
| 74 |
+
64.57435607910156,
|
| 75 |
+
64.69000244140625,
|
| 76 |
+
64.76000213623047
|
| 77 |
+
],
|
| 78 |
+
"short_factor": [
|
| 79 |
+
1.1,
|
| 80 |
+
1.1,
|
| 81 |
+
1.1,
|
| 82 |
+
1.3000000000000003,
|
| 83 |
+
1.3500000000000003,
|
| 84 |
+
1.3500000000000003,
|
| 85 |
+
1.4000000000000004,
|
| 86 |
+
1.5500000000000005,
|
| 87 |
+
2.000000000000001,
|
| 88 |
+
2.000000000000001,
|
| 89 |
+
2.000000000000001,
|
| 90 |
+
2.000000000000001,
|
| 91 |
+
2.000000000000001,
|
| 92 |
+
2.000000000000001,
|
| 93 |
+
2.000000000000001,
|
| 94 |
+
2.000000000000001,
|
| 95 |
+
2.000000000000001,
|
| 96 |
+
2.000000000000001,
|
| 97 |
+
2.000000000000001,
|
| 98 |
+
2.000000000000001,
|
| 99 |
+
2.000000000000001,
|
| 100 |
+
2.000000000000001,
|
| 101 |
+
2.000000000000001,
|
| 102 |
+
2.000000000000001,
|
| 103 |
+
2.000000000000001,
|
| 104 |
+
2.0500000000000007,
|
| 105 |
+
2.0500000000000007,
|
| 106 |
+
2.0500000000000007,
|
| 107 |
+
2.0500000000000007,
|
| 108 |
+
2.0500000000000007,
|
| 109 |
+
2.0500000000000007,
|
| 110 |
+
2.1000000000000005,
|
| 111 |
+
2.1000000000000005,
|
| 112 |
+
2.1500000000000004,
|
| 113 |
+
2.25,
|
| 114 |
+
2.25,
|
| 115 |
+
2.25,
|
| 116 |
+
2.25,
|
| 117 |
+
2.25,
|
| 118 |
+
2.3999999999999995,
|
| 119 |
+
2.4499999999999993,
|
| 120 |
+
2.499999999999999,
|
| 121 |
+
2.6999999999999984,
|
| 122 |
+
2.6999999999999984,
|
| 123 |
+
2.7499999999999982,
|
| 124 |
+
2.799999999999998,
|
| 125 |
+
2.8999999999999977,
|
| 126 |
+
3.049999999999997
|
| 127 |
+
],
|
| 128 |
+
"type": "longrope"
|
| 129 |
+
},
|
| 130 |
+
"rope_theta": 10000.0,
|
| 131 |
+
"sliding_window": 262144,
|
| 132 |
+
"tie_word_embeddings": false,
|
| 133 |
+
"torch_dtype": "bfloat16",
|
| 134 |
+
"transformers_version": "4.40.2",
|
| 135 |
+
"use_cache": true,
|
| 136 |
+
"attention_bias": false,
|
| 137 |
+
"vocab_size": 32064
|
| 138 |
+
}
|
cpu_and_mobile/cpu-int4-awq-block-128/configuration_phi3.py
ADDED
|
@@ -0,0 +1,227 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# coding=utf-8
|
| 2 |
+
# Copyright 2024 Microsoft and the HuggingFace Inc. team. All rights reserved.
|
| 3 |
+
#
|
| 4 |
+
# Licensed under the Apache License, Version 2.0 (the "License");
|
| 5 |
+
# you may not use this file except in compliance with the License.
|
| 6 |
+
# You may obtain a copy of the License at
|
| 7 |
+
#
|
| 8 |
+
# http://www.apache.org/licenses/LICENSE-2.0
|
| 9 |
+
#
|
| 10 |
+
# Unless required by applicable law or agreed to in writing, software
|
| 11 |
+
# distributed under the License is distributed on an "AS IS" BASIS,
|
| 12 |
+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
| 13 |
+
# See the License for the specific language governing permissions and
|
| 14 |
+
# limitations under the License.
|
| 15 |
+
|
| 16 |
+
""" Phi-3 model configuration"""
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
from transformers.configuration_utils import PretrainedConfig
|
| 20 |
+
from transformers.utils import logging
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
logger = logging.get_logger(__name__)
|
| 24 |
+
|
| 25 |
+
PHI3_PRETRAINED_CONFIG_ARCHIVE_MAP = {
|
| 26 |
+
"microsoft/Phi-3-mini-4k-instruct": "https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/resolve/main/config.json",
|
| 27 |
+
"microsoft/Phi-3-mini-128k-instruct": "https://huggingface.co/microsoft/Phi-3-mini-128k-instruct/resolve/main/config.json",
|
| 28 |
+
}
|
| 29 |
+
|
| 30 |
+
|
| 31 |
+
class Phi3Config(PretrainedConfig):
|
| 32 |
+
r"""
|
| 33 |
+
This is the configuration class to store the configuration of a [`Phi3Model`]. It is used to instantiate a Phi-3
|
| 34 |
+
model according to the specified arguments, defining the model architecture. Instantiating a configuration with the
|
| 35 |
+
defaults will yield a similar configuration to that of the
|
| 36 |
+
[microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct).
|
| 37 |
+
|
| 38 |
+
Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
|
| 39 |
+
documentation from [`PretrainedConfig`] for more information.
|
| 40 |
+
|
| 41 |
+
Args:
|
| 42 |
+
vocab_size (`int`, *optional*, defaults to 32064):
|
| 43 |
+
Vocabulary size of the Phi-3 model. Defines the number of different tokens that can be represented by the
|
| 44 |
+
`inputs_ids` passed when calling [`Phi3Model`].
|
| 45 |
+
hidden_size (`int`, *optional*, defaults to 3072):
|
| 46 |
+
Dimension of the hidden representations.
|
| 47 |
+
intermediate_size (`int`, *optional*, defaults to 8192):
|
| 48 |
+
Dimension of the MLP representations.
|
| 49 |
+
num_hidden_layers (`int`, *optional*, defaults to 32):
|
| 50 |
+
Number of hidden layers in the Transformer decoder.
|
| 51 |
+
num_attention_heads (`int`, *optional*, defaults to 32):
|
| 52 |
+
Number of attention heads for each attention layer in the Transformer decoder.
|
| 53 |
+
num_key_value_heads (`int`, *optional*):
|
| 54 |
+
This is the number of key_value heads that should be used to implement Grouped Query Attention. If
|
| 55 |
+
`num_key_value_heads=num_attention_heads`, the model will use Multi Head Attention (MHA), if
|
| 56 |
+
`num_key_value_heads=1 the model will use Multi Query Attention (MQA) otherwise GQA is used. When
|
| 57 |
+
converting a multi-head checkpoint to a GQA checkpoint, each group key and value head should be constructed
|
| 58 |
+
by meanpooling all the original heads within that group. For more details checkout [this
|
| 59 |
+
paper](https://arxiv.org/pdf/2305.13245.pdf). If it is not specified, will default to
|
| 60 |
+
`num_attention_heads`.
|
| 61 |
+
resid_pdrop (`float`, *optional*, defaults to 0.0):
|
| 62 |
+
Dropout probability for mlp outputs.
|
| 63 |
+
embd_pdrop (`int`, *optional*, defaults to 0.0):
|
| 64 |
+
The dropout ratio for the embeddings.
|
| 65 |
+
attention_dropout (`float`, *optional*, defaults to 0.0):
|
| 66 |
+
The dropout ratio after computing the attention scores.
|
| 67 |
+
hidden_act (`str` or `function`, *optional*, defaults to `"silu"`):
|
| 68 |
+
The non-linear activation function (function or string) in the decoder.
|
| 69 |
+
max_position_embeddings (`int`, *optional*, defaults to 4096):
|
| 70 |
+
The maximum sequence length that this model might ever be used with.
|
| 71 |
+
original_max_position_embeddings (`int`, *optional*, defaults to 4096):
|
| 72 |
+
The maximum sequence length that this model was trained with. This is used to determine the size of the
|
| 73 |
+
original RoPE embeddings when using long scaling.
|
| 74 |
+
initializer_range (`float`, *optional*, defaults to 0.02):
|
| 75 |
+
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
|
| 76 |
+
rms_norm_eps (`float`, *optional*, defaults to 1e-05):
|
| 77 |
+
The epsilon value used for the RMSNorm.
|
| 78 |
+
use_cache (`bool`, *optional*, defaults to `True`):
|
| 79 |
+
Whether or not the model should return the last key/values attentions (not used by all models). Only
|
| 80 |
+
relevant if `config.is_decoder=True`. Whether to tie weight embeddings or not.
|
| 81 |
+
tie_word_embeddings (`bool`, *optional*, defaults to `False`):
|
| 82 |
+
Whether to tie weight embeddings
|
| 83 |
+
rope_theta (`float`, *optional*, defaults to 10000.0):
|
| 84 |
+
The base period of the RoPE embeddings.
|
| 85 |
+
rope_scaling (`dict`, *optional*):
|
| 86 |
+
The scaling strategy for the RoPE embeddings. If `None`, no scaling is applied. If a dictionary, it must
|
| 87 |
+
contain the following keys: `type`, `short_factor` and `long_factor`. The `type` must be `longrope` and
|
| 88 |
+
the `short_factor` and `long_factor` must be lists of numbers with the same length as the hidden size
|
| 89 |
+
divided by the number of attention heads divided by 2.
|
| 90 |
+
bos_token_id (`int`, *optional*, defaults to 1):
|
| 91 |
+
The id of the "beginning-of-sequence" token.
|
| 92 |
+
eos_token_id (`int`, *optional*, defaults to 32000):
|
| 93 |
+
The id of the "end-of-sequence" token.
|
| 94 |
+
pad_token_id (`int`, *optional*, defaults to 32000):
|
| 95 |
+
The id of the padding token.
|
| 96 |
+
sliding_window (`int`, *optional*):
|
| 97 |
+
Sliding window attention window size. If `None`, no sliding window is applied.
|
| 98 |
+
|
| 99 |
+
Example:
|
| 100 |
+
|
| 101 |
+
```python
|
| 102 |
+
>>> from transformers import Phi3Model, Phi3Config
|
| 103 |
+
|
| 104 |
+
>>> # Initializing a Phi-3 style configuration
|
| 105 |
+
>>> configuration = Phi3Config.from_pretrained("microsoft/Phi-3-mini-4k-instruct")
|
| 106 |
+
|
| 107 |
+
>>> # Initializing a model from the configuration
|
| 108 |
+
>>> model = Phi3Model(configuration)
|
| 109 |
+
|
| 110 |
+
>>> # Accessing the model configuration
|
| 111 |
+
>>> configuration = model.config
|
| 112 |
+
```"""
|
| 113 |
+
|
| 114 |
+
model_type = "phi3"
|
| 115 |
+
keys_to_ignore_at_inference = ["past_key_values"]
|
| 116 |
+
|
| 117 |
+
def __init__(
|
| 118 |
+
self,
|
| 119 |
+
vocab_size=32064,
|
| 120 |
+
hidden_size=3072,
|
| 121 |
+
intermediate_size=8192,
|
| 122 |
+
num_hidden_layers=32,
|
| 123 |
+
num_attention_heads=32,
|
| 124 |
+
num_key_value_heads=None,
|
| 125 |
+
resid_pdrop=0.0,
|
| 126 |
+
embd_pdrop=0.0,
|
| 127 |
+
attention_dropout=0.0,
|
| 128 |
+
hidden_act="silu",
|
| 129 |
+
max_position_embeddings=4096,
|
| 130 |
+
original_max_position_embeddings=4096,
|
| 131 |
+
initializer_range=0.02,
|
| 132 |
+
rms_norm_eps=1e-5,
|
| 133 |
+
use_cache=True,
|
| 134 |
+
tie_word_embeddings=False,
|
| 135 |
+
rope_theta=10000.0,
|
| 136 |
+
rope_scaling=None,
|
| 137 |
+
bos_token_id=1,
|
| 138 |
+
eos_token_id=32000,
|
| 139 |
+
pad_token_id=32000,
|
| 140 |
+
sliding_window=None,
|
| 141 |
+
**kwargs,
|
| 142 |
+
):
|
| 143 |
+
self.vocab_size = vocab_size
|
| 144 |
+
self.hidden_size = hidden_size
|
| 145 |
+
self.intermediate_size = intermediate_size
|
| 146 |
+
self.num_hidden_layers = num_hidden_layers
|
| 147 |
+
self.num_attention_heads = num_attention_heads
|
| 148 |
+
|
| 149 |
+
if num_key_value_heads is None:
|
| 150 |
+
num_key_value_heads = num_attention_heads
|
| 151 |
+
|
| 152 |
+
self.num_key_value_heads = num_key_value_heads
|
| 153 |
+
self.resid_pdrop = resid_pdrop
|
| 154 |
+
self.embd_pdrop = embd_pdrop
|
| 155 |
+
self.attention_dropout = attention_dropout
|
| 156 |
+
self.hidden_act = hidden_act
|
| 157 |
+
self.max_position_embeddings = max_position_embeddings
|
| 158 |
+
self.original_max_position_embeddings = original_max_position_embeddings
|
| 159 |
+
self.initializer_range = initializer_range
|
| 160 |
+
self.rms_norm_eps = rms_norm_eps
|
| 161 |
+
self.use_cache = use_cache
|
| 162 |
+
self.rope_theta = rope_theta
|
| 163 |
+
self.rope_scaling = rope_scaling
|
| 164 |
+
self._rope_scaling_adjustment()
|
| 165 |
+
self._rope_scaling_validation()
|
| 166 |
+
self.sliding_window = sliding_window
|
| 167 |
+
|
| 168 |
+
super().__init__(
|
| 169 |
+
bos_token_id=bos_token_id,
|
| 170 |
+
eos_token_id=eos_token_id,
|
| 171 |
+
pad_token_id=pad_token_id,
|
| 172 |
+
tie_word_embeddings=tie_word_embeddings,
|
| 173 |
+
**kwargs,
|
| 174 |
+
)
|
| 175 |
+
|
| 176 |
+
def _rope_scaling_adjustment(self):
|
| 177 |
+
"""
|
| 178 |
+
Adjust the `type` of the `rope_scaling` configuration for backward compatibility.
|
| 179 |
+
"""
|
| 180 |
+
if self.rope_scaling is None:
|
| 181 |
+
return
|
| 182 |
+
|
| 183 |
+
rope_scaling_type = self.rope_scaling.get("type", None)
|
| 184 |
+
|
| 185 |
+
# For backward compatibility if previous version used "su" or "yarn"
|
| 186 |
+
if rope_scaling_type is not None and rope_scaling_type in ["su", "yarn"]:
|
| 187 |
+
self.rope_scaling["type"] = "longrope"
|
| 188 |
+
|
| 189 |
+
def _rope_scaling_validation(self):
|
| 190 |
+
"""
|
| 191 |
+
Validate the `rope_scaling` configuration.
|
| 192 |
+
"""
|
| 193 |
+
if self.rope_scaling is None:
|
| 194 |
+
return
|
| 195 |
+
|
| 196 |
+
if not isinstance(self.rope_scaling, dict) or len(self.rope_scaling) != 3:
|
| 197 |
+
raise ValueError(
|
| 198 |
+
"`rope_scaling` must be a dictionary with three fields, `type`, `short_factor` and `long_factor`, "
|
| 199 |
+
f"got {self.rope_scaling}"
|
| 200 |
+
)
|
| 201 |
+
rope_scaling_type = self.rope_scaling.get("type", None)
|
| 202 |
+
rope_scaling_short_factor = self.rope_scaling.get("short_factor", None)
|
| 203 |
+
rope_scaling_long_factor = self.rope_scaling.get("long_factor", None)
|
| 204 |
+
if rope_scaling_type is None or rope_scaling_type not in ["longrope"]:
|
| 205 |
+
raise ValueError(f"`rope_scaling`'s type field must be one of ['longrope'], got {rope_scaling_type}")
|
| 206 |
+
if not (
|
| 207 |
+
isinstance(rope_scaling_short_factor, list)
|
| 208 |
+
and all(isinstance(x, (int, float)) for x in rope_scaling_short_factor)
|
| 209 |
+
):
|
| 210 |
+
raise ValueError(
|
| 211 |
+
f"`rope_scaling`'s short_factor field must be a list of numbers, got {rope_scaling_short_factor}"
|
| 212 |
+
)
|
| 213 |
+
if not len(rope_scaling_short_factor) == self.hidden_size // self.num_attention_heads // 2:
|
| 214 |
+
raise ValueError(
|
| 215 |
+
f"`rope_scaling`'s short_factor field must have length {self.hidden_size // self.num_attention_heads // 2}, got {len(rope_scaling_short_factor)}"
|
| 216 |
+
)
|
| 217 |
+
if not (
|
| 218 |
+
isinstance(rope_scaling_long_factor, list)
|
| 219 |
+
and all(isinstance(x, (int, float)) for x in rope_scaling_long_factor)
|
| 220 |
+
):
|
| 221 |
+
raise ValueError(
|
| 222 |
+
f"`rope_scaling`'s long_factor field must be a list of numbers, got {rope_scaling_long_factor}"
|
| 223 |
+
)
|
| 224 |
+
if not len(rope_scaling_long_factor) == self.hidden_size // self.num_attention_heads // 2:
|
| 225 |
+
raise ValueError(
|
| 226 |
+
f"`rope_scaling`'s long_factor field must have length {self.hidden_size // self.num_attention_heads // 2}, got {len(rope_scaling_long_factor)}"
|
| 227 |
+
)
|
cpu_and_mobile/cpu-int4-awq-block-128/genai_config.json
ADDED
|
@@ -0,0 +1,53 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"model": {
|
| 3 |
+
"bos_token_id": 1,
|
| 4 |
+
"context_length": 131072,
|
| 5 |
+
"decoder": {
|
| 6 |
+
"session_options": {
|
| 7 |
+
"log_id": "onnxruntime-genai",
|
| 8 |
+
"provider_options": []
|
| 9 |
+
},
|
| 10 |
+
"filename": "phi3-mini-128k-instruct-cpu-int4-awq-block-128.onnx",
|
| 11 |
+
"head_size": 96,
|
| 12 |
+
"hidden_size": 3072,
|
| 13 |
+
"inputs": {
|
| 14 |
+
"input_ids": "input_ids",
|
| 15 |
+
"attention_mask": "attention_mask",
|
| 16 |
+
"past_key_names": "past_key_values.%d.key",
|
| 17 |
+
"past_value_names": "past_key_values.%d.value"
|
| 18 |
+
},
|
| 19 |
+
"outputs": {
|
| 20 |
+
"logits": "logits",
|
| 21 |
+
"present_key_names": "present.%d.key",
|
| 22 |
+
"present_value_names": "present.%d.value"
|
| 23 |
+
},
|
| 24 |
+
"num_attention_heads": 32,
|
| 25 |
+
"num_hidden_layers": 32,
|
| 26 |
+
"num_key_value_heads": 32
|
| 27 |
+
},
|
| 28 |
+
"eos_token_id": [
|
| 29 |
+
32000,
|
| 30 |
+
32001,
|
| 31 |
+
32007
|
| 32 |
+
],
|
| 33 |
+
"pad_token_id": 32000,
|
| 34 |
+
"type": "phi3",
|
| 35 |
+
"vocab_size": 32064
|
| 36 |
+
},
|
| 37 |
+
"search": {
|
| 38 |
+
"diversity_penalty": 0.0,
|
| 39 |
+
"do_sample": false,
|
| 40 |
+
"early_stopping": true,
|
| 41 |
+
"length_penalty": 1.0,
|
| 42 |
+
"max_length": 131072,
|
| 43 |
+
"min_length": 0,
|
| 44 |
+
"no_repeat_ngram_size": 0,
|
| 45 |
+
"num_beams": 1,
|
| 46 |
+
"num_return_sequences": 1,
|
| 47 |
+
"past_present_share_buffer": true,
|
| 48 |
+
"repetition_penalty": 1.0,
|
| 49 |
+
"temperature": 1.0,
|
| 50 |
+
"top_k": 1,
|
| 51 |
+
"top_p": 1.0
|
| 52 |
+
}
|
| 53 |
+
}
|
cpu_and_mobile/cpu-int4-awq-block-128/phi3-mini-128k-instruct-cpu-int4-awq-block-128.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:648cc852954cb71d92a611bcebaa109a71ebe4656b5b918fa65d04d70911b4f0
|
| 3 |
+
size 52167465
|
cpu_and_mobile/cpu-int4-awq-block-128/phi3-mini-128k-instruct-cpu-int4-awq-block-128.onnx.data
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b05189af87b804fedbc2f92a031b8c0274fe9558c16f5accf919fb8f3a6ccfbe
|
| 3 |
+
size 2728144896
|
cpu_and_mobile/cpu-int4-awq-block-128/special_tokens_map.json
ADDED
|
@@ -0,0 +1,30 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bos_token": {
|
| 3 |
+
"content": "<s>",
|
| 4 |
+
"lstrip": false,
|
| 5 |
+
"normalized": false,
|
| 6 |
+
"rstrip": false,
|
| 7 |
+
"single_word": false
|
| 8 |
+
},
|
| 9 |
+
"eos_token": {
|
| 10 |
+
"content": "<|endoftext|>",
|
| 11 |
+
"lstrip": false,
|
| 12 |
+
"normalized": false,
|
| 13 |
+
"rstrip": false,
|
| 14 |
+
"single_word": false
|
| 15 |
+
},
|
| 16 |
+
"pad_token": {
|
| 17 |
+
"content": "<|endoftext|>",
|
| 18 |
+
"lstrip": false,
|
| 19 |
+
"normalized": false,
|
| 20 |
+
"rstrip": false,
|
| 21 |
+
"single_word": false
|
| 22 |
+
},
|
| 23 |
+
"unk_token": {
|
| 24 |
+
"content": "<unk>",
|
| 25 |
+
"lstrip": false,
|
| 26 |
+
"normalized": false,
|
| 27 |
+
"rstrip": false,
|
| 28 |
+
"single_word": false
|
| 29 |
+
}
|
| 30 |
+
}
|
cpu_and_mobile/cpu-int4-awq-block-128/tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
cpu_and_mobile/cpu-int4-awq-block-128/tokenizer.model
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
|
| 3 |
+
size 499723
|
cpu_and_mobile/cpu-int4-awq-block-128/tokenizer_config.json
ADDED
|
@@ -0,0 +1,130 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
| 1 |
+
{
|
| 2 |
+
"add_bos_token": false,
|
| 3 |
+
"add_eos_token": false,
|
| 4 |
+
"added_tokens_decoder": {
|
| 5 |
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"0": {
|
| 6 |
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"content": "<unk>",
|
| 7 |
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"lstrip": false,
|
| 8 |
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|
| 9 |
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"rstrip": false,
|
| 10 |
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"single_word": false,
|
| 11 |
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"special": true
|
| 12 |
+
},
|
| 13 |
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"1": {
|
| 14 |
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"content": "<s>",
|
| 15 |
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"lstrip": false,
|
| 16 |
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|
| 17 |
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"rstrip": false,
|
| 18 |
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|
| 19 |
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"special": true
|
| 20 |
+
},
|
| 21 |
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"2": {
|
| 22 |
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"content": "</s>",
|
| 23 |
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"lstrip": false,
|
| 24 |
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"normalized": false,
|
| 25 |
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"rstrip": true,
|
| 26 |
+
"single_word": false,
|
| 27 |
+
"special": false
|
| 28 |
+
},
|
| 29 |
+
"32000": {
|
| 30 |
+
"content": "<|endoftext|>",
|
| 31 |
+
"lstrip": false,
|
| 32 |
+
"normalized": false,
|
| 33 |
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"rstrip": false,
|
| 34 |
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"single_word": false,
|
| 35 |
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"special": true
|
| 36 |
+
},
|
| 37 |
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"32001": {
|
| 38 |
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"content": "<|assistant|>",
|
| 39 |
+
"lstrip": false,
|
| 40 |
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"normalized": false,
|
| 41 |
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"rstrip": true,
|
| 42 |
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"single_word": false,
|
| 43 |
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"special": true
|
| 44 |
+
},
|
| 45 |
+
"32002": {
|
| 46 |
+
"content": "<|placeholder1|>",
|
| 47 |
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"lstrip": false,
|
| 48 |
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"normalized": false,
|
| 49 |
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"rstrip": true,
|
| 50 |
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"single_word": false,
|
| 51 |
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"special": true
|
| 52 |
+
},
|
| 53 |
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"32003": {
|
| 54 |
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"content": "<|placeholder2|>",
|
| 55 |
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"lstrip": false,
|
| 56 |
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"normalized": false,
|
| 57 |
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"rstrip": true,
|
| 58 |
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"single_word": false,
|
| 59 |
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"special": true
|
| 60 |
+
},
|
| 61 |
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"32004": {
|
| 62 |
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"content": "<|placeholder3|>",
|
| 63 |
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"lstrip": false,
|
| 64 |
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"normalized": false,
|
| 65 |
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"rstrip": true,
|
| 66 |
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"single_word": false,
|
| 67 |
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"special": true
|
| 68 |
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},
|
| 69 |
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"32005": {
|
| 70 |
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"content": "<|placeholder4|>",
|
| 71 |
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"lstrip": false,
|
| 72 |
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"normalized": false,
|
| 73 |
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"rstrip": true,
|
| 74 |
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"single_word": false,
|
| 75 |
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"special": true
|
| 76 |
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},
|
| 77 |
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"32006": {
|
| 78 |
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"content": "<|system|>",
|
| 79 |
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|
| 80 |
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"normalized": false,
|
| 81 |
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"rstrip": true,
|
| 82 |
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"single_word": false,
|
| 83 |
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"special": true
|
| 84 |
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},
|
| 85 |
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"32007": {
|
| 86 |
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"content": "<|end|>",
|
| 87 |
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"lstrip": false,
|
| 88 |
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"normalized": false,
|
| 89 |
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"rstrip": true,
|
| 90 |
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"single_word": false,
|
| 91 |
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"special": true
|
| 92 |
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},
|
| 93 |
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"32008": {
|
| 94 |
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"content": "<|placeholder5|>",
|
| 95 |
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"lstrip": false,
|
| 96 |
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"normalized": false,
|
| 97 |
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"rstrip": true,
|
| 98 |
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"single_word": false,
|
| 99 |
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"special": true
|
| 100 |
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},
|
| 101 |
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"32009": {
|
| 102 |
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"content": "<|placeholder6|>",
|
| 103 |
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"lstrip": false,
|
| 104 |
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"normalized": false,
|
| 105 |
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"rstrip": true,
|
| 106 |
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"single_word": false,
|
| 107 |
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"special": true
|
| 108 |
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},
|
| 109 |
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"32010": {
|
| 110 |
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"content": "<|user|>",
|
| 111 |
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"lstrip": false,
|
| 112 |
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"normalized": false,
|
| 113 |
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"rstrip": true,
|
| 114 |
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"single_word": false,
|
| 115 |
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"special": true
|
| 116 |
+
}
|
| 117 |
+
},
|
| 118 |
+
"bos_token": "<s>",
|
| 119 |
+
"chat_template": "{% for message in messages %}{% if message['role'] == 'system' %}{{'<|system|>\n' + message['content'] + '<|end|>\n'}}{% elif message['role'] == 'user' %}{{'<|user|>\n' + message['content'] + '<|end|>\n'}}{% elif message['role'] == 'assistant' %}{{'<|assistant|>\n' + message['content'] + '<|end|>\n'}}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|assistant|>\n' }}{% else %}{{ eos_token }}{% endif %}",
|
| 120 |
+
"clean_up_tokenization_spaces": false,
|
| 121 |
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"eos_token": "<|endoftext|>",
|
| 122 |
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"legacy": false,
|
| 123 |
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"model_max_length": 131072,
|
| 124 |
+
"pad_token": "<|endoftext|>",
|
| 125 |
+
"padding_side": "left",
|
| 126 |
+
"sp_model_kwargs": {},
|
| 127 |
+
"tokenizer_class": "LlamaTokenizer",
|
| 128 |
+
"unk_token": "<unk>",
|
| 129 |
+
"use_default_system_prompt": false
|
| 130 |
+
}
|
cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/added_tokens.json
CHANGED
|
@@ -1,13 +1,13 @@
|
|
| 1 |
-
{
|
| 2 |
-
"<|endoftext|>": 32000,
|
| 3 |
-
"<|assistant|>": 32001,
|
| 4 |
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"<|placeholder1|>": 32002,
|
| 5 |
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"<|placeholder2|>": 32003,
|
| 6 |
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"<|placeholder3|>": 32004,
|
| 7 |
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"<|placeholder4|>": 32005,
|
| 8 |
-
"<|system|>": 32006,
|
| 9 |
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"<|end|>": 32007,
|
| 10 |
-
"<|placeholder5|>": 32008,
|
| 11 |
-
"<|placeholder6|>": 32009,
|
| 12 |
-
"<|user|>": 32010
|
| 13 |
-
}
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"<|endoftext|>": 32000,
|
| 3 |
+
"<|assistant|>": 32001,
|
| 4 |
+
"<|placeholder1|>": 32002,
|
| 5 |
+
"<|placeholder2|>": 32003,
|
| 6 |
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"<|placeholder3|>": 32004,
|
| 7 |
+
"<|placeholder4|>": 32005,
|
| 8 |
+
"<|system|>": 32006,
|
| 9 |
+
"<|end|>": 32007,
|
| 10 |
+
"<|placeholder5|>": 32008,
|
| 11 |
+
"<|placeholder6|>": 32009,
|
| 12 |
+
"<|user|>": 32010
|
| 13 |
+
}
|
cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/config.json
CHANGED
|
@@ -1,137 +1,138 @@
|
|
| 1 |
-
{
|
| 2 |
-
"_name_or_path": "
|
| 3 |
-
"architectures": [
|
| 4 |
-
"Phi3ForCausalLM"
|
| 5 |
-
],
|
| 6 |
-
"attention_dropout": 0.0,
|
| 7 |
-
"auto_map": {
|
| 8 |
-
"AutoConfig": "configuration_phi3.Phi3Config",
|
| 9 |
-
"AutoModelForCausalLM": "modeling_phi3.Phi3ForCausalLM"
|
| 10 |
-
},
|
| 11 |
-
"bos_token_id": 1,
|
| 12 |
-
"embd_pdrop": 0.0,
|
| 13 |
-
"eos_token_id": 32000,
|
| 14 |
-
"hidden_act": "silu",
|
| 15 |
-
"hidden_size": 3072,
|
| 16 |
-
"initializer_range": 0.02,
|
| 17 |
-
"intermediate_size": 8192,
|
| 18 |
-
"max_position_embeddings": 131072,
|
| 19 |
-
"model_type": "phi3",
|
| 20 |
-
"num_attention_heads": 32,
|
| 21 |
-
"num_hidden_layers": 32,
|
| 22 |
-
"num_key_value_heads": 32,
|
| 23 |
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|
| 24 |
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|
| 25 |
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|
| 26 |
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"rms_norm_eps": 1e-05,
|
| 27 |
-
"rope_scaling": {
|
| 28 |
-
"long_factor": [
|
| 29 |
-
1.
|
| 30 |
-
1.
|
| 31 |
-
1.
|
| 32 |
-
1.
|
| 33 |
-
1.
|
| 34 |
-
1.
|
| 35 |
-
|
| 36 |
-
|
| 37 |
-
|
| 38 |
-
|
| 39 |
-
|
| 40 |
-
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| 41 |
-
|
| 42 |
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|
| 43 |
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|
| 44 |
-
|
| 45 |
-
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| 46 |
-
|
| 47 |
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|
| 48 |
-
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| 49 |
-
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| 50 |
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| 51 |
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| 52 |
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| 53 |
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| 54 |
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| 55 |
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| 56 |
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| 57 |
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|
| 58 |
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|
| 59 |
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|
| 60 |
-
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| 61 |
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| 62 |
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|
| 63 |
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|
| 64 |
-
|
| 65 |
-
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| 66 |
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| 67 |
-
63.
|
| 68 |
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| 69 |
-
|
| 70 |
-
|
| 71 |
-
|
| 72 |
-
64.
|
| 73 |
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64.
|
| 74 |
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64.
|
| 75 |
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64.
|
| 76 |
-
64.
|
| 77 |
-
],
|
| 78 |
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"short_factor": [
|
| 79 |
-
1.
|
| 80 |
-
1.
|
| 81 |
-
1.
|
| 82 |
-
1.
|
| 83 |
-
1.
|
| 84 |
-
1.
|
| 85 |
-
1.
|
| 86 |
-
1.
|
| 87 |
-
|
| 88 |
-
|
| 89 |
-
|
| 90 |
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2.000000000000001,
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| 110 |
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| 112 |
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| 113 |
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| 118 |
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| 119 |
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2.
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| 123 |
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2.7499999999999982,
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| 129 |
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|
| 84 |
+
1.3500000000000003,
|
| 85 |
+
1.4000000000000004,
|
| 86 |
+
1.5500000000000005,
|
| 87 |
+
2.000000000000001,
|
| 88 |
+
2.000000000000001,
|
| 89 |
+
2.000000000000001,
|
| 90 |
+
2.000000000000001,
|
| 91 |
+
2.000000000000001,
|
| 92 |
+
2.000000000000001,
|
| 93 |
+
2.000000000000001,
|
| 94 |
+
2.000000000000001,
|
| 95 |
+
2.000000000000001,
|
| 96 |
+
2.000000000000001,
|
| 97 |
+
2.000000000000001,
|
| 98 |
+
2.000000000000001,
|
| 99 |
+
2.000000000000001,
|
| 100 |
+
2.000000000000001,
|
| 101 |
+
2.000000000000001,
|
| 102 |
+
2.000000000000001,
|
| 103 |
+
2.000000000000001,
|
| 104 |
+
2.0500000000000007,
|
| 105 |
+
2.0500000000000007,
|
| 106 |
+
2.0500000000000007,
|
| 107 |
+
2.0500000000000007,
|
| 108 |
+
2.0500000000000007,
|
| 109 |
+
2.0500000000000007,
|
| 110 |
+
2.1000000000000005,
|
| 111 |
+
2.1000000000000005,
|
| 112 |
+
2.1500000000000004,
|
| 113 |
+
2.25,
|
| 114 |
+
2.25,
|
| 115 |
+
2.25,
|
| 116 |
+
2.25,
|
| 117 |
+
2.25,
|
| 118 |
+
2.3999999999999995,
|
| 119 |
+
2.4499999999999993,
|
| 120 |
+
2.499999999999999,
|
| 121 |
+
2.6999999999999984,
|
| 122 |
+
2.6999999999999984,
|
| 123 |
+
2.7499999999999982,
|
| 124 |
+
2.799999999999998,
|
| 125 |
+
2.8999999999999977,
|
| 126 |
+
3.049999999999997
|
| 127 |
+
],
|
| 128 |
+
"type": "longrope"
|
| 129 |
+
},
|
| 130 |
+
"rope_theta": 10000.0,
|
| 131 |
+
"sliding_window": 262144,
|
| 132 |
+
"tie_word_embeddings": false,
|
| 133 |
+
"torch_dtype": "bfloat16",
|
| 134 |
+
"transformers_version": "4.40.2",
|
| 135 |
+
"use_cache": true,
|
| 136 |
+
"attention_bias": false,
|
| 137 |
+
"vocab_size": 32064
|
| 138 |
+
}
|
cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/configuration_phi3.py
CHANGED
|
@@ -1,213 +1,227 @@
|
|
| 1 |
-
# coding=utf-8
|
| 2 |
-
# Copyright 2024 Microsoft and the HuggingFace Inc. team. All rights reserved.
|
| 3 |
-
#
|
| 4 |
-
# Licensed under the Apache License, Version 2.0 (the "License");
|
| 5 |
-
# you may not use this file except in compliance with the License.
|
| 6 |
-
# You may obtain a copy of the License at
|
| 7 |
-
#
|
| 8 |
-
# http://www.apache.org/licenses/LICENSE-2.0
|
| 9 |
-
#
|
| 10 |
-
# Unless required by applicable law or agreed to in writing, software
|
| 11 |
-
# distributed under the License is distributed on an "AS IS" BASIS,
|
| 12 |
-
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
| 13 |
-
# See the License for the specific language governing permissions and
|
| 14 |
-
# limitations under the License.
|
| 15 |
-
|
| 16 |
-
""" Phi-3 model configuration"""
|
| 17 |
-
|
| 18 |
-
|
| 19 |
-
from transformers.configuration_utils import PretrainedConfig
|
| 20 |
-
from transformers.utils import logging
|
| 21 |
-
|
| 22 |
-
|
| 23 |
-
logger = logging.get_logger(__name__)
|
| 24 |
-
|
| 25 |
-
PHI3_PRETRAINED_CONFIG_ARCHIVE_MAP = {
|
| 26 |
-
"microsoft/Phi-3-mini-4k-instruct": "https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/resolve/main/config.json",
|
| 27 |
-
"microsoft/Phi-3-mini-128k-instruct": "https://huggingface.co/microsoft/Phi-3-mini-128k-instruct/resolve/main/config.json",
|
| 28 |
-
}
|
| 29 |
-
|
| 30 |
-
|
| 31 |
-
class Phi3Config(PretrainedConfig):
|
| 32 |
-
r"""
|
| 33 |
-
This is the configuration class to store the configuration of a [`Phi3Model`]. It is used to instantiate a Phi-3
|
| 34 |
-
model according to the specified arguments, defining the model architecture. Instantiating a configuration with the
|
| 35 |
-
defaults will yield a similar configuration to that of the
|
| 36 |
-
[microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct).
|
| 37 |
-
|
| 38 |
-
Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
|
| 39 |
-
documentation from [`PretrainedConfig`] for more information.
|
| 40 |
-
|
| 41 |
-
Args:
|
| 42 |
-
vocab_size (`int`, *optional*, defaults to 32064):
|
| 43 |
-
Vocabulary size of the Phi-3 model. Defines the number of different tokens that can be represented by the
|
| 44 |
-
`inputs_ids` passed when calling [`Phi3Model`].
|
| 45 |
-
hidden_size (`int`, *optional*, defaults to 3072):
|
| 46 |
-
Dimension of the hidden representations.
|
| 47 |
-
intermediate_size (`int`, *optional*, defaults to 8192):
|
| 48 |
-
Dimension of the MLP representations.
|
| 49 |
-
num_hidden_layers (`int`, *optional*, defaults to 32):
|
| 50 |
-
Number of hidden layers in the Transformer decoder.
|
| 51 |
-
num_attention_heads (`int`, *optional*, defaults to 32):
|
| 52 |
-
Number of attention heads for each attention layer in the Transformer decoder.
|
| 53 |
-
num_key_value_heads (`int`, *optional*):
|
| 54 |
-
This is the number of key_value heads that should be used to implement Grouped Query Attention. If
|
| 55 |
-
`num_key_value_heads=num_attention_heads`, the model will use Multi Head Attention (MHA), if
|
| 56 |
-
`num_key_value_heads=1 the model will use Multi Query Attention (MQA) otherwise GQA is used. When
|
| 57 |
-
converting a multi-head checkpoint to a GQA checkpoint, each group key and value head should be constructed
|
| 58 |
-
by meanpooling all the original heads within that group. For more details checkout [this
|
| 59 |
-
paper](https://arxiv.org/pdf/2305.13245.pdf). If it is not specified, will default to
|
| 60 |
-
`num_attention_heads`.
|
| 61 |
-
resid_pdrop (`float`, *optional*, defaults to 0.0):
|
| 62 |
-
Dropout probability for mlp outputs.
|
| 63 |
-
embd_pdrop (`int`, *optional*, defaults to 0.0):
|
| 64 |
-
The dropout ratio for the embeddings.
|
| 65 |
-
attention_dropout (`float`, *optional*, defaults to 0.0):
|
| 66 |
-
The dropout ratio after computing the attention scores.
|
| 67 |
-
hidden_act (`str` or `function`, *optional*, defaults to `"silu"`):
|
| 68 |
-
The non-linear activation function (function or string) in the decoder.
|
| 69 |
-
max_position_embeddings (`int`, *optional*, defaults to 4096):
|
| 70 |
-
The maximum sequence length that this model might ever be used with.
|
| 71 |
-
original_max_position_embeddings (`int`, *optional*, defaults to 4096):
|
| 72 |
-
The maximum sequence length that this model was trained with. This is used to determine the size of the
|
| 73 |
-
original RoPE embeddings when using long scaling.
|
| 74 |
-
initializer_range (`float`, *optional*, defaults to 0.02):
|
| 75 |
-
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
|
| 76 |
-
rms_norm_eps (`float`, *optional*, defaults to 1e-05):
|
| 77 |
-
The epsilon value used for the RMSNorm.
|
| 78 |
-
use_cache (`bool`, *optional*, defaults to `True`):
|
| 79 |
-
Whether or not the model should return the last key/values attentions (not used by all models). Only
|
| 80 |
-
relevant if `config.is_decoder=True`. Whether to tie weight embeddings or not.
|
| 81 |
-
tie_word_embeddings (`bool`, *optional*, defaults to `False`):
|
| 82 |
-
Whether to tie weight embeddings
|
| 83 |
-
rope_theta (`float`, *optional*, defaults to 10000.0):
|
| 84 |
-
The base period of the RoPE embeddings.
|
| 85 |
-
rope_scaling (`dict`, *optional*):
|
| 86 |
-
The scaling strategy for the RoPE embeddings. If `None`, no scaling is applied. If a dictionary, it must
|
| 87 |
-
contain the following keys: `type`, `short_factor` and `long_factor`. The `type` must be
|
| 88 |
-
the `short_factor` and `long_factor` must be lists of numbers with the same length as the hidden size
|
| 89 |
-
divided by the number of attention heads divided by 2.
|
| 90 |
-
bos_token_id (`int`, *optional*, defaults to 1):
|
| 91 |
-
The id of the "beginning-of-sequence" token.
|
| 92 |
-
eos_token_id (`int`, *optional*, defaults to 32000):
|
| 93 |
-
The id of the "end-of-sequence" token.
|
| 94 |
-
pad_token_id (`int`, *optional*, defaults to 32000):
|
| 95 |
-
The id of the padding token.
|
| 96 |
-
sliding_window (`int`, *optional*):
|
| 97 |
-
Sliding window attention window size. If `None`, no sliding window is applied.
|
| 98 |
-
|
| 99 |
-
Example:
|
| 100 |
-
|
| 101 |
-
```python
|
| 102 |
-
>>> from transformers import Phi3Model, Phi3Config
|
| 103 |
-
|
| 104 |
-
>>> # Initializing a Phi-3 style configuration
|
| 105 |
-
>>> configuration = Phi3Config.from_pretrained("microsoft/Phi-3-mini-4k-instruct")
|
| 106 |
-
|
| 107 |
-
>>> # Initializing a model from the configuration
|
| 108 |
-
>>> model = Phi3Model(configuration)
|
| 109 |
-
|
| 110 |
-
>>> # Accessing the model configuration
|
| 111 |
-
>>> configuration = model.config
|
| 112 |
-
```"""
|
| 113 |
-
|
| 114 |
-
model_type = "phi3"
|
| 115 |
-
keys_to_ignore_at_inference = ["past_key_values"]
|
| 116 |
-
|
| 117 |
-
def __init__(
|
| 118 |
-
self,
|
| 119 |
-
vocab_size=32064,
|
| 120 |
-
hidden_size=3072,
|
| 121 |
-
intermediate_size=8192,
|
| 122 |
-
num_hidden_layers=32,
|
| 123 |
-
num_attention_heads=32,
|
| 124 |
-
num_key_value_heads=None,
|
| 125 |
-
resid_pdrop=0.0,
|
| 126 |
-
embd_pdrop=0.0,
|
| 127 |
-
attention_dropout=0.0,
|
| 128 |
-
hidden_act="silu",
|
| 129 |
-
max_position_embeddings=4096,
|
| 130 |
-
original_max_position_embeddings=4096,
|
| 131 |
-
initializer_range=0.02,
|
| 132 |
-
rms_norm_eps=1e-5,
|
| 133 |
-
use_cache=True,
|
| 134 |
-
tie_word_embeddings=False,
|
| 135 |
-
rope_theta=10000.0,
|
| 136 |
-
rope_scaling=None,
|
| 137 |
-
bos_token_id=1,
|
| 138 |
-
eos_token_id=32000,
|
| 139 |
-
pad_token_id=32000,
|
| 140 |
-
sliding_window=None,
|
| 141 |
-
**kwargs,
|
| 142 |
-
):
|
| 143 |
-
self.vocab_size = vocab_size
|
| 144 |
-
self.hidden_size = hidden_size
|
| 145 |
-
self.intermediate_size = intermediate_size
|
| 146 |
-
self.num_hidden_layers = num_hidden_layers
|
| 147 |
-
self.num_attention_heads = num_attention_heads
|
| 148 |
-
|
| 149 |
-
if num_key_value_heads is None:
|
| 150 |
-
num_key_value_heads = num_attention_heads
|
| 151 |
-
|
| 152 |
-
self.num_key_value_heads = num_key_value_heads
|
| 153 |
-
self.resid_pdrop = resid_pdrop
|
| 154 |
-
self.embd_pdrop = embd_pdrop
|
| 155 |
-
self.attention_dropout = attention_dropout
|
| 156 |
-
self.hidden_act = hidden_act
|
| 157 |
-
self.max_position_embeddings = max_position_embeddings
|
| 158 |
-
self.original_max_position_embeddings = original_max_position_embeddings
|
| 159 |
-
self.initializer_range = initializer_range
|
| 160 |
-
self.rms_norm_eps = rms_norm_eps
|
| 161 |
-
self.use_cache = use_cache
|
| 162 |
-
self.rope_theta = rope_theta
|
| 163 |
-
self.rope_scaling = rope_scaling
|
| 164 |
-
self.
|
| 165 |
-
self.
|
| 166 |
-
|
| 167 |
-
|
| 168 |
-
|
| 169 |
-
|
| 170 |
-
|
| 171 |
-
|
| 172 |
-
|
| 173 |
-
|
| 174 |
-
|
| 175 |
-
|
| 176 |
-
|
| 177 |
-
|
| 178 |
-
|
| 179 |
-
|
| 180 |
-
|
| 181 |
-
|
| 182 |
-
|
| 183 |
-
|
| 184 |
-
|
| 185 |
-
|
| 186 |
-
|
| 187 |
-
|
| 188 |
-
|
| 189 |
-
|
| 190 |
-
|
| 191 |
-
|
| 192 |
-
|
| 193 |
-
|
| 194 |
-
|
| 195 |
-
|
| 196 |
-
|
| 197 |
-
|
| 198 |
-
|
| 199 |
-
|
| 200 |
-
|
| 201 |
-
|
| 202 |
-
|
| 203 |
-
|
| 204 |
-
|
| 205 |
-
|
| 206 |
-
|
| 207 |
-
|
| 208 |
-
|
| 209 |
-
|
| 210 |
-
|
| 211 |
-
|
| 212 |
-
|
| 213 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# coding=utf-8
|
| 2 |
+
# Copyright 2024 Microsoft and the HuggingFace Inc. team. All rights reserved.
|
| 3 |
+
#
|
| 4 |
+
# Licensed under the Apache License, Version 2.0 (the "License");
|
| 5 |
+
# you may not use this file except in compliance with the License.
|
| 6 |
+
# You may obtain a copy of the License at
|
| 7 |
+
#
|
| 8 |
+
# http://www.apache.org/licenses/LICENSE-2.0
|
| 9 |
+
#
|
| 10 |
+
# Unless required by applicable law or agreed to in writing, software
|
| 11 |
+
# distributed under the License is distributed on an "AS IS" BASIS,
|
| 12 |
+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
| 13 |
+
# See the License for the specific language governing permissions and
|
| 14 |
+
# limitations under the License.
|
| 15 |
+
|
| 16 |
+
""" Phi-3 model configuration"""
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
from transformers.configuration_utils import PretrainedConfig
|
| 20 |
+
from transformers.utils import logging
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
logger = logging.get_logger(__name__)
|
| 24 |
+
|
| 25 |
+
PHI3_PRETRAINED_CONFIG_ARCHIVE_MAP = {
|
| 26 |
+
"microsoft/Phi-3-mini-4k-instruct": "https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/resolve/main/config.json",
|
| 27 |
+
"microsoft/Phi-3-mini-128k-instruct": "https://huggingface.co/microsoft/Phi-3-mini-128k-instruct/resolve/main/config.json",
|
| 28 |
+
}
|
| 29 |
+
|
| 30 |
+
|
| 31 |
+
class Phi3Config(PretrainedConfig):
|
| 32 |
+
r"""
|
| 33 |
+
This is the configuration class to store the configuration of a [`Phi3Model`]. It is used to instantiate a Phi-3
|
| 34 |
+
model according to the specified arguments, defining the model architecture. Instantiating a configuration with the
|
| 35 |
+
defaults will yield a similar configuration to that of the
|
| 36 |
+
[microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct).
|
| 37 |
+
|
| 38 |
+
Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
|
| 39 |
+
documentation from [`PretrainedConfig`] for more information.
|
| 40 |
+
|
| 41 |
+
Args:
|
| 42 |
+
vocab_size (`int`, *optional*, defaults to 32064):
|
| 43 |
+
Vocabulary size of the Phi-3 model. Defines the number of different tokens that can be represented by the
|
| 44 |
+
`inputs_ids` passed when calling [`Phi3Model`].
|
| 45 |
+
hidden_size (`int`, *optional*, defaults to 3072):
|
| 46 |
+
Dimension of the hidden representations.
|
| 47 |
+
intermediate_size (`int`, *optional*, defaults to 8192):
|
| 48 |
+
Dimension of the MLP representations.
|
| 49 |
+
num_hidden_layers (`int`, *optional*, defaults to 32):
|
| 50 |
+
Number of hidden layers in the Transformer decoder.
|
| 51 |
+
num_attention_heads (`int`, *optional*, defaults to 32):
|
| 52 |
+
Number of attention heads for each attention layer in the Transformer decoder.
|
| 53 |
+
num_key_value_heads (`int`, *optional*):
|
| 54 |
+
This is the number of key_value heads that should be used to implement Grouped Query Attention. If
|
| 55 |
+
`num_key_value_heads=num_attention_heads`, the model will use Multi Head Attention (MHA), if
|
| 56 |
+
`num_key_value_heads=1 the model will use Multi Query Attention (MQA) otherwise GQA is used. When
|
| 57 |
+
converting a multi-head checkpoint to a GQA checkpoint, each group key and value head should be constructed
|
| 58 |
+
by meanpooling all the original heads within that group. For more details checkout [this
|
| 59 |
+
paper](https://arxiv.org/pdf/2305.13245.pdf). If it is not specified, will default to
|
| 60 |
+
`num_attention_heads`.
|
| 61 |
+
resid_pdrop (`float`, *optional*, defaults to 0.0):
|
| 62 |
+
Dropout probability for mlp outputs.
|
| 63 |
+
embd_pdrop (`int`, *optional*, defaults to 0.0):
|
| 64 |
+
The dropout ratio for the embeddings.
|
| 65 |
+
attention_dropout (`float`, *optional*, defaults to 0.0):
|
| 66 |
+
The dropout ratio after computing the attention scores.
|
| 67 |
+
hidden_act (`str` or `function`, *optional*, defaults to `"silu"`):
|
| 68 |
+
The non-linear activation function (function or string) in the decoder.
|
| 69 |
+
max_position_embeddings (`int`, *optional*, defaults to 4096):
|
| 70 |
+
The maximum sequence length that this model might ever be used with.
|
| 71 |
+
original_max_position_embeddings (`int`, *optional*, defaults to 4096):
|
| 72 |
+
The maximum sequence length that this model was trained with. This is used to determine the size of the
|
| 73 |
+
original RoPE embeddings when using long scaling.
|
| 74 |
+
initializer_range (`float`, *optional*, defaults to 0.02):
|
| 75 |
+
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
|
| 76 |
+
rms_norm_eps (`float`, *optional*, defaults to 1e-05):
|
| 77 |
+
The epsilon value used for the RMSNorm.
|
| 78 |
+
use_cache (`bool`, *optional*, defaults to `True`):
|
| 79 |
+
Whether or not the model should return the last key/values attentions (not used by all models). Only
|
| 80 |
+
relevant if `config.is_decoder=True`. Whether to tie weight embeddings or not.
|
| 81 |
+
tie_word_embeddings (`bool`, *optional*, defaults to `False`):
|
| 82 |
+
Whether to tie weight embeddings
|
| 83 |
+
rope_theta (`float`, *optional*, defaults to 10000.0):
|
| 84 |
+
The base period of the RoPE embeddings.
|
| 85 |
+
rope_scaling (`dict`, *optional*):
|
| 86 |
+
The scaling strategy for the RoPE embeddings. If `None`, no scaling is applied. If a dictionary, it must
|
| 87 |
+
contain the following keys: `type`, `short_factor` and `long_factor`. The `type` must be `longrope` and
|
| 88 |
+
the `short_factor` and `long_factor` must be lists of numbers with the same length as the hidden size
|
| 89 |
+
divided by the number of attention heads divided by 2.
|
| 90 |
+
bos_token_id (`int`, *optional*, defaults to 1):
|
| 91 |
+
The id of the "beginning-of-sequence" token.
|
| 92 |
+
eos_token_id (`int`, *optional*, defaults to 32000):
|
| 93 |
+
The id of the "end-of-sequence" token.
|
| 94 |
+
pad_token_id (`int`, *optional*, defaults to 32000):
|
| 95 |
+
The id of the padding token.
|
| 96 |
+
sliding_window (`int`, *optional*):
|
| 97 |
+
Sliding window attention window size. If `None`, no sliding window is applied.
|
| 98 |
+
|
| 99 |
+
Example:
|
| 100 |
+
|
| 101 |
+
```python
|
| 102 |
+
>>> from transformers import Phi3Model, Phi3Config
|
| 103 |
+
|
| 104 |
+
>>> # Initializing a Phi-3 style configuration
|
| 105 |
+
>>> configuration = Phi3Config.from_pretrained("microsoft/Phi-3-mini-4k-instruct")
|
| 106 |
+
|
| 107 |
+
>>> # Initializing a model from the configuration
|
| 108 |
+
>>> model = Phi3Model(configuration)
|
| 109 |
+
|
| 110 |
+
>>> # Accessing the model configuration
|
| 111 |
+
>>> configuration = model.config
|
| 112 |
+
```"""
|
| 113 |
+
|
| 114 |
+
model_type = "phi3"
|
| 115 |
+
keys_to_ignore_at_inference = ["past_key_values"]
|
| 116 |
+
|
| 117 |
+
def __init__(
|
| 118 |
+
self,
|
| 119 |
+
vocab_size=32064,
|
| 120 |
+
hidden_size=3072,
|
| 121 |
+
intermediate_size=8192,
|
| 122 |
+
num_hidden_layers=32,
|
| 123 |
+
num_attention_heads=32,
|
| 124 |
+
num_key_value_heads=None,
|
| 125 |
+
resid_pdrop=0.0,
|
| 126 |
+
embd_pdrop=0.0,
|
| 127 |
+
attention_dropout=0.0,
|
| 128 |
+
hidden_act="silu",
|
| 129 |
+
max_position_embeddings=4096,
|
| 130 |
+
original_max_position_embeddings=4096,
|
| 131 |
+
initializer_range=0.02,
|
| 132 |
+
rms_norm_eps=1e-5,
|
| 133 |
+
use_cache=True,
|
| 134 |
+
tie_word_embeddings=False,
|
| 135 |
+
rope_theta=10000.0,
|
| 136 |
+
rope_scaling=None,
|
| 137 |
+
bos_token_id=1,
|
| 138 |
+
eos_token_id=32000,
|
| 139 |
+
pad_token_id=32000,
|
| 140 |
+
sliding_window=None,
|
| 141 |
+
**kwargs,
|
| 142 |
+
):
|
| 143 |
+
self.vocab_size = vocab_size
|
| 144 |
+
self.hidden_size = hidden_size
|
| 145 |
+
self.intermediate_size = intermediate_size
|
| 146 |
+
self.num_hidden_layers = num_hidden_layers
|
| 147 |
+
self.num_attention_heads = num_attention_heads
|
| 148 |
+
|
| 149 |
+
if num_key_value_heads is None:
|
| 150 |
+
num_key_value_heads = num_attention_heads
|
| 151 |
+
|
| 152 |
+
self.num_key_value_heads = num_key_value_heads
|
| 153 |
+
self.resid_pdrop = resid_pdrop
|
| 154 |
+
self.embd_pdrop = embd_pdrop
|
| 155 |
+
self.attention_dropout = attention_dropout
|
| 156 |
+
self.hidden_act = hidden_act
|
| 157 |
+
self.max_position_embeddings = max_position_embeddings
|
| 158 |
+
self.original_max_position_embeddings = original_max_position_embeddings
|
| 159 |
+
self.initializer_range = initializer_range
|
| 160 |
+
self.rms_norm_eps = rms_norm_eps
|
| 161 |
+
self.use_cache = use_cache
|
| 162 |
+
self.rope_theta = rope_theta
|
| 163 |
+
self.rope_scaling = rope_scaling
|
| 164 |
+
self._rope_scaling_adjustment()
|
| 165 |
+
self._rope_scaling_validation()
|
| 166 |
+
self.sliding_window = sliding_window
|
| 167 |
+
|
| 168 |
+
super().__init__(
|
| 169 |
+
bos_token_id=bos_token_id,
|
| 170 |
+
eos_token_id=eos_token_id,
|
| 171 |
+
pad_token_id=pad_token_id,
|
| 172 |
+
tie_word_embeddings=tie_word_embeddings,
|
| 173 |
+
**kwargs,
|
| 174 |
+
)
|
| 175 |
+
|
| 176 |
+
def _rope_scaling_adjustment(self):
|
| 177 |
+
"""
|
| 178 |
+
Adjust the `type` of the `rope_scaling` configuration for backward compatibility.
|
| 179 |
+
"""
|
| 180 |
+
if self.rope_scaling is None:
|
| 181 |
+
return
|
| 182 |
+
|
| 183 |
+
rope_scaling_type = self.rope_scaling.get("type", None)
|
| 184 |
+
|
| 185 |
+
# For backward compatibility if previous version used "su" or "yarn"
|
| 186 |
+
if rope_scaling_type is not None and rope_scaling_type in ["su", "yarn"]:
|
| 187 |
+
self.rope_scaling["type"] = "longrope"
|
| 188 |
+
|
| 189 |
+
def _rope_scaling_validation(self):
|
| 190 |
+
"""
|
| 191 |
+
Validate the `rope_scaling` configuration.
|
| 192 |
+
"""
|
| 193 |
+
if self.rope_scaling is None:
|
| 194 |
+
return
|
| 195 |
+
|
| 196 |
+
if not isinstance(self.rope_scaling, dict) or len(self.rope_scaling) != 3:
|
| 197 |
+
raise ValueError(
|
| 198 |
+
"`rope_scaling` must be a dictionary with three fields, `type`, `short_factor` and `long_factor`, "
|
| 199 |
+
f"got {self.rope_scaling}"
|
| 200 |
+
)
|
| 201 |
+
rope_scaling_type = self.rope_scaling.get("type", None)
|
| 202 |
+
rope_scaling_short_factor = self.rope_scaling.get("short_factor", None)
|
| 203 |
+
rope_scaling_long_factor = self.rope_scaling.get("long_factor", None)
|
| 204 |
+
if rope_scaling_type is None or rope_scaling_type not in ["longrope"]:
|
| 205 |
+
raise ValueError(f"`rope_scaling`'s type field must be one of ['longrope'], got {rope_scaling_type}")
|
| 206 |
+
if not (
|
| 207 |
+
isinstance(rope_scaling_short_factor, list)
|
| 208 |
+
and all(isinstance(x, (int, float)) for x in rope_scaling_short_factor)
|
| 209 |
+
):
|
| 210 |
+
raise ValueError(
|
| 211 |
+
f"`rope_scaling`'s short_factor field must be a list of numbers, got {rope_scaling_short_factor}"
|
| 212 |
+
)
|
| 213 |
+
if not len(rope_scaling_short_factor) == self.hidden_size // self.num_attention_heads // 2:
|
| 214 |
+
raise ValueError(
|
| 215 |
+
f"`rope_scaling`'s short_factor field must have length {self.hidden_size // self.num_attention_heads // 2}, got {len(rope_scaling_short_factor)}"
|
| 216 |
+
)
|
| 217 |
+
if not (
|
| 218 |
+
isinstance(rope_scaling_long_factor, list)
|
| 219 |
+
and all(isinstance(x, (int, float)) for x in rope_scaling_long_factor)
|
| 220 |
+
):
|
| 221 |
+
raise ValueError(
|
| 222 |
+
f"`rope_scaling`'s long_factor field must be a list of numbers, got {rope_scaling_long_factor}"
|
| 223 |
+
)
|
| 224 |
+
if not len(rope_scaling_long_factor) == self.hidden_size // self.num_attention_heads // 2:
|
| 225 |
+
raise ValueError(
|
| 226 |
+
f"`rope_scaling`'s long_factor field must have length {self.hidden_size // self.num_attention_heads // 2}, got {len(rope_scaling_long_factor)}"
|
| 227 |
+
)
|
cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/phi3-mini-128k-instruct-cpu-int4-rtn-block-32-acc-level-4.onnx
CHANGED
|
@@ -1,3 +1,3 @@
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|
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|
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size 52137679
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cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/phi3-mini-128k-instruct-cpu-int4-rtn-block-32-acc-level-4.onnx.data
CHANGED
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@@ -1,3 +1,3 @@
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|
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size 2721288192
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|
| 3 |
size 2721288192
|
cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/special_tokens_map.json
CHANGED
|
@@ -1,30 +1,30 @@
|
|
| 1 |
-
{
|
| 2 |
-
"bos_token": {
|
| 3 |
-
"content": "<s>",
|
| 4 |
-
"lstrip": false,
|
| 5 |
-
"normalized": false,
|
| 6 |
-
"rstrip": false,
|
| 7 |
-
"single_word": false
|
| 8 |
-
},
|
| 9 |
-
"eos_token": {
|
| 10 |
-
"content": "<|endoftext|>",
|
| 11 |
-
"lstrip": false,
|
| 12 |
-
"normalized": false,
|
| 13 |
-
"rstrip": false,
|
| 14 |
-
"single_word": false
|
| 15 |
-
},
|
| 16 |
-
"pad_token": {
|
| 17 |
-
"content": "<|endoftext|>",
|
| 18 |
-
"lstrip": false,
|
| 19 |
-
"normalized": false,
|
| 20 |
-
"rstrip": false,
|
| 21 |
-
"single_word": false
|
| 22 |
-
},
|
| 23 |
-
"unk_token": {
|
| 24 |
-
"content": "<unk>",
|
| 25 |
-
"lstrip": false,
|
| 26 |
-
"normalized": false,
|
| 27 |
-
"rstrip": false,
|
| 28 |
-
"single_word": false
|
| 29 |
-
}
|
| 30 |
-
}
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bos_token": {
|
| 3 |
+
"content": "<s>",
|
| 4 |
+
"lstrip": false,
|
| 5 |
+
"normalized": false,
|
| 6 |
+
"rstrip": false,
|
| 7 |
+
"single_word": false
|
| 8 |
+
},
|
| 9 |
+
"eos_token": {
|
| 10 |
+
"content": "<|endoftext|>",
|
| 11 |
+
"lstrip": false,
|
| 12 |
+
"normalized": false,
|
| 13 |
+
"rstrip": false,
|
| 14 |
+
"single_word": false
|
| 15 |
+
},
|
| 16 |
+
"pad_token": {
|
| 17 |
+
"content": "<|endoftext|>",
|
| 18 |
+
"lstrip": false,
|
| 19 |
+
"normalized": false,
|
| 20 |
+
"rstrip": false,
|
| 21 |
+
"single_word": false
|
| 22 |
+
},
|
| 23 |
+
"unk_token": {
|
| 24 |
+
"content": "<unk>",
|
| 25 |
+
"lstrip": false,
|
| 26 |
+
"normalized": false,
|
| 27 |
+
"rstrip": false,
|
| 28 |
+
"single_word": false
|
| 29 |
+
}
|
| 30 |
+
}
|
cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/tokenizer.json
CHANGED
|
The diff for this file is too large to render.
See raw diff
|
|
|
cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/tokenizer_config.json
CHANGED
|
@@ -1,130 +1,130 @@
|
|
| 1 |
-
{
|
| 2 |
-
"add_bos_token":
|
| 3 |
-
"add_eos_token": false,
|
| 4 |
-
"added_tokens_decoder": {
|
| 5 |
-
"0": {
|
| 6 |
-
"content": "<unk>",
|
| 7 |
-
"lstrip": false,
|
| 8 |
-
"normalized": false,
|
| 9 |
-
"rstrip": false,
|
| 10 |
-
"single_word": false,
|
| 11 |
-
"special": true
|
| 12 |
-
},
|
| 13 |
-
"1": {
|
| 14 |
-
"content": "<s>",
|
| 15 |
-
"lstrip": false,
|
| 16 |
-
"normalized": false,
|
| 17 |
-
"rstrip": false,
|
| 18 |
-
"single_word": false,
|
| 19 |
-
"special": true
|
| 20 |
-
},
|
| 21 |
-
"2": {
|
| 22 |
-
"content": "</s>",
|
| 23 |
-
"lstrip": false,
|
| 24 |
-
"normalized": false,
|
| 25 |
-
"rstrip": true,
|
| 26 |
-
"single_word": false,
|
| 27 |
-
"special": false
|
| 28 |
-
},
|
| 29 |
-
"32000": {
|
| 30 |
-
"content": "<|endoftext|>",
|
| 31 |
-
"lstrip": false,
|
| 32 |
-
"normalized": false,
|
| 33 |
-
"rstrip": false,
|
| 34 |
-
"single_word": false,
|
| 35 |
-
"special": true
|
| 36 |
-
},
|
| 37 |
-
"32001": {
|
| 38 |
-
"content": "<|assistant|>",
|
| 39 |
-
"lstrip": false,
|
| 40 |
-
"normalized": false,
|
| 41 |
-
"rstrip": true,
|
| 42 |
-
"single_word": false,
|
| 43 |
-
"special": true
|
| 44 |
-
},
|
| 45 |
-
"32002": {
|
| 46 |
-
"content": "<|placeholder1|>",
|
| 47 |
-
"lstrip": false,
|
| 48 |
-
"normalized": false,
|
| 49 |
-
"rstrip": true,
|
| 50 |
-
"single_word": false,
|
| 51 |
-
"special": true
|
| 52 |
-
},
|
| 53 |
-
"32003": {
|
| 54 |
-
"content": "<|placeholder2|>",
|
| 55 |
-
"lstrip": false,
|
| 56 |
-
"normalized": false,
|
| 57 |
-
"rstrip": true,
|
| 58 |
-
"single_word": false,
|
| 59 |
-
"special": true
|
| 60 |
-
},
|
| 61 |
-
"32004": {
|
| 62 |
-
"content": "<|placeholder3|>",
|
| 63 |
-
"lstrip": false,
|
| 64 |
-
"normalized": false,
|
| 65 |
-
"rstrip": true,
|
| 66 |
-
"single_word": false,
|
| 67 |
-
"special": true
|
| 68 |
-
},
|
| 69 |
-
"32005": {
|
| 70 |
-
"content": "<|placeholder4|>",
|
| 71 |
-
"lstrip": false,
|
| 72 |
-
"normalized": false,
|
| 73 |
-
"rstrip": true,
|
| 74 |
-
"single_word": false,
|
| 75 |
-
"special": true
|
| 76 |
-
},
|
| 77 |
-
"32006": {
|
| 78 |
-
"content": "<|system|>",
|
| 79 |
-
"lstrip": false,
|
| 80 |
-
"normalized": false,
|
| 81 |
-
"rstrip": true,
|
| 82 |
-
"single_word": false,
|
| 83 |
-
"special": true
|
| 84 |
-
},
|
| 85 |
-
"32007": {
|
| 86 |
-
"content": "<|end|>",
|
| 87 |
-
"lstrip": false,
|
| 88 |
-
"normalized": false,
|
| 89 |
-
"rstrip": true,
|
| 90 |
-
"single_word": false,
|
| 91 |
-
"special": true
|
| 92 |
-
},
|
| 93 |
-
"32008": {
|
| 94 |
-
"content": "<|placeholder5|>",
|
| 95 |
-
"lstrip": false,
|
| 96 |
-
"normalized": false,
|
| 97 |
-
"rstrip": true,
|
| 98 |
-
"single_word": false,
|
| 99 |
-
"special": true
|
| 100 |
-
},
|
| 101 |
-
"32009": {
|
| 102 |
-
"content": "<|placeholder6|>",
|
| 103 |
-
"lstrip": false,
|
| 104 |
-
"normalized": false,
|
| 105 |
-
"rstrip": true,
|
| 106 |
-
"single_word": false,
|
| 107 |
-
"special": true
|
| 108 |
-
},
|
| 109 |
-
"32010": {
|
| 110 |
-
"content": "<|user|>",
|
| 111 |
-
"lstrip": false,
|
| 112 |
-
"normalized": false,
|
| 113 |
-
"rstrip": true,
|
| 114 |
-
"single_word": false,
|
| 115 |
-
"special": true
|
| 116 |
-
}
|
| 117 |
-
},
|
| 118 |
-
"bos_token": "<s>",
|
| 119 |
-
"chat_template": "{
|
| 120 |
-
"clean_up_tokenization_spaces": false,
|
| 121 |
-
"eos_token": "<|endoftext|>",
|
| 122 |
-
"legacy": false,
|
| 123 |
-
"model_max_length": 131072,
|
| 124 |
-
"pad_token": "<|endoftext|>",
|
| 125 |
-
"padding_side": "left",
|
| 126 |
-
"sp_model_kwargs": {},
|
| 127 |
-
"tokenizer_class": "LlamaTokenizer",
|
| 128 |
-
"unk_token": "<unk>",
|
| 129 |
-
"use_default_system_prompt": false
|
| 130 |
-
}
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_bos_token": false,
|
| 3 |
+
"add_eos_token": false,
|
| 4 |
+
"added_tokens_decoder": {
|
| 5 |
+
"0": {
|
| 6 |
+
"content": "<unk>",
|
| 7 |
+
"lstrip": false,
|
| 8 |
+
"normalized": false,
|
| 9 |
+
"rstrip": false,
|
| 10 |
+
"single_word": false,
|
| 11 |
+
"special": true
|
| 12 |
+
},
|
| 13 |
+
"1": {
|
| 14 |
+
"content": "<s>",
|
| 15 |
+
"lstrip": false,
|
| 16 |
+
"normalized": false,
|
| 17 |
+
"rstrip": false,
|
| 18 |
+
"single_word": false,
|
| 19 |
+
"special": true
|
| 20 |
+
},
|
| 21 |
+
"2": {
|
| 22 |
+
"content": "</s>",
|
| 23 |
+
"lstrip": false,
|
| 24 |
+
"normalized": false,
|
| 25 |
+
"rstrip": true,
|
| 26 |
+
"single_word": false,
|
| 27 |
+
"special": false
|
| 28 |
+
},
|
| 29 |
+
"32000": {
|
| 30 |
+
"content": "<|endoftext|>",
|
| 31 |
+
"lstrip": false,
|
| 32 |
+
"normalized": false,
|
| 33 |
+
"rstrip": false,
|
| 34 |
+
"single_word": false,
|
| 35 |
+
"special": true
|
| 36 |
+
},
|
| 37 |
+
"32001": {
|
| 38 |
+
"content": "<|assistant|>",
|
| 39 |
+
"lstrip": false,
|
| 40 |
+
"normalized": false,
|
| 41 |
+
"rstrip": true,
|
| 42 |
+
"single_word": false,
|
| 43 |
+
"special": true
|
| 44 |
+
},
|
| 45 |
+
"32002": {
|
| 46 |
+
"content": "<|placeholder1|>",
|
| 47 |
+
"lstrip": false,
|
| 48 |
+
"normalized": false,
|
| 49 |
+
"rstrip": true,
|
| 50 |
+
"single_word": false,
|
| 51 |
+
"special": true
|
| 52 |
+
},
|
| 53 |
+
"32003": {
|
| 54 |
+
"content": "<|placeholder2|>",
|
| 55 |
+
"lstrip": false,
|
| 56 |
+
"normalized": false,
|
| 57 |
+
"rstrip": true,
|
| 58 |
+
"single_word": false,
|
| 59 |
+
"special": true
|
| 60 |
+
},
|
| 61 |
+
"32004": {
|
| 62 |
+
"content": "<|placeholder3|>",
|
| 63 |
+
"lstrip": false,
|
| 64 |
+
"normalized": false,
|
| 65 |
+
"rstrip": true,
|
| 66 |
+
"single_word": false,
|
| 67 |
+
"special": true
|
| 68 |
+
},
|
| 69 |
+
"32005": {
|
| 70 |
+
"content": "<|placeholder4|>",
|
| 71 |
+
"lstrip": false,
|
| 72 |
+
"normalized": false,
|
| 73 |
+
"rstrip": true,
|
| 74 |
+
"single_word": false,
|
| 75 |
+
"special": true
|
| 76 |
+
},
|
| 77 |
+
"32006": {
|
| 78 |
+
"content": "<|system|>",
|
| 79 |
+
"lstrip": false,
|
| 80 |
+
"normalized": false,
|
| 81 |
+
"rstrip": true,
|
| 82 |
+
"single_word": false,
|
| 83 |
+
"special": true
|
| 84 |
+
},
|
| 85 |
+
"32007": {
|
| 86 |
+
"content": "<|end|>",
|
| 87 |
+
"lstrip": false,
|
| 88 |
+
"normalized": false,
|
| 89 |
+
"rstrip": true,
|
| 90 |
+
"single_word": false,
|
| 91 |
+
"special": true
|
| 92 |
+
},
|
| 93 |
+
"32008": {
|
| 94 |
+
"content": "<|placeholder5|>",
|
| 95 |
+
"lstrip": false,
|
| 96 |
+
"normalized": false,
|
| 97 |
+
"rstrip": true,
|
| 98 |
+
"single_word": false,
|
| 99 |
+
"special": true
|
| 100 |
+
},
|
| 101 |
+
"32009": {
|
| 102 |
+
"content": "<|placeholder6|>",
|
| 103 |
+
"lstrip": false,
|
| 104 |
+
"normalized": false,
|
| 105 |
+
"rstrip": true,
|
| 106 |
+
"single_word": false,
|
| 107 |
+
"special": true
|
| 108 |
+
},
|
| 109 |
+
"32010": {
|
| 110 |
+
"content": "<|user|>",
|
| 111 |
+
"lstrip": false,
|
| 112 |
+
"normalized": false,
|
| 113 |
+
"rstrip": true,
|
| 114 |
+
"single_word": false,
|
| 115 |
+
"special": true
|
| 116 |
+
}
|
| 117 |
+
},
|
| 118 |
+
"bos_token": "<s>",
|
| 119 |
+
"chat_template": "{% for message in messages %}{% if message['role'] == 'system' %}{{'<|system|>\n' + message['content'] + '<|end|>\n'}}{% elif message['role'] == 'user' %}{{'<|user|>\n' + message['content'] + '<|end|>\n'}}{% elif message['role'] == 'assistant' %}{{'<|assistant|>\n' + message['content'] + '<|end|>\n'}}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|assistant|>\n' }}{% else %}{{ eos_token }}{% endif %}",
|
| 120 |
+
"clean_up_tokenization_spaces": false,
|
| 121 |
+
"eos_token": "<|endoftext|>",
|
| 122 |
+
"legacy": false,
|
| 123 |
+
"model_max_length": 131072,
|
| 124 |
+
"pad_token": "<|endoftext|>",
|
| 125 |
+
"padding_side": "left",
|
| 126 |
+
"sp_model_kwargs": {},
|
| 127 |
+
"tokenizer_class": "LlamaTokenizer",
|
| 128 |
+
"unk_token": "<unk>",
|
| 129 |
+
"use_default_system_prompt": false
|
| 130 |
+
}
|
cpu_and_mobile/cpu-int4-rtn-block-32/added_tokens.json
CHANGED
|
@@ -1,13 +1,13 @@
|
|
| 1 |
-
{
|
| 2 |
-
"<|endoftext|>": 32000,
|
| 3 |
-
"<|assistant|>": 32001,
|
| 4 |
-
"<|placeholder1|>": 32002,
|
| 5 |
-
"<|placeholder2|>": 32003,
|
| 6 |
-
"<|placeholder3|>": 32004,
|
| 7 |
-
"<|placeholder4|>": 32005,
|
| 8 |
-
"<|system|>": 32006,
|
| 9 |
-
"<|end|>": 32007,
|
| 10 |
-
"<|placeholder5|>": 32008,
|
| 11 |
-
"<|placeholder6|>": 32009,
|
| 12 |
-
"<|user|>": 32010
|
| 13 |
-
}
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"<|endoftext|>": 32000,
|
| 3 |
+
"<|assistant|>": 32001,
|
| 4 |
+
"<|placeholder1|>": 32002,
|
| 5 |
+
"<|placeholder2|>": 32003,
|
| 6 |
+
"<|placeholder3|>": 32004,
|
| 7 |
+
"<|placeholder4|>": 32005,
|
| 8 |
+
"<|system|>": 32006,
|
| 9 |
+
"<|end|>": 32007,
|
| 10 |
+
"<|placeholder5|>": 32008,
|
| 11 |
+
"<|placeholder6|>": 32009,
|
| 12 |
+
"<|user|>": 32010
|
| 13 |
+
}
|
cpu_and_mobile/cpu-int4-rtn-block-32/config.json
CHANGED
|
@@ -1,137 +1,138 @@
|
|
| 1 |
-
{
|
| 2 |
-
"_name_or_path": "
|
| 3 |
-
"architectures": [
|
| 4 |
-
"Phi3ForCausalLM"
|
| 5 |
-
],
|
| 6 |
-
"attention_dropout": 0.0,
|
| 7 |
-
"auto_map": {
|
| 8 |
-
"AutoConfig": "configuration_phi3.Phi3Config",
|
| 9 |
-
"AutoModelForCausalLM": "modeling_phi3.Phi3ForCausalLM"
|
| 10 |
-
},
|
| 11 |
-
"bos_token_id": 1,
|
| 12 |
-
"embd_pdrop": 0.0,
|
| 13 |
-
"eos_token_id": 32000,
|
| 14 |
-
"hidden_act": "silu",
|
| 15 |
-
"hidden_size": 3072,
|
| 16 |
-
"initializer_range": 0.02,
|
| 17 |
-
"intermediate_size": 8192,
|
| 18 |
-
"max_position_embeddings": 131072,
|
| 19 |
-
"model_type": "phi3",
|
| 20 |
-
"num_attention_heads": 32,
|
| 21 |
-
"num_hidden_layers": 32,
|
| 22 |
-
"num_key_value_heads": 32,
|
| 23 |
-
"original_max_position_embeddings": 4096,
|
| 24 |
-
"pad_token_id": 32000,
|
| 25 |
-
"resid_pdrop": 0.0,
|
| 26 |
-
"rms_norm_eps": 1e-05,
|
| 27 |
-
"rope_scaling": {
|
| 28 |
-
"long_factor": [
|
| 29 |
-
1.
|
| 30 |
-
1.
|
| 31 |
-
1.
|
| 32 |
-
1.
|
| 33 |
-
1.
|
| 34 |
-
1.
|
| 35 |
-
|
| 36 |
-
|
| 37 |
-
|
| 38 |
-
|
| 39 |
-
|
| 40 |
-
|
| 41 |
-
|
| 42 |
-
|
| 43 |
-
|
| 44 |
-
|
| 45 |
-
|
| 46 |
-
|
| 47 |
-
|
| 48 |
-
|
| 49 |
-
|
| 50 |
-
|
| 51 |
-
|
| 52 |
-
|
| 53 |
-
|
| 54 |
-
|
| 55 |
-
|
| 56 |
-
|
| 57 |
-
|
| 58 |
-
|
| 59 |
-
|
| 60 |
-
|
| 61 |
-
|
| 62 |
-
|
| 63 |
-
|
| 64 |
-
|
| 65 |
-
|
| 66 |
-
|
| 67 |
-
63.
|
| 68 |
-
|
| 69 |
-
|
| 70 |
-
|
| 71 |
-
|
| 72 |
-
64.
|
| 73 |
-
64.
|
| 74 |
-
64.
|
| 75 |
-
64.
|
| 76 |
-
64.
|
| 77 |
-
],
|
| 78 |
-
"short_factor": [
|
| 79 |
-
1.
|
| 80 |
-
1.
|
| 81 |
-
1.
|
| 82 |
-
1.
|
| 83 |
-
1.
|
| 84 |
-
1.
|
| 85 |
-
1.
|
| 86 |
-
1.
|
| 87 |
-
|
| 88 |
-
|
| 89 |
-
|
| 90 |
-
2.000000000000001,
|
| 91 |
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2.000000000000001,
|
| 92 |
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2.000000000000001,
|
| 93 |
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2.000000000000001,
|
| 94 |
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2.000000000000001,
|
| 95 |
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2.000000000000001,
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| 96 |
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2.000000000000001,
|
| 97 |
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2.000000000000001,
|
| 98 |
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2.000000000000001,
|
| 99 |
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2.000000000000001,
|
| 100 |
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2.000000000000001,
|
| 101 |
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2.000000000000001,
|
| 102 |
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2.000000000000001,
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2.000000000000001,
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| 104 |
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2.
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| 105 |
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2.
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| 106 |
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2.
|
| 107 |
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2.
|
| 108 |
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2.
|
| 109 |
-
2.
|
| 110 |
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2.
|
| 111 |
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2.
|
| 112 |
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2.
|
| 113 |
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2.
|
| 114 |
-
2.
|
| 115 |
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2.
|
| 116 |
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2.
|
| 117 |
-
2.
|
| 118 |
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2.
|
| 119 |
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2.
|
| 120 |
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2.
|
| 121 |
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2.
|
| 122 |
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2.
|
| 123 |
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2.7499999999999982,
|
| 124 |
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2.
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| 125 |
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2.
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| 126 |
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| 127 |
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| 128 |
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| 129 |
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},
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| 130 |
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|
| 131 |
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|
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|
| 136 |
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"
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| 137 |
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|
|
|
|
|
| 1 |
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{
|
| 2 |
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"_name_or_path": "Phi-3-mini-128k-instruct",
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| 3 |
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| 4 |
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"Phi3ForCausalLM"
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| 5 |
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],
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| 6 |
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| 10 |
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},
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],
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3.049999999999997
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],
|
| 128 |
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"type": "longrope"
|
| 129 |
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},
|
| 130 |
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|
| 131 |
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|
| 132 |
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|
| 133 |
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"torch_dtype": "bfloat16",
|
| 134 |
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|
| 135 |
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"use_cache": true,
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| 136 |
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"attention_bias": false,
|
| 137 |
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"vocab_size": 32064
|
| 138 |
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}
|
cpu_and_mobile/cpu-int4-rtn-block-32/configuration_phi3.py
CHANGED
|
@@ -1,213 +1,227 @@
|
|
| 1 |
-
# coding=utf-8
|
| 2 |
-
# Copyright 2024 Microsoft and the HuggingFace Inc. team. All rights reserved.
|
| 3 |
-
#
|
| 4 |
-
# Licensed under the Apache License, Version 2.0 (the "License");
|
| 5 |
-
# you may not use this file except in compliance with the License.
|
| 6 |
-
# You may obtain a copy of the License at
|
| 7 |
-
#
|
| 8 |
-
# http://www.apache.org/licenses/LICENSE-2.0
|
| 9 |
-
#
|
| 10 |
-
# Unless required by applicable law or agreed to in writing, software
|
| 11 |
-
# distributed under the License is distributed on an "AS IS" BASIS,
|
| 12 |
-
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
| 13 |
-
# See the License for the specific language governing permissions and
|
| 14 |
-
# limitations under the License.
|
| 15 |
-
|
| 16 |
-
""" Phi-3 model configuration"""
|
| 17 |
-
|
| 18 |
-
|
| 19 |
-
from transformers.configuration_utils import PretrainedConfig
|
| 20 |
-
from transformers.utils import logging
|
| 21 |
-
|
| 22 |
-
|
| 23 |
-
logger = logging.get_logger(__name__)
|
| 24 |
-
|
| 25 |
-
PHI3_PRETRAINED_CONFIG_ARCHIVE_MAP = {
|
| 26 |
-
"microsoft/Phi-3-mini-4k-instruct": "https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/resolve/main/config.json",
|
| 27 |
-
"microsoft/Phi-3-mini-128k-instruct": "https://huggingface.co/microsoft/Phi-3-mini-128k-instruct/resolve/main/config.json",
|
| 28 |
-
}
|
| 29 |
-
|
| 30 |
-
|
| 31 |
-
class Phi3Config(PretrainedConfig):
|
| 32 |
-
r"""
|
| 33 |
-
This is the configuration class to store the configuration of a [`Phi3Model`]. It is used to instantiate a Phi-3
|
| 34 |
-
model according to the specified arguments, defining the model architecture. Instantiating a configuration with the
|
| 35 |
-
defaults will yield a similar configuration to that of the
|
| 36 |
-
[microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct).
|
| 37 |
-
|
| 38 |
-
Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
|
| 39 |
-
documentation from [`PretrainedConfig`] for more information.
|
| 40 |
-
|
| 41 |
-
Args:
|
| 42 |
-
vocab_size (`int`, *optional*, defaults to 32064):
|
| 43 |
-
Vocabulary size of the Phi-3 model. Defines the number of different tokens that can be represented by the
|
| 44 |
-
`inputs_ids` passed when calling [`Phi3Model`].
|
| 45 |
-
hidden_size (`int`, *optional*, defaults to 3072):
|
| 46 |
-
Dimension of the hidden representations.
|
| 47 |
-
intermediate_size (`int`, *optional*, defaults to 8192):
|
| 48 |
-
Dimension of the MLP representations.
|
| 49 |
-
num_hidden_layers (`int`, *optional*, defaults to 32):
|
| 50 |
-
Number of hidden layers in the Transformer decoder.
|
| 51 |
-
num_attention_heads (`int`, *optional*, defaults to 32):
|
| 52 |
-
Number of attention heads for each attention layer in the Transformer decoder.
|
| 53 |
-
num_key_value_heads (`int`, *optional*):
|
| 54 |
-
This is the number of key_value heads that should be used to implement Grouped Query Attention. If
|
| 55 |
-
`num_key_value_heads=num_attention_heads`, the model will use Multi Head Attention (MHA), if
|
| 56 |
-
`num_key_value_heads=1 the model will use Multi Query Attention (MQA) otherwise GQA is used. When
|
| 57 |
-
converting a multi-head checkpoint to a GQA checkpoint, each group key and value head should be constructed
|
| 58 |
-
by meanpooling all the original heads within that group. For more details checkout [this
|
| 59 |
-
paper](https://arxiv.org/pdf/2305.13245.pdf). If it is not specified, will default to
|
| 60 |
-
`num_attention_heads`.
|
| 61 |
-
resid_pdrop (`float`, *optional*, defaults to 0.0):
|
| 62 |
-
Dropout probability for mlp outputs.
|
| 63 |
-
embd_pdrop (`int`, *optional*, defaults to 0.0):
|
| 64 |
-
The dropout ratio for the embeddings.
|
| 65 |
-
attention_dropout (`float`, *optional*, defaults to 0.0):
|
| 66 |
-
The dropout ratio after computing the attention scores.
|
| 67 |
-
hidden_act (`str` or `function`, *optional*, defaults to `"silu"`):
|
| 68 |
-
The non-linear activation function (function or string) in the decoder.
|
| 69 |
-
max_position_embeddings (`int`, *optional*, defaults to 4096):
|
| 70 |
-
The maximum sequence length that this model might ever be used with.
|
| 71 |
-
original_max_position_embeddings (`int`, *optional*, defaults to 4096):
|
| 72 |
-
The maximum sequence length that this model was trained with. This is used to determine the size of the
|
| 73 |
-
original RoPE embeddings when using long scaling.
|
| 74 |
-
initializer_range (`float`, *optional*, defaults to 0.02):
|
| 75 |
-
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
|
| 76 |
-
rms_norm_eps (`float`, *optional*, defaults to 1e-05):
|
| 77 |
-
The epsilon value used for the RMSNorm.
|
| 78 |
-
use_cache (`bool`, *optional*, defaults to `True`):
|
| 79 |
-
Whether or not the model should return the last key/values attentions (not used by all models). Only
|
| 80 |
-
relevant if `config.is_decoder=True`. Whether to tie weight embeddings or not.
|
| 81 |
-
tie_word_embeddings (`bool`, *optional*, defaults to `False`):
|
| 82 |
-
Whether to tie weight embeddings
|
| 83 |
-
rope_theta (`float`, *optional*, defaults to 10000.0):
|
| 84 |
-
The base period of the RoPE embeddings.
|
| 85 |
-
rope_scaling (`dict`, *optional*):
|
| 86 |
-
The scaling strategy for the RoPE embeddings. If `None`, no scaling is applied. If a dictionary, it must
|
| 87 |
-
contain the following keys: `type`, `short_factor` and `long_factor`. The `type` must be
|
| 88 |
-
the `short_factor` and `long_factor` must be lists of numbers with the same length as the hidden size
|
| 89 |
-
divided by the number of attention heads divided by 2.
|
| 90 |
-
bos_token_id (`int`, *optional*, defaults to 1):
|
| 91 |
-
The id of the "beginning-of-sequence" token.
|
| 92 |
-
eos_token_id (`int`, *optional*, defaults to 32000):
|
| 93 |
-
The id of the "end-of-sequence" token.
|
| 94 |
-
pad_token_id (`int`, *optional*, defaults to 32000):
|
| 95 |
-
The id of the padding token.
|
| 96 |
-
sliding_window (`int`, *optional*):
|
| 97 |
-
Sliding window attention window size. If `None`, no sliding window is applied.
|
| 98 |
-
|
| 99 |
-
Example:
|
| 100 |
-
|
| 101 |
-
```python
|
| 102 |
-
>>> from transformers import Phi3Model, Phi3Config
|
| 103 |
-
|
| 104 |
-
>>> # Initializing a Phi-3 style configuration
|
| 105 |
-
>>> configuration = Phi3Config.from_pretrained("microsoft/Phi-3-mini-4k-instruct")
|
| 106 |
-
|
| 107 |
-
>>> # Initializing a model from the configuration
|
| 108 |
-
>>> model = Phi3Model(configuration)
|
| 109 |
-
|
| 110 |
-
>>> # Accessing the model configuration
|
| 111 |
-
>>> configuration = model.config
|
| 112 |
-
```"""
|
| 113 |
-
|
| 114 |
-
model_type = "phi3"
|
| 115 |
-
keys_to_ignore_at_inference = ["past_key_values"]
|
| 116 |
-
|
| 117 |
-
def __init__(
|
| 118 |
-
self,
|
| 119 |
-
vocab_size=32064,
|
| 120 |
-
hidden_size=3072,
|
| 121 |
-
intermediate_size=8192,
|
| 122 |
-
num_hidden_layers=32,
|
| 123 |
-
num_attention_heads=32,
|
| 124 |
-
num_key_value_heads=None,
|
| 125 |
-
resid_pdrop=0.0,
|
| 126 |
-
embd_pdrop=0.0,
|
| 127 |
-
attention_dropout=0.0,
|
| 128 |
-
hidden_act="silu",
|
| 129 |
-
max_position_embeddings=4096,
|
| 130 |
-
original_max_position_embeddings=4096,
|
| 131 |
-
initializer_range=0.02,
|
| 132 |
-
rms_norm_eps=1e-5,
|
| 133 |
-
use_cache=True,
|
| 134 |
-
tie_word_embeddings=False,
|
| 135 |
-
rope_theta=10000.0,
|
| 136 |
-
rope_scaling=None,
|
| 137 |
-
bos_token_id=1,
|
| 138 |
-
eos_token_id=32000,
|
| 139 |
-
pad_token_id=32000,
|
| 140 |
-
sliding_window=None,
|
| 141 |
-
**kwargs,
|
| 142 |
-
):
|
| 143 |
-
self.vocab_size = vocab_size
|
| 144 |
-
self.hidden_size = hidden_size
|
| 145 |
-
self.intermediate_size = intermediate_size
|
| 146 |
-
self.num_hidden_layers = num_hidden_layers
|
| 147 |
-
self.num_attention_heads = num_attention_heads
|
| 148 |
-
|
| 149 |
-
if num_key_value_heads is None:
|
| 150 |
-
num_key_value_heads = num_attention_heads
|
| 151 |
-
|
| 152 |
-
self.num_key_value_heads = num_key_value_heads
|
| 153 |
-
self.resid_pdrop = resid_pdrop
|
| 154 |
-
self.embd_pdrop = embd_pdrop
|
| 155 |
-
self.attention_dropout = attention_dropout
|
| 156 |
-
self.hidden_act = hidden_act
|
| 157 |
-
self.max_position_embeddings = max_position_embeddings
|
| 158 |
-
self.original_max_position_embeddings = original_max_position_embeddings
|
| 159 |
-
self.initializer_range = initializer_range
|
| 160 |
-
self.rms_norm_eps = rms_norm_eps
|
| 161 |
-
self.use_cache = use_cache
|
| 162 |
-
self.rope_theta = rope_theta
|
| 163 |
-
self.rope_scaling = rope_scaling
|
| 164 |
-
self.
|
| 165 |
-
self.
|
| 166 |
-
|
| 167 |
-
|
| 168 |
-
|
| 169 |
-
|
| 170 |
-
|
| 171 |
-
|
| 172 |
-
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| 173 |
-
|
| 174 |
-
|
| 175 |
-
|
| 176 |
-
|
| 177 |
-
|
| 178 |
-
|
| 179 |
-
|
| 180 |
-
|
| 181 |
-
|
| 182 |
-
|
| 183 |
-
|
| 184 |
-
|
| 185 |
-
|
| 186 |
-
|
| 187 |
-
|
| 188 |
-
|
| 189 |
-
|
| 190 |
-
|
| 191 |
-
|
| 192 |
-
|
| 193 |
-
|
| 194 |
-
|
| 195 |
-
|
| 196 |
-
|
| 197 |
-
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-
|
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-
|
| 200 |
-
|
| 201 |
-
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| 202 |
-
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| 203 |
-
|
| 204 |
-
|
| 205 |
-
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-
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-
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-
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-
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-
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-
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-
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-
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# coding=utf-8
|
| 2 |
+
# Copyright 2024 Microsoft and the HuggingFace Inc. team. All rights reserved.
|
| 3 |
+
#
|
| 4 |
+
# Licensed under the Apache License, Version 2.0 (the "License");
|
| 5 |
+
# you may not use this file except in compliance with the License.
|
| 6 |
+
# You may obtain a copy of the License at
|
| 7 |
+
#
|
| 8 |
+
# http://www.apache.org/licenses/LICENSE-2.0
|
| 9 |
+
#
|
| 10 |
+
# Unless required by applicable law or agreed to in writing, software
|
| 11 |
+
# distributed under the License is distributed on an "AS IS" BASIS,
|
| 12 |
+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
| 13 |
+
# See the License for the specific language governing permissions and
|
| 14 |
+
# limitations under the License.
|
| 15 |
+
|
| 16 |
+
""" Phi-3 model configuration"""
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
from transformers.configuration_utils import PretrainedConfig
|
| 20 |
+
from transformers.utils import logging
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
logger = logging.get_logger(__name__)
|
| 24 |
+
|
| 25 |
+
PHI3_PRETRAINED_CONFIG_ARCHIVE_MAP = {
|
| 26 |
+
"microsoft/Phi-3-mini-4k-instruct": "https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/resolve/main/config.json",
|
| 27 |
+
"microsoft/Phi-3-mini-128k-instruct": "https://huggingface.co/microsoft/Phi-3-mini-128k-instruct/resolve/main/config.json",
|
| 28 |
+
}
|
| 29 |
+
|
| 30 |
+
|
| 31 |
+
class Phi3Config(PretrainedConfig):
|
| 32 |
+
r"""
|
| 33 |
+
This is the configuration class to store the configuration of a [`Phi3Model`]. It is used to instantiate a Phi-3
|
| 34 |
+
model according to the specified arguments, defining the model architecture. Instantiating a configuration with the
|
| 35 |
+
defaults will yield a similar configuration to that of the
|
| 36 |
+
[microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct).
|
| 37 |
+
|
| 38 |
+
Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
|
| 39 |
+
documentation from [`PretrainedConfig`] for more information.
|
| 40 |
+
|
| 41 |
+
Args:
|
| 42 |
+
vocab_size (`int`, *optional*, defaults to 32064):
|
| 43 |
+
Vocabulary size of the Phi-3 model. Defines the number of different tokens that can be represented by the
|
| 44 |
+
`inputs_ids` passed when calling [`Phi3Model`].
|
| 45 |
+
hidden_size (`int`, *optional*, defaults to 3072):
|
| 46 |
+
Dimension of the hidden representations.
|
| 47 |
+
intermediate_size (`int`, *optional*, defaults to 8192):
|
| 48 |
+
Dimension of the MLP representations.
|
| 49 |
+
num_hidden_layers (`int`, *optional*, defaults to 32):
|
| 50 |
+
Number of hidden layers in the Transformer decoder.
|
| 51 |
+
num_attention_heads (`int`, *optional*, defaults to 32):
|
| 52 |
+
Number of attention heads for each attention layer in the Transformer decoder.
|
| 53 |
+
num_key_value_heads (`int`, *optional*):
|
| 54 |
+
This is the number of key_value heads that should be used to implement Grouped Query Attention. If
|
| 55 |
+
`num_key_value_heads=num_attention_heads`, the model will use Multi Head Attention (MHA), if
|
| 56 |
+
`num_key_value_heads=1 the model will use Multi Query Attention (MQA) otherwise GQA is used. When
|
| 57 |
+
converting a multi-head checkpoint to a GQA checkpoint, each group key and value head should be constructed
|
| 58 |
+
by meanpooling all the original heads within that group. For more details checkout [this
|
| 59 |
+
paper](https://arxiv.org/pdf/2305.13245.pdf). If it is not specified, will default to
|
| 60 |
+
`num_attention_heads`.
|
| 61 |
+
resid_pdrop (`float`, *optional*, defaults to 0.0):
|
| 62 |
+
Dropout probability for mlp outputs.
|
| 63 |
+
embd_pdrop (`int`, *optional*, defaults to 0.0):
|
| 64 |
+
The dropout ratio for the embeddings.
|
| 65 |
+
attention_dropout (`float`, *optional*, defaults to 0.0):
|
| 66 |
+
The dropout ratio after computing the attention scores.
|
| 67 |
+
hidden_act (`str` or `function`, *optional*, defaults to `"silu"`):
|
| 68 |
+
The non-linear activation function (function or string) in the decoder.
|
| 69 |
+
max_position_embeddings (`int`, *optional*, defaults to 4096):
|
| 70 |
+
The maximum sequence length that this model might ever be used with.
|
| 71 |
+
original_max_position_embeddings (`int`, *optional*, defaults to 4096):
|
| 72 |
+
The maximum sequence length that this model was trained with. This is used to determine the size of the
|
| 73 |
+
original RoPE embeddings when using long scaling.
|
| 74 |
+
initializer_range (`float`, *optional*, defaults to 0.02):
|
| 75 |
+
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
|
| 76 |
+
rms_norm_eps (`float`, *optional*, defaults to 1e-05):
|
| 77 |
+
The epsilon value used for the RMSNorm.
|
| 78 |
+
use_cache (`bool`, *optional*, defaults to `True`):
|
| 79 |
+
Whether or not the model should return the last key/values attentions (not used by all models). Only
|
| 80 |
+
relevant if `config.is_decoder=True`. Whether to tie weight embeddings or not.
|
| 81 |
+
tie_word_embeddings (`bool`, *optional*, defaults to `False`):
|
| 82 |
+
Whether to tie weight embeddings
|
| 83 |
+
rope_theta (`float`, *optional*, defaults to 10000.0):
|
| 84 |
+
The base period of the RoPE embeddings.
|
| 85 |
+
rope_scaling (`dict`, *optional*):
|
| 86 |
+
The scaling strategy for the RoPE embeddings. If `None`, no scaling is applied. If a dictionary, it must
|
| 87 |
+
contain the following keys: `type`, `short_factor` and `long_factor`. The `type` must be `longrope` and
|
| 88 |
+
the `short_factor` and `long_factor` must be lists of numbers with the same length as the hidden size
|
| 89 |
+
divided by the number of attention heads divided by 2.
|
| 90 |
+
bos_token_id (`int`, *optional*, defaults to 1):
|
| 91 |
+
The id of the "beginning-of-sequence" token.
|
| 92 |
+
eos_token_id (`int`, *optional*, defaults to 32000):
|
| 93 |
+
The id of the "end-of-sequence" token.
|
| 94 |
+
pad_token_id (`int`, *optional*, defaults to 32000):
|
| 95 |
+
The id of the padding token.
|
| 96 |
+
sliding_window (`int`, *optional*):
|
| 97 |
+
Sliding window attention window size. If `None`, no sliding window is applied.
|
| 98 |
+
|
| 99 |
+
Example:
|
| 100 |
+
|
| 101 |
+
```python
|
| 102 |
+
>>> from transformers import Phi3Model, Phi3Config
|
| 103 |
+
|
| 104 |
+
>>> # Initializing a Phi-3 style configuration
|
| 105 |
+
>>> configuration = Phi3Config.from_pretrained("microsoft/Phi-3-mini-4k-instruct")
|
| 106 |
+
|
| 107 |
+
>>> # Initializing a model from the configuration
|
| 108 |
+
>>> model = Phi3Model(configuration)
|
| 109 |
+
|
| 110 |
+
>>> # Accessing the model configuration
|
| 111 |
+
>>> configuration = model.config
|
| 112 |
+
```"""
|
| 113 |
+
|
| 114 |
+
model_type = "phi3"
|
| 115 |
+
keys_to_ignore_at_inference = ["past_key_values"]
|
| 116 |
+
|
| 117 |
+
def __init__(
|
| 118 |
+
self,
|
| 119 |
+
vocab_size=32064,
|
| 120 |
+
hidden_size=3072,
|
| 121 |
+
intermediate_size=8192,
|
| 122 |
+
num_hidden_layers=32,
|
| 123 |
+
num_attention_heads=32,
|
| 124 |
+
num_key_value_heads=None,
|
| 125 |
+
resid_pdrop=0.0,
|
| 126 |
+
embd_pdrop=0.0,
|
| 127 |
+
attention_dropout=0.0,
|
| 128 |
+
hidden_act="silu",
|
| 129 |
+
max_position_embeddings=4096,
|
| 130 |
+
original_max_position_embeddings=4096,
|
| 131 |
+
initializer_range=0.02,
|
| 132 |
+
rms_norm_eps=1e-5,
|
| 133 |
+
use_cache=True,
|
| 134 |
+
tie_word_embeddings=False,
|
| 135 |
+
rope_theta=10000.0,
|
| 136 |
+
rope_scaling=None,
|
| 137 |
+
bos_token_id=1,
|
| 138 |
+
eos_token_id=32000,
|
| 139 |
+
pad_token_id=32000,
|
| 140 |
+
sliding_window=None,
|
| 141 |
+
**kwargs,
|
| 142 |
+
):
|
| 143 |
+
self.vocab_size = vocab_size
|
| 144 |
+
self.hidden_size = hidden_size
|
| 145 |
+
self.intermediate_size = intermediate_size
|
| 146 |
+
self.num_hidden_layers = num_hidden_layers
|
| 147 |
+
self.num_attention_heads = num_attention_heads
|
| 148 |
+
|
| 149 |
+
if num_key_value_heads is None:
|
| 150 |
+
num_key_value_heads = num_attention_heads
|
| 151 |
+
|
| 152 |
+
self.num_key_value_heads = num_key_value_heads
|
| 153 |
+
self.resid_pdrop = resid_pdrop
|
| 154 |
+
self.embd_pdrop = embd_pdrop
|
| 155 |
+
self.attention_dropout = attention_dropout
|
| 156 |
+
self.hidden_act = hidden_act
|
| 157 |
+
self.max_position_embeddings = max_position_embeddings
|
| 158 |
+
self.original_max_position_embeddings = original_max_position_embeddings
|
| 159 |
+
self.initializer_range = initializer_range
|
| 160 |
+
self.rms_norm_eps = rms_norm_eps
|
| 161 |
+
self.use_cache = use_cache
|
| 162 |
+
self.rope_theta = rope_theta
|
| 163 |
+
self.rope_scaling = rope_scaling
|
| 164 |
+
self._rope_scaling_adjustment()
|
| 165 |
+
self._rope_scaling_validation()
|
| 166 |
+
self.sliding_window = sliding_window
|
| 167 |
+
|
| 168 |
+
super().__init__(
|
| 169 |
+
bos_token_id=bos_token_id,
|
| 170 |
+
eos_token_id=eos_token_id,
|
| 171 |
+
pad_token_id=pad_token_id,
|
| 172 |
+
tie_word_embeddings=tie_word_embeddings,
|
| 173 |
+
**kwargs,
|
| 174 |
+
)
|
| 175 |
+
|
| 176 |
+
def _rope_scaling_adjustment(self):
|
| 177 |
+
"""
|
| 178 |
+
Adjust the `type` of the `rope_scaling` configuration for backward compatibility.
|
| 179 |
+
"""
|
| 180 |
+
if self.rope_scaling is None:
|
| 181 |
+
return
|
| 182 |
+
|
| 183 |
+
rope_scaling_type = self.rope_scaling.get("type", None)
|
| 184 |
+
|
| 185 |
+
# For backward compatibility if previous version used "su" or "yarn"
|
| 186 |
+
if rope_scaling_type is not None and rope_scaling_type in ["su", "yarn"]:
|
| 187 |
+
self.rope_scaling["type"] = "longrope"
|
| 188 |
+
|
| 189 |
+
def _rope_scaling_validation(self):
|
| 190 |
+
"""
|
| 191 |
+
Validate the `rope_scaling` configuration.
|
| 192 |
+
"""
|
| 193 |
+
if self.rope_scaling is None:
|
| 194 |
+
return
|
| 195 |
+
|
| 196 |
+
if not isinstance(self.rope_scaling, dict) or len(self.rope_scaling) != 3:
|
| 197 |
+
raise ValueError(
|
| 198 |
+
"`rope_scaling` must be a dictionary with three fields, `type`, `short_factor` and `long_factor`, "
|
| 199 |
+
f"got {self.rope_scaling}"
|
| 200 |
+
)
|
| 201 |
+
rope_scaling_type = self.rope_scaling.get("type", None)
|
| 202 |
+
rope_scaling_short_factor = self.rope_scaling.get("short_factor", None)
|
| 203 |
+
rope_scaling_long_factor = self.rope_scaling.get("long_factor", None)
|
| 204 |
+
if rope_scaling_type is None or rope_scaling_type not in ["longrope"]:
|
| 205 |
+
raise ValueError(f"`rope_scaling`'s type field must be one of ['longrope'], got {rope_scaling_type}")
|
| 206 |
+
if not (
|
| 207 |
+
isinstance(rope_scaling_short_factor, list)
|
| 208 |
+
and all(isinstance(x, (int, float)) for x in rope_scaling_short_factor)
|
| 209 |
+
):
|
| 210 |
+
raise ValueError(
|
| 211 |
+
f"`rope_scaling`'s short_factor field must be a list of numbers, got {rope_scaling_short_factor}"
|
| 212 |
+
)
|
| 213 |
+
if not len(rope_scaling_short_factor) == self.hidden_size // self.num_attention_heads // 2:
|
| 214 |
+
raise ValueError(
|
| 215 |
+
f"`rope_scaling`'s short_factor field must have length {self.hidden_size // self.num_attention_heads // 2}, got {len(rope_scaling_short_factor)}"
|
| 216 |
+
)
|
| 217 |
+
if not (
|
| 218 |
+
isinstance(rope_scaling_long_factor, list)
|
| 219 |
+
and all(isinstance(x, (int, float)) for x in rope_scaling_long_factor)
|
| 220 |
+
):
|
| 221 |
+
raise ValueError(
|
| 222 |
+
f"`rope_scaling`'s long_factor field must be a list of numbers, got {rope_scaling_long_factor}"
|
| 223 |
+
)
|
| 224 |
+
if not len(rope_scaling_long_factor) == self.hidden_size // self.num_attention_heads // 2:
|
| 225 |
+
raise ValueError(
|
| 226 |
+
f"`rope_scaling`'s long_factor field must have length {self.hidden_size // self.num_attention_heads // 2}, got {len(rope_scaling_long_factor)}"
|
| 227 |
+
)
|
cpu_and_mobile/cpu-int4-rtn-block-32/phi3-mini-128k-instruct-cpu-int4-rtn-block-32.onnx
CHANGED
|
@@ -1,3 +1,3 @@
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|
| 1 |
version https://git-lfs.github.com/spec/v1
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| 2 |
-
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|
| 3 |
size 52129320
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
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+
oid sha256:099d0991876ab8fb9dbc5f91f63e98b78b4b165a420901586b8e2dfd400f5a98
|
| 3 |
size 52129320
|
cpu_and_mobile/cpu-int4-rtn-block-32/phi3-mini-128k-instruct-cpu-int4-rtn-block-32.onnx.data
CHANGED
|
@@ -1,3 +1,3 @@
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|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
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oid sha256:
|
| 3 |
size 2721288192
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
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+
oid sha256:6509dbd67338d2b5ef3366779655181274b9a9bdce4299a13eefdaf8ad001e32
|
| 3 |
size 2721288192
|
cpu_and_mobile/cpu-int4-rtn-block-32/special_tokens_map.json
CHANGED
|
@@ -1,30 +1,30 @@
|
|
| 1 |
-
{
|
| 2 |
-
"bos_token": {
|
| 3 |
-
"content": "<s>",
|
| 4 |
-
"lstrip": false,
|
| 5 |
-
"normalized": false,
|
| 6 |
-
"rstrip": false,
|
| 7 |
-
"single_word": false
|
| 8 |
-
},
|
| 9 |
-
"eos_token": {
|
| 10 |
-
"content": "<|endoftext|>",
|
| 11 |
-
"lstrip": false,
|
| 12 |
-
"normalized": false,
|
| 13 |
-
"rstrip": false,
|
| 14 |
-
"single_word": false
|
| 15 |
-
},
|
| 16 |
-
"pad_token": {
|
| 17 |
-
"content": "<|endoftext|>",
|
| 18 |
-
"lstrip": false,
|
| 19 |
-
"normalized": false,
|
| 20 |
-
"rstrip": false,
|
| 21 |
-
"single_word": false
|
| 22 |
-
},
|
| 23 |
-
"unk_token": {
|
| 24 |
-
"content": "<unk>",
|
| 25 |
-
"lstrip": false,
|
| 26 |
-
"normalized": false,
|
| 27 |
-
"rstrip": false,
|
| 28 |
-
"single_word": false
|
| 29 |
-
}
|
| 30 |
-
}
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bos_token": {
|
| 3 |
+
"content": "<s>",
|
| 4 |
+
"lstrip": false,
|
| 5 |
+
"normalized": false,
|
| 6 |
+
"rstrip": false,
|
| 7 |
+
"single_word": false
|
| 8 |
+
},
|
| 9 |
+
"eos_token": {
|
| 10 |
+
"content": "<|endoftext|>",
|
| 11 |
+
"lstrip": false,
|
| 12 |
+
"normalized": false,
|
| 13 |
+
"rstrip": false,
|
| 14 |
+
"single_word": false
|
| 15 |
+
},
|
| 16 |
+
"pad_token": {
|
| 17 |
+
"content": "<|endoftext|>",
|
| 18 |
+
"lstrip": false,
|
| 19 |
+
"normalized": false,
|
| 20 |
+
"rstrip": false,
|
| 21 |
+
"single_word": false
|
| 22 |
+
},
|
| 23 |
+
"unk_token": {
|
| 24 |
+
"content": "<unk>",
|
| 25 |
+
"lstrip": false,
|
| 26 |
+
"normalized": false,
|
| 27 |
+
"rstrip": false,
|
| 28 |
+
"single_word": false
|
| 29 |
+
}
|
| 30 |
+
}
|
cpu_and_mobile/cpu-int4-rtn-block-32/tokenizer.json
CHANGED
|
The diff for this file is too large to render.
See raw diff
|
|
|
cpu_and_mobile/cpu-int4-rtn-block-32/tokenizer_config.json
CHANGED
|
@@ -1,130 +1,130 @@
|
|
| 1 |
-
{
|
| 2 |
-
"add_bos_token":
|
| 3 |
-
"add_eos_token": false,
|
| 4 |
-
"added_tokens_decoder": {
|
| 5 |
-
"0": {
|
| 6 |
-
"content": "<unk>",
|
| 7 |
-
"lstrip": false,
|
| 8 |
-
"normalized": false,
|
| 9 |
-
"rstrip": false,
|
| 10 |
-
"single_word": false,
|
| 11 |
-
"special": true
|
| 12 |
-
},
|
| 13 |
-
"1": {
|
| 14 |
-
"content": "<s>",
|
| 15 |
-
"lstrip": false,
|
| 16 |
-
"normalized": false,
|
| 17 |
-
"rstrip": false,
|
| 18 |
-
"single_word": false,
|
| 19 |
-
"special": true
|
| 20 |
-
},
|
| 21 |
-
"2": {
|
| 22 |
-
"content": "</s>",
|
| 23 |
-
"lstrip": false,
|
| 24 |
-
"normalized": false,
|
| 25 |
-
"rstrip": true,
|
| 26 |
-
"single_word": false,
|
| 27 |
-
"special": false
|
| 28 |
-
},
|
| 29 |
-
"32000": {
|
| 30 |
-
"content": "<|endoftext|>",
|
| 31 |
-
"lstrip": false,
|
| 32 |
-
"normalized": false,
|
| 33 |
-
"rstrip": false,
|
| 34 |
-
"single_word": false,
|
| 35 |
-
"special": true
|
| 36 |
-
},
|
| 37 |
-
"32001": {
|
| 38 |
-
"content": "<|assistant|>",
|
| 39 |
-
"lstrip": false,
|
| 40 |
-
"normalized": false,
|
| 41 |
-
"rstrip": true,
|
| 42 |
-
"single_word": false,
|
| 43 |
-
"special": true
|
| 44 |
-
},
|
| 45 |
-
"32002": {
|
| 46 |
-
"content": "<|placeholder1|>",
|
| 47 |
-
"lstrip": false,
|
| 48 |
-
"normalized": false,
|
| 49 |
-
"rstrip": true,
|
| 50 |
-
"single_word": false,
|
| 51 |
-
"special": true
|
| 52 |
-
},
|
| 53 |
-
"32003": {
|
| 54 |
-
"content": "<|placeholder2|>",
|
| 55 |
-
"lstrip": false,
|
| 56 |
-
"normalized": false,
|
| 57 |
-
"rstrip": true,
|
| 58 |
-
"single_word": false,
|
| 59 |
-
"special": true
|
| 60 |
-
},
|
| 61 |
-
"32004": {
|
| 62 |
-
"content": "<|placeholder3|>",
|
| 63 |
-
"lstrip": false,
|
| 64 |
-
"normalized": false,
|
| 65 |
-
"rstrip": true,
|
| 66 |
-
"single_word": false,
|
| 67 |
-
"special": true
|
| 68 |
-
},
|
| 69 |
-
"32005": {
|
| 70 |
-
"content": "<|placeholder4|>",
|
| 71 |
-
"lstrip": false,
|
| 72 |
-
"normalized": false,
|
| 73 |
-
"rstrip": true,
|
| 74 |
-
"single_word": false,
|
| 75 |
-
"special": true
|
| 76 |
-
},
|
| 77 |
-
"32006": {
|
| 78 |
-
"content": "<|system|>",
|
| 79 |
-
"lstrip": false,
|
| 80 |
-
"normalized": false,
|
| 81 |
-
"rstrip": true,
|
| 82 |
-
"single_word": false,
|
| 83 |
-
"special": true
|
| 84 |
-
},
|
| 85 |
-
"32007": {
|
| 86 |
-
"content": "<|end|>",
|
| 87 |
-
"lstrip": false,
|
| 88 |
-
"normalized": false,
|
| 89 |
-
"rstrip": true,
|
| 90 |
-
"single_word": false,
|
| 91 |
-
"special": true
|
| 92 |
-
},
|
| 93 |
-
"32008": {
|
| 94 |
-
"content": "<|placeholder5|>",
|
| 95 |
-
"lstrip": false,
|
| 96 |
-
"normalized": false,
|
| 97 |
-
"rstrip": true,
|
| 98 |
-
"single_word": false,
|
| 99 |
-
"special": true
|
| 100 |
-
},
|
| 101 |
-
"32009": {
|
| 102 |
-
"content": "<|placeholder6|>",
|
| 103 |
-
"lstrip": false,
|
| 104 |
-
"normalized": false,
|
| 105 |
-
"rstrip": true,
|
| 106 |
-
"single_word": false,
|
| 107 |
-
"special": true
|
| 108 |
-
},
|
| 109 |
-
"32010": {
|
| 110 |
-
"content": "<|user|>",
|
| 111 |
-
"lstrip": false,
|
| 112 |
-
"normalized": false,
|
| 113 |
-
"rstrip": true,
|
| 114 |
-
"single_word": false,
|
| 115 |
-
"special": true
|
| 116 |
-
}
|
| 117 |
-
},
|
| 118 |
-
"bos_token": "<s>",
|
| 119 |
-
"chat_template": "{
|
| 120 |
-
"clean_up_tokenization_spaces": false,
|
| 121 |
-
"eos_token": "<|endoftext|>",
|
| 122 |
-
"legacy": false,
|
| 123 |
-
"model_max_length": 131072,
|
| 124 |
-
"pad_token": "<|endoftext|>",
|
| 125 |
-
"padding_side": "left",
|
| 126 |
-
"sp_model_kwargs": {},
|
| 127 |
-
"tokenizer_class": "LlamaTokenizer",
|
| 128 |
-
"unk_token": "<unk>",
|
| 129 |
-
"use_default_system_prompt": false
|
| 130 |
-
}
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_bos_token": false,
|
| 3 |
+
"add_eos_token": false,
|
| 4 |
+
"added_tokens_decoder": {
|
| 5 |
+
"0": {
|
| 6 |
+
"content": "<unk>",
|
| 7 |
+
"lstrip": false,
|
| 8 |
+
"normalized": false,
|
| 9 |
+
"rstrip": false,
|
| 10 |
+
"single_word": false,
|
| 11 |
+
"special": true
|
| 12 |
+
},
|
| 13 |
+
"1": {
|
| 14 |
+
"content": "<s>",
|
| 15 |
+
"lstrip": false,
|
| 16 |
+
"normalized": false,
|
| 17 |
+
"rstrip": false,
|
| 18 |
+
"single_word": false,
|
| 19 |
+
"special": true
|
| 20 |
+
},
|
| 21 |
+
"2": {
|
| 22 |
+
"content": "</s>",
|
| 23 |
+
"lstrip": false,
|
| 24 |
+
"normalized": false,
|
| 25 |
+
"rstrip": true,
|
| 26 |
+
"single_word": false,
|
| 27 |
+
"special": false
|
| 28 |
+
},
|
| 29 |
+
"32000": {
|
| 30 |
+
"content": "<|endoftext|>",
|
| 31 |
+
"lstrip": false,
|
| 32 |
+
"normalized": false,
|
| 33 |
+
"rstrip": false,
|
| 34 |
+
"single_word": false,
|
| 35 |
+
"special": true
|
| 36 |
+
},
|
| 37 |
+
"32001": {
|
| 38 |
+
"content": "<|assistant|>",
|
| 39 |
+
"lstrip": false,
|
| 40 |
+
"normalized": false,
|
| 41 |
+
"rstrip": true,
|
| 42 |
+
"single_word": false,
|
| 43 |
+
"special": true
|
| 44 |
+
},
|
| 45 |
+
"32002": {
|
| 46 |
+
"content": "<|placeholder1|>",
|
| 47 |
+
"lstrip": false,
|
| 48 |
+
"normalized": false,
|
| 49 |
+
"rstrip": true,
|
| 50 |
+
"single_word": false,
|
| 51 |
+
"special": true
|
| 52 |
+
},
|
| 53 |
+
"32003": {
|
| 54 |
+
"content": "<|placeholder2|>",
|
| 55 |
+
"lstrip": false,
|
| 56 |
+
"normalized": false,
|
| 57 |
+
"rstrip": true,
|
| 58 |
+
"single_word": false,
|
| 59 |
+
"special": true
|
| 60 |
+
},
|
| 61 |
+
"32004": {
|
| 62 |
+
"content": "<|placeholder3|>",
|
| 63 |
+
"lstrip": false,
|
| 64 |
+
"normalized": false,
|
| 65 |
+
"rstrip": true,
|
| 66 |
+
"single_word": false,
|
| 67 |
+
"special": true
|
| 68 |
+
},
|
| 69 |
+
"32005": {
|
| 70 |
+
"content": "<|placeholder4|>",
|
| 71 |
+
"lstrip": false,
|
| 72 |
+
"normalized": false,
|
| 73 |
+
"rstrip": true,
|
| 74 |
+
"single_word": false,
|
| 75 |
+
"special": true
|
| 76 |
+
},
|
| 77 |
+
"32006": {
|
| 78 |
+
"content": "<|system|>",
|
| 79 |
+
"lstrip": false,
|
| 80 |
+
"normalized": false,
|
| 81 |
+
"rstrip": true,
|
| 82 |
+
"single_word": false,
|
| 83 |
+
"special": true
|
| 84 |
+
},
|
| 85 |
+
"32007": {
|
| 86 |
+
"content": "<|end|>",
|
| 87 |
+
"lstrip": false,
|
| 88 |
+
"normalized": false,
|
| 89 |
+
"rstrip": true,
|
| 90 |
+
"single_word": false,
|
| 91 |
+
"special": true
|
| 92 |
+
},
|
| 93 |
+
"32008": {
|
| 94 |
+
"content": "<|placeholder5|>",
|
| 95 |
+
"lstrip": false,
|
| 96 |
+
"normalized": false,
|
| 97 |
+
"rstrip": true,
|
| 98 |
+
"single_word": false,
|
| 99 |
+
"special": true
|
| 100 |
+
},
|
| 101 |
+
"32009": {
|
| 102 |
+
"content": "<|placeholder6|>",
|
| 103 |
+
"lstrip": false,
|
| 104 |
+
"normalized": false,
|
| 105 |
+
"rstrip": true,
|
| 106 |
+
"single_word": false,
|
| 107 |
+
"special": true
|
| 108 |
+
},
|
| 109 |
+
"32010": {
|
| 110 |
+
"content": "<|user|>",
|
| 111 |
+
"lstrip": false,
|
| 112 |
+
"normalized": false,
|
| 113 |
+
"rstrip": true,
|
| 114 |
+
"single_word": false,
|
| 115 |
+
"special": true
|
| 116 |
+
}
|
| 117 |
+
},
|
| 118 |
+
"bos_token": "<s>",
|
| 119 |
+
"chat_template": "{% for message in messages %}{% if message['role'] == 'system' %}{{'<|system|>\n' + message['content'] + '<|end|>\n'}}{% elif message['role'] == 'user' %}{{'<|user|>\n' + message['content'] + '<|end|>\n'}}{% elif message['role'] == 'assistant' %}{{'<|assistant|>\n' + message['content'] + '<|end|>\n'}}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|assistant|>\n' }}{% else %}{{ eos_token }}{% endif %}",
|
| 120 |
+
"clean_up_tokenization_spaces": false,
|
| 121 |
+
"eos_token": "<|endoftext|>",
|
| 122 |
+
"legacy": false,
|
| 123 |
+
"model_max_length": 131072,
|
| 124 |
+
"pad_token": "<|endoftext|>",
|
| 125 |
+
"padding_side": "left",
|
| 126 |
+
"sp_model_kwargs": {},
|
| 127 |
+
"tokenizer_class": "LlamaTokenizer",
|
| 128 |
+
"unk_token": "<unk>",
|
| 129 |
+
"use_default_system_prompt": false
|
| 130 |
+
}
|
cuda/cuda-fp16/added_tokens.json
CHANGED
|
@@ -1,13 +1,13 @@
|
|
| 1 |
-
{
|
| 2 |
-
"<|endoftext|>": 32000,
|
| 3 |
-
"<|assistant|>": 32001,
|
| 4 |
-
"<|placeholder1|>": 32002,
|
| 5 |
-
"<|placeholder2|>": 32003,
|
| 6 |
-
"<|placeholder3|>": 32004,
|
| 7 |
-
"<|placeholder4|>": 32005,
|
| 8 |
-
"<|system|>": 32006,
|
| 9 |
-
"<|end|>": 32007,
|
| 10 |
-
"<|placeholder5|>": 32008,
|
| 11 |
-
"<|placeholder6|>": 32009,
|
| 12 |
-
"<|user|>": 32010
|
| 13 |
-
}
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"<|endoftext|>": 32000,
|
| 3 |
+
"<|assistant|>": 32001,
|
| 4 |
+
"<|placeholder1|>": 32002,
|
| 5 |
+
"<|placeholder2|>": 32003,
|
| 6 |
+
"<|placeholder3|>": 32004,
|
| 7 |
+
"<|placeholder4|>": 32005,
|
| 8 |
+
"<|system|>": 32006,
|
| 9 |
+
"<|end|>": 32007,
|
| 10 |
+
"<|placeholder5|>": 32008,
|
| 11 |
+
"<|placeholder6|>": 32009,
|
| 12 |
+
"<|user|>": 32010
|
| 13 |
+
}
|
cuda/cuda-fp16/config.json
CHANGED
|
@@ -1,137 +1,138 @@
|
|
| 1 |
-
{
|
| 2 |
-
"_name_or_path": "
|
| 3 |
-
"architectures": [
|
| 4 |
-
"Phi3ForCausalLM"
|
| 5 |
-
],
|
| 6 |
-
"attention_dropout": 0.0,
|
| 7 |
-
"auto_map": {
|
| 8 |
-
"AutoConfig": "configuration_phi3.Phi3Config",
|
| 9 |
-
"AutoModelForCausalLM": "modeling_phi3.Phi3ForCausalLM"
|
| 10 |
-
},
|
| 11 |
-
"bos_token_id": 1,
|
| 12 |
-
"embd_pdrop": 0.0,
|
| 13 |
-
"eos_token_id": 32000,
|
| 14 |
-
"hidden_act": "silu",
|
| 15 |
-
"hidden_size": 3072,
|
| 16 |
-
"initializer_range": 0.02,
|
| 17 |
-
"intermediate_size": 8192,
|
| 18 |
-
"max_position_embeddings": 131072,
|
| 19 |
-
"model_type": "phi3",
|
| 20 |
-
"num_attention_heads": 32,
|
| 21 |
-
"num_hidden_layers": 32,
|
| 22 |
-
"num_key_value_heads": 32,
|
| 23 |
-
"original_max_position_embeddings": 4096,
|
| 24 |
-
"pad_token_id": 32000,
|
| 25 |
-
"resid_pdrop": 0.0,
|
| 26 |
-
"rms_norm_eps": 1e-05,
|
| 27 |
-
"rope_scaling": {
|
| 28 |
-
"long_factor": [
|
| 29 |
-
1.
|
| 30 |
-
1.
|
| 31 |
-
1.
|
| 32 |
-
1.
|
| 33 |
-
1.
|
| 34 |
-
1.
|
| 35 |
-
|
| 36 |
-
|
| 37 |
-
|
| 38 |
-
|
| 39 |
-
|
| 40 |
-
|
| 41 |
-
|
| 42 |
-
|
| 43 |
-
|
| 44 |
-
|
| 45 |
-
|
| 46 |
-
|
| 47 |
-
|
| 48 |
-
|
| 49 |
-
|
| 50 |
-
|
| 51 |
-
|
| 52 |
-
|
| 53 |
-
|
| 54 |
-
|
| 55 |
-
|
| 56 |
-
|
| 57 |
-
|
| 58 |
-
|
| 59 |
-
|
| 60 |
-
|
| 61 |
-
|
| 62 |
-
|
| 63 |
-
|
| 64 |
-
|
| 65 |
-
|
| 66 |
-
|
| 67 |
-
63.
|
| 68 |
-
|
| 69 |
-
|
| 70 |
-
|
| 71 |
-
|
| 72 |
-
64.
|
| 73 |
-
64.
|
| 74 |
-
64.
|
| 75 |
-
64.
|
| 76 |
-
64.
|
| 77 |
-
],
|
| 78 |
-
"short_factor": [
|
| 79 |
-
1.
|
| 80 |
-
1.
|
| 81 |
-
1.
|
| 82 |
-
1.
|
| 83 |
-
1.
|
| 84 |
-
1.
|
| 85 |
-
1.
|
| 86 |
-
1.
|
| 87 |
-
|
| 88 |
-
|
| 89 |
-
|
| 90 |
-
2.000000000000001,
|
| 91 |
-
2.000000000000001,
|
| 92 |
-
2.000000000000001,
|
| 93 |
-
2.000000000000001,
|
| 94 |
-
2.000000000000001,
|
| 95 |
-
2.000000000000001,
|
| 96 |
-
2.000000000000001,
|
| 97 |
-
2.000000000000001,
|
| 98 |
-
2.000000000000001,
|
| 99 |
-
2.000000000000001,
|
| 100 |
-
2.000000000000001,
|
| 101 |
-
2.000000000000001,
|
| 102 |
-
2.000000000000001,
|
| 103 |
-
2.000000000000001,
|
| 104 |
-
2.
|
| 105 |
-
2.
|
| 106 |
-
2.
|
| 107 |
-
2.
|
| 108 |
-
2.
|
| 109 |
-
2.
|
| 110 |
-
2.
|
| 111 |
-
2.
|
| 112 |
-
2.
|
| 113 |
-
2.
|
| 114 |
-
2.
|
| 115 |
-
2.
|
| 116 |
-
2.
|
| 117 |
-
2.
|
| 118 |
-
2.
|
| 119 |
-
2.
|
| 120 |
-
2.
|
| 121 |
-
2.
|
| 122 |
-
2.
|
| 123 |
-
2.7499999999999982,
|
| 124 |
-
2.
|
| 125 |
-
2.
|
| 126 |
-
|
| 127 |
-
],
|
| 128 |
-
|
| 129 |
-
},
|
| 130 |
-
"rope_theta": 10000.0,
|
| 131 |
-
"sliding_window": 262144,
|
| 132 |
-
"tie_word_embeddings": false,
|
| 133 |
-
"torch_dtype": "bfloat16",
|
| 134 |
-
"transformers_version": "4.
|
| 135 |
-
"use_cache": true,
|
| 136 |
-
"
|
| 137 |
-
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_name_or_path": "Phi-3-mini-128k-instruct",
|
| 3 |
+
"architectures": [
|
| 4 |
+
"Phi3ForCausalLM"
|
| 5 |
+
],
|
| 6 |
+
"attention_dropout": 0.0,
|
| 7 |
+
"auto_map": {
|
| 8 |
+
"AutoConfig": "configuration_phi3.Phi3Config",
|
| 9 |
+
"AutoModelForCausalLM": "modeling_phi3.Phi3ForCausalLM"
|
| 10 |
+
},
|
| 11 |
+
"bos_token_id": 1,
|
| 12 |
+
"embd_pdrop": 0.0,
|
| 13 |
+
"eos_token_id": 32000,
|
| 14 |
+
"hidden_act": "silu",
|
| 15 |
+
"hidden_size": 3072,
|
| 16 |
+
"initializer_range": 0.02,
|
| 17 |
+
"intermediate_size": 8192,
|
| 18 |
+
"max_position_embeddings": 131072,
|
| 19 |
+
"model_type": "phi3",
|
| 20 |
+
"num_attention_heads": 32,
|
| 21 |
+
"num_hidden_layers": 32,
|
| 22 |
+
"num_key_value_heads": 32,
|
| 23 |
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"original_max_position_embeddings": 4096,
|
| 24 |
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"pad_token_id": 32000,
|
| 25 |
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"resid_pdrop": 0.0,
|
| 26 |
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"rms_norm_eps": 1e-05,
|
| 27 |
+
"rope_scaling": {
|
| 28 |
+
"long_factor": [
|
| 29 |
+
1.0700000524520874,
|
| 30 |
+
1.1200000047683716,
|
| 31 |
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1.149999976158142,
|
| 32 |
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1.4199999570846558,
|
| 33 |
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1.5699999332427979,
|
| 34 |
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1.7999999523162842,
|
| 35 |
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2.129999876022339,
|
| 36 |
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2.129999876022339,
|
| 37 |
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3.009999990463257,
|
| 38 |
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5.910000324249268,
|
| 39 |
+
6.950000286102295,
|
| 40 |
+
9.070000648498535,
|
| 41 |
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9.930000305175781,
|
| 42 |
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10.710000038146973,
|
| 43 |
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11.130000114440918,
|
| 44 |
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14.609999656677246,
|
| 45 |
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15.409998893737793,
|
| 46 |
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19.809999465942383,
|
| 47 |
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37.279998779296875,
|
| 48 |
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38.279998779296875,
|
| 49 |
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38.599998474121094,
|
| 50 |
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40.12000274658203,
|
| 51 |
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46.20000457763672,
|
| 52 |
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50.940006256103516,
|
| 53 |
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53.66000747680664,
|
| 54 |
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54.9373893737793,
|
| 55 |
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56.89738845825195,
|
| 56 |
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57.28738784790039,
|
| 57 |
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59.98738479614258,
|
| 58 |
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60.86738586425781,
|
| 59 |
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60.887386322021484,
|
| 60 |
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61.71739196777344,
|
| 61 |
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62.91739273071289,
|
| 62 |
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62.957393646240234,
|
| 63 |
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63.41739273071289,
|
| 64 |
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63.8173942565918,
|
| 65 |
+
63.83739471435547,
|
| 66 |
+
63.897396087646484,
|
| 67 |
+
63.93739700317383,
|
| 68 |
+
64.06739807128906,
|
| 69 |
+
64.11434936523438,
|
| 70 |
+
64.12435150146484,
|
| 71 |
+
64.15435028076172,
|
| 72 |
+
64.19435119628906,
|
| 73 |
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64.24435424804688,
|
| 74 |
+
64.57435607910156,
|
| 75 |
+
64.69000244140625,
|
| 76 |
+
64.76000213623047
|
| 77 |
+
],
|
| 78 |
+
"short_factor": [
|
| 79 |
+
1.1,
|
| 80 |
+
1.1,
|
| 81 |
+
1.1,
|
| 82 |
+
1.3000000000000003,
|
| 83 |
+
1.3500000000000003,
|
| 84 |
+
1.3500000000000003,
|
| 85 |
+
1.4000000000000004,
|
| 86 |
+
1.5500000000000005,
|
| 87 |
+
2.000000000000001,
|
| 88 |
+
2.000000000000001,
|
| 89 |
+
2.000000000000001,
|
| 90 |
+
2.000000000000001,
|
| 91 |
+
2.000000000000001,
|
| 92 |
+
2.000000000000001,
|
| 93 |
+
2.000000000000001,
|
| 94 |
+
2.000000000000001,
|
| 95 |
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2.000000000000001,
|
| 96 |
+
2.000000000000001,
|
| 97 |
+
2.000000000000001,
|
| 98 |
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2.000000000000001,
|
| 99 |
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2.000000000000001,
|
| 100 |
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2.000000000000001,
|
| 101 |
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2.000000000000001,
|
| 102 |
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2.000000000000001,
|
| 103 |
+
2.000000000000001,
|
| 104 |
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2.0500000000000007,
|
| 105 |
+
2.0500000000000007,
|
| 106 |
+
2.0500000000000007,
|
| 107 |
+
2.0500000000000007,
|
| 108 |
+
2.0500000000000007,
|
| 109 |
+
2.0500000000000007,
|
| 110 |
+
2.1000000000000005,
|
| 111 |
+
2.1000000000000005,
|
| 112 |
+
2.1500000000000004,
|
| 113 |
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2.25,
|
| 114 |
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2.25,
|
| 115 |
+
2.25,
|
| 116 |
+
2.25,
|
| 117 |
+
2.25,
|
| 118 |
+
2.3999999999999995,
|
| 119 |
+
2.4499999999999993,
|
| 120 |
+
2.499999999999999,
|
| 121 |
+
2.6999999999999984,
|
| 122 |
+
2.6999999999999984,
|
| 123 |
+
2.7499999999999982,
|
| 124 |
+
2.799999999999998,
|
| 125 |
+
2.8999999999999977,
|
| 126 |
+
3.049999999999997
|
| 127 |
+
],
|
| 128 |
+
"type": "longrope"
|
| 129 |
+
},
|
| 130 |
+
"rope_theta": 10000.0,
|
| 131 |
+
"sliding_window": 262144,
|
| 132 |
+
"tie_word_embeddings": false,
|
| 133 |
+
"torch_dtype": "bfloat16",
|
| 134 |
+
"transformers_version": "4.40.2",
|
| 135 |
+
"use_cache": true,
|
| 136 |
+
"attention_bias": false,
|
| 137 |
+
"vocab_size": 32064
|
| 138 |
+
}
|
cuda/cuda-fp16/configuration_phi3.py
CHANGED
|
@@ -1,213 +1,227 @@
|
|
| 1 |
-
# coding=utf-8
|
| 2 |
-
# Copyright 2024 Microsoft and the HuggingFace Inc. team. All rights reserved.
|
| 3 |
-
#
|
| 4 |
-
# Licensed under the Apache License, Version 2.0 (the "License");
|
| 5 |
-
# you may not use this file except in compliance with the License.
|
| 6 |
-
# You may obtain a copy of the License at
|
| 7 |
-
#
|
| 8 |
-
# http://www.apache.org/licenses/LICENSE-2.0
|
| 9 |
-
#
|
| 10 |
-
# Unless required by applicable law or agreed to in writing, software
|
| 11 |
-
# distributed under the License is distributed on an "AS IS" BASIS,
|
| 12 |
-
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
| 13 |
-
# See the License for the specific language governing permissions and
|
| 14 |
-
# limitations under the License.
|
| 15 |
-
|
| 16 |
-
""" Phi-3 model configuration"""
|
| 17 |
-
|
| 18 |
-
|
| 19 |
-
from transformers.configuration_utils import PretrainedConfig
|
| 20 |
-
from transformers.utils import logging
|
| 21 |
-
|
| 22 |
-
|
| 23 |
-
logger = logging.get_logger(__name__)
|
| 24 |
-
|
| 25 |
-
PHI3_PRETRAINED_CONFIG_ARCHIVE_MAP = {
|
| 26 |
-
"microsoft/Phi-3-mini-4k-instruct": "https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/resolve/main/config.json",
|
| 27 |
-
"microsoft/Phi-3-mini-128k-instruct": "https://huggingface.co/microsoft/Phi-3-mini-128k-instruct/resolve/main/config.json",
|
| 28 |
-
}
|
| 29 |
-
|
| 30 |
-
|
| 31 |
-
class Phi3Config(PretrainedConfig):
|
| 32 |
-
r"""
|
| 33 |
-
This is the configuration class to store the configuration of a [`Phi3Model`]. It is used to instantiate a Phi-3
|
| 34 |
-
model according to the specified arguments, defining the model architecture. Instantiating a configuration with the
|
| 35 |
-
defaults will yield a similar configuration to that of the
|
| 36 |
-
[microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct).
|
| 37 |
-
|
| 38 |
-
Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
|
| 39 |
-
documentation from [`PretrainedConfig`] for more information.
|
| 40 |
-
|
| 41 |
-
Args:
|
| 42 |
-
vocab_size (`int`, *optional*, defaults to 32064):
|
| 43 |
-
Vocabulary size of the Phi-3 model. Defines the number of different tokens that can be represented by the
|
| 44 |
-
`inputs_ids` passed when calling [`Phi3Model`].
|
| 45 |
-
hidden_size (`int`, *optional*, defaults to 3072):
|
| 46 |
-
Dimension of the hidden representations.
|
| 47 |
-
intermediate_size (`int`, *optional*, defaults to 8192):
|
| 48 |
-
Dimension of the MLP representations.
|
| 49 |
-
num_hidden_layers (`int`, *optional*, defaults to 32):
|
| 50 |
-
Number of hidden layers in the Transformer decoder.
|
| 51 |
-
num_attention_heads (`int`, *optional*, defaults to 32):
|
| 52 |
-
Number of attention heads for each attention layer in the Transformer decoder.
|
| 53 |
-
num_key_value_heads (`int`, *optional*):
|
| 54 |
-
This is the number of key_value heads that should be used to implement Grouped Query Attention. If
|
| 55 |
-
`num_key_value_heads=num_attention_heads`, the model will use Multi Head Attention (MHA), if
|
| 56 |
-
`num_key_value_heads=1 the model will use Multi Query Attention (MQA) otherwise GQA is used. When
|
| 57 |
-
converting a multi-head checkpoint to a GQA checkpoint, each group key and value head should be constructed
|
| 58 |
-
by meanpooling all the original heads within that group. For more details checkout [this
|
| 59 |
-
paper](https://arxiv.org/pdf/2305.13245.pdf). If it is not specified, will default to
|
| 60 |
-
`num_attention_heads`.
|
| 61 |
-
resid_pdrop (`float`, *optional*, defaults to 0.0):
|
| 62 |
-
Dropout probability for mlp outputs.
|
| 63 |
-
embd_pdrop (`int`, *optional*, defaults to 0.0):
|
| 64 |
-
The dropout ratio for the embeddings.
|
| 65 |
-
attention_dropout (`float`, *optional*, defaults to 0.0):
|
| 66 |
-
The dropout ratio after computing the attention scores.
|
| 67 |
-
hidden_act (`str` or `function`, *optional*, defaults to `"silu"`):
|
| 68 |
-
The non-linear activation function (function or string) in the decoder.
|
| 69 |
-
max_position_embeddings (`int`, *optional*, defaults to 4096):
|
| 70 |
-
The maximum sequence length that this model might ever be used with.
|
| 71 |
-
original_max_position_embeddings (`int`, *optional*, defaults to 4096):
|
| 72 |
-
The maximum sequence length that this model was trained with. This is used to determine the size of the
|
| 73 |
-
original RoPE embeddings when using long scaling.
|
| 74 |
-
initializer_range (`float`, *optional*, defaults to 0.02):
|
| 75 |
-
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
|
| 76 |
-
rms_norm_eps (`float`, *optional*, defaults to 1e-05):
|
| 77 |
-
The epsilon value used for the RMSNorm.
|
| 78 |
-
use_cache (`bool`, *optional*, defaults to `True`):
|
| 79 |
-
Whether or not the model should return the last key/values attentions (not used by all models). Only
|
| 80 |
-
relevant if `config.is_decoder=True`. Whether to tie weight embeddings or not.
|
| 81 |
-
tie_word_embeddings (`bool`, *optional*, defaults to `False`):
|
| 82 |
-
Whether to tie weight embeddings
|
| 83 |
-
rope_theta (`float`, *optional*, defaults to 10000.0):
|
| 84 |
-
The base period of the RoPE embeddings.
|
| 85 |
-
rope_scaling (`dict`, *optional*):
|
| 86 |
-
The scaling strategy for the RoPE embeddings. If `None`, no scaling is applied. If a dictionary, it must
|
| 87 |
-
contain the following keys: `type`, `short_factor` and `long_factor`. The `type` must be
|
| 88 |
-
the `short_factor` and `long_factor` must be lists of numbers with the same length as the hidden size
|
| 89 |
-
divided by the number of attention heads divided by 2.
|
| 90 |
-
bos_token_id (`int`, *optional*, defaults to 1):
|
| 91 |
-
The id of the "beginning-of-sequence" token.
|
| 92 |
-
eos_token_id (`int`, *optional*, defaults to 32000):
|
| 93 |
-
The id of the "end-of-sequence" token.
|
| 94 |
-
pad_token_id (`int`, *optional*, defaults to 32000):
|
| 95 |
-
The id of the padding token.
|
| 96 |
-
sliding_window (`int`, *optional*):
|
| 97 |
-
Sliding window attention window size. If `None`, no sliding window is applied.
|
| 98 |
-
|
| 99 |
-
Example:
|
| 100 |
-
|
| 101 |
-
```python
|
| 102 |
-
>>> from transformers import Phi3Model, Phi3Config
|
| 103 |
-
|
| 104 |
-
>>> # Initializing a Phi-3 style configuration
|
| 105 |
-
>>> configuration = Phi3Config.from_pretrained("microsoft/Phi-3-mini-4k-instruct")
|
| 106 |
-
|
| 107 |
-
>>> # Initializing a model from the configuration
|
| 108 |
-
>>> model = Phi3Model(configuration)
|
| 109 |
-
|
| 110 |
-
>>> # Accessing the model configuration
|
| 111 |
-
>>> configuration = model.config
|
| 112 |
-
```"""
|
| 113 |
-
|
| 114 |
-
model_type = "phi3"
|
| 115 |
-
keys_to_ignore_at_inference = ["past_key_values"]
|
| 116 |
-
|
| 117 |
-
def __init__(
|
| 118 |
-
self,
|
| 119 |
-
vocab_size=32064,
|
| 120 |
-
hidden_size=3072,
|
| 121 |
-
intermediate_size=8192,
|
| 122 |
-
num_hidden_layers=32,
|
| 123 |
-
num_attention_heads=32,
|
| 124 |
-
num_key_value_heads=None,
|
| 125 |
-
resid_pdrop=0.0,
|
| 126 |
-
embd_pdrop=0.0,
|
| 127 |
-
attention_dropout=0.0,
|
| 128 |
-
hidden_act="silu",
|
| 129 |
-
max_position_embeddings=4096,
|
| 130 |
-
original_max_position_embeddings=4096,
|
| 131 |
-
initializer_range=0.02,
|
| 132 |
-
rms_norm_eps=1e-5,
|
| 133 |
-
use_cache=True,
|
| 134 |
-
tie_word_embeddings=False,
|
| 135 |
-
rope_theta=10000.0,
|
| 136 |
-
rope_scaling=None,
|
| 137 |
-
bos_token_id=1,
|
| 138 |
-
eos_token_id=32000,
|
| 139 |
-
pad_token_id=32000,
|
| 140 |
-
sliding_window=None,
|
| 141 |
-
**kwargs,
|
| 142 |
-
):
|
| 143 |
-
self.vocab_size = vocab_size
|
| 144 |
-
self.hidden_size = hidden_size
|
| 145 |
-
self.intermediate_size = intermediate_size
|
| 146 |
-
self.num_hidden_layers = num_hidden_layers
|
| 147 |
-
self.num_attention_heads = num_attention_heads
|
| 148 |
-
|
| 149 |
-
if num_key_value_heads is None:
|
| 150 |
-
num_key_value_heads = num_attention_heads
|
| 151 |
-
|
| 152 |
-
self.num_key_value_heads = num_key_value_heads
|
| 153 |
-
self.resid_pdrop = resid_pdrop
|
| 154 |
-
self.embd_pdrop = embd_pdrop
|
| 155 |
-
self.attention_dropout = attention_dropout
|
| 156 |
-
self.hidden_act = hidden_act
|
| 157 |
-
self.max_position_embeddings = max_position_embeddings
|
| 158 |
-
self.original_max_position_embeddings = original_max_position_embeddings
|
| 159 |
-
self.initializer_range = initializer_range
|
| 160 |
-
self.rms_norm_eps = rms_norm_eps
|
| 161 |
-
self.use_cache = use_cache
|
| 162 |
-
self.rope_theta = rope_theta
|
| 163 |
-
self.rope_scaling = rope_scaling
|
| 164 |
-
self.
|
| 165 |
-
self.
|
| 166 |
-
|
| 167 |
-
|
| 168 |
-
|
| 169 |
-
|
| 170 |
-
|
| 171 |
-
|
| 172 |
-
|
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-
|
| 174 |
-
|
| 175 |
-
|
| 176 |
-
|
| 177 |
-
|
| 178 |
-
|
| 179 |
-
|
| 180 |
-
|
| 181 |
-
|
| 182 |
-
|
| 183 |
-
|
| 184 |
-
|
| 185 |
-
|
| 186 |
-
|
| 187 |
-
|
| 188 |
-
|
| 189 |
-
|
| 190 |
-
|
| 191 |
-
|
| 192 |
-
|
| 193 |
-
|
| 194 |
-
|
| 195 |
-
|
| 196 |
-
|
| 197 |
-
|
| 198 |
-
|
| 199 |
-
|
| 200 |
-
|
| 201 |
-
|
| 202 |
-
|
| 203 |
-
|
| 204 |
-
|
| 205 |
-
|
| 206 |
-
|
| 207 |
-
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-
|
| 209 |
-
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| 210 |
-
|
| 211 |
-
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| 212 |
-
|
| 213 |
-
|
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|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# coding=utf-8
|
| 2 |
+
# Copyright 2024 Microsoft and the HuggingFace Inc. team. All rights reserved.
|
| 3 |
+
#
|
| 4 |
+
# Licensed under the Apache License, Version 2.0 (the "License");
|
| 5 |
+
# you may not use this file except in compliance with the License.
|
| 6 |
+
# You may obtain a copy of the License at
|
| 7 |
+
#
|
| 8 |
+
# http://www.apache.org/licenses/LICENSE-2.0
|
| 9 |
+
#
|
| 10 |
+
# Unless required by applicable law or agreed to in writing, software
|
| 11 |
+
# distributed under the License is distributed on an "AS IS" BASIS,
|
| 12 |
+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
| 13 |
+
# See the License for the specific language governing permissions and
|
| 14 |
+
# limitations under the License.
|
| 15 |
+
|
| 16 |
+
""" Phi-3 model configuration"""
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
from transformers.configuration_utils import PretrainedConfig
|
| 20 |
+
from transformers.utils import logging
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
logger = logging.get_logger(__name__)
|
| 24 |
+
|
| 25 |
+
PHI3_PRETRAINED_CONFIG_ARCHIVE_MAP = {
|
| 26 |
+
"microsoft/Phi-3-mini-4k-instruct": "https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/resolve/main/config.json",
|
| 27 |
+
"microsoft/Phi-3-mini-128k-instruct": "https://huggingface.co/microsoft/Phi-3-mini-128k-instruct/resolve/main/config.json",
|
| 28 |
+
}
|
| 29 |
+
|
| 30 |
+
|
| 31 |
+
class Phi3Config(PretrainedConfig):
|
| 32 |
+
r"""
|
| 33 |
+
This is the configuration class to store the configuration of a [`Phi3Model`]. It is used to instantiate a Phi-3
|
| 34 |
+
model according to the specified arguments, defining the model architecture. Instantiating a configuration with the
|
| 35 |
+
defaults will yield a similar configuration to that of the
|
| 36 |
+
[microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct).
|
| 37 |
+
|
| 38 |
+
Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
|
| 39 |
+
documentation from [`PretrainedConfig`] for more information.
|
| 40 |
+
|
| 41 |
+
Args:
|
| 42 |
+
vocab_size (`int`, *optional*, defaults to 32064):
|
| 43 |
+
Vocabulary size of the Phi-3 model. Defines the number of different tokens that can be represented by the
|
| 44 |
+
`inputs_ids` passed when calling [`Phi3Model`].
|
| 45 |
+
hidden_size (`int`, *optional*, defaults to 3072):
|
| 46 |
+
Dimension of the hidden representations.
|
| 47 |
+
intermediate_size (`int`, *optional*, defaults to 8192):
|
| 48 |
+
Dimension of the MLP representations.
|
| 49 |
+
num_hidden_layers (`int`, *optional*, defaults to 32):
|
| 50 |
+
Number of hidden layers in the Transformer decoder.
|
| 51 |
+
num_attention_heads (`int`, *optional*, defaults to 32):
|
| 52 |
+
Number of attention heads for each attention layer in the Transformer decoder.
|
| 53 |
+
num_key_value_heads (`int`, *optional*):
|
| 54 |
+
This is the number of key_value heads that should be used to implement Grouped Query Attention. If
|
| 55 |
+
`num_key_value_heads=num_attention_heads`, the model will use Multi Head Attention (MHA), if
|
| 56 |
+
`num_key_value_heads=1 the model will use Multi Query Attention (MQA) otherwise GQA is used. When
|
| 57 |
+
converting a multi-head checkpoint to a GQA checkpoint, each group key and value head should be constructed
|
| 58 |
+
by meanpooling all the original heads within that group. For more details checkout [this
|
| 59 |
+
paper](https://arxiv.org/pdf/2305.13245.pdf). If it is not specified, will default to
|
| 60 |
+
`num_attention_heads`.
|
| 61 |
+
resid_pdrop (`float`, *optional*, defaults to 0.0):
|
| 62 |
+
Dropout probability for mlp outputs.
|
| 63 |
+
embd_pdrop (`int`, *optional*, defaults to 0.0):
|
| 64 |
+
The dropout ratio for the embeddings.
|
| 65 |
+
attention_dropout (`float`, *optional*, defaults to 0.0):
|
| 66 |
+
The dropout ratio after computing the attention scores.
|
| 67 |
+
hidden_act (`str` or `function`, *optional*, defaults to `"silu"`):
|
| 68 |
+
The non-linear activation function (function or string) in the decoder.
|
| 69 |
+
max_position_embeddings (`int`, *optional*, defaults to 4096):
|
| 70 |
+
The maximum sequence length that this model might ever be used with.
|
| 71 |
+
original_max_position_embeddings (`int`, *optional*, defaults to 4096):
|
| 72 |
+
The maximum sequence length that this model was trained with. This is used to determine the size of the
|
| 73 |
+
original RoPE embeddings when using long scaling.
|
| 74 |
+
initializer_range (`float`, *optional*, defaults to 0.02):
|
| 75 |
+
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
|
| 76 |
+
rms_norm_eps (`float`, *optional*, defaults to 1e-05):
|
| 77 |
+
The epsilon value used for the RMSNorm.
|
| 78 |
+
use_cache (`bool`, *optional*, defaults to `True`):
|
| 79 |
+
Whether or not the model should return the last key/values attentions (not used by all models). Only
|
| 80 |
+
relevant if `config.is_decoder=True`. Whether to tie weight embeddings or not.
|
| 81 |
+
tie_word_embeddings (`bool`, *optional*, defaults to `False`):
|
| 82 |
+
Whether to tie weight embeddings
|
| 83 |
+
rope_theta (`float`, *optional*, defaults to 10000.0):
|
| 84 |
+
The base period of the RoPE embeddings.
|
| 85 |
+
rope_scaling (`dict`, *optional*):
|
| 86 |
+
The scaling strategy for the RoPE embeddings. If `None`, no scaling is applied. If a dictionary, it must
|
| 87 |
+
contain the following keys: `type`, `short_factor` and `long_factor`. The `type` must be `longrope` and
|
| 88 |
+
the `short_factor` and `long_factor` must be lists of numbers with the same length as the hidden size
|
| 89 |
+
divided by the number of attention heads divided by 2.
|
| 90 |
+
bos_token_id (`int`, *optional*, defaults to 1):
|
| 91 |
+
The id of the "beginning-of-sequence" token.
|
| 92 |
+
eos_token_id (`int`, *optional*, defaults to 32000):
|
| 93 |
+
The id of the "end-of-sequence" token.
|
| 94 |
+
pad_token_id (`int`, *optional*, defaults to 32000):
|
| 95 |
+
The id of the padding token.
|
| 96 |
+
sliding_window (`int`, *optional*):
|
| 97 |
+
Sliding window attention window size. If `None`, no sliding window is applied.
|
| 98 |
+
|
| 99 |
+
Example:
|
| 100 |
+
|
| 101 |
+
```python
|
| 102 |
+
>>> from transformers import Phi3Model, Phi3Config
|
| 103 |
+
|
| 104 |
+
>>> # Initializing a Phi-3 style configuration
|
| 105 |
+
>>> configuration = Phi3Config.from_pretrained("microsoft/Phi-3-mini-4k-instruct")
|
| 106 |
+
|
| 107 |
+
>>> # Initializing a model from the configuration
|
| 108 |
+
>>> model = Phi3Model(configuration)
|
| 109 |
+
|
| 110 |
+
>>> # Accessing the model configuration
|
| 111 |
+
>>> configuration = model.config
|
| 112 |
+
```"""
|
| 113 |
+
|
| 114 |
+
model_type = "phi3"
|
| 115 |
+
keys_to_ignore_at_inference = ["past_key_values"]
|
| 116 |
+
|
| 117 |
+
def __init__(
|
| 118 |
+
self,
|
| 119 |
+
vocab_size=32064,
|
| 120 |
+
hidden_size=3072,
|
| 121 |
+
intermediate_size=8192,
|
| 122 |
+
num_hidden_layers=32,
|
| 123 |
+
num_attention_heads=32,
|
| 124 |
+
num_key_value_heads=None,
|
| 125 |
+
resid_pdrop=0.0,
|
| 126 |
+
embd_pdrop=0.0,
|
| 127 |
+
attention_dropout=0.0,
|
| 128 |
+
hidden_act="silu",
|
| 129 |
+
max_position_embeddings=4096,
|
| 130 |
+
original_max_position_embeddings=4096,
|
| 131 |
+
initializer_range=0.02,
|
| 132 |
+
rms_norm_eps=1e-5,
|
| 133 |
+
use_cache=True,
|
| 134 |
+
tie_word_embeddings=False,
|
| 135 |
+
rope_theta=10000.0,
|
| 136 |
+
rope_scaling=None,
|
| 137 |
+
bos_token_id=1,
|
| 138 |
+
eos_token_id=32000,
|
| 139 |
+
pad_token_id=32000,
|
| 140 |
+
sliding_window=None,
|
| 141 |
+
**kwargs,
|
| 142 |
+
):
|
| 143 |
+
self.vocab_size = vocab_size
|
| 144 |
+
self.hidden_size = hidden_size
|
| 145 |
+
self.intermediate_size = intermediate_size
|
| 146 |
+
self.num_hidden_layers = num_hidden_layers
|
| 147 |
+
self.num_attention_heads = num_attention_heads
|
| 148 |
+
|
| 149 |
+
if num_key_value_heads is None:
|
| 150 |
+
num_key_value_heads = num_attention_heads
|
| 151 |
+
|
| 152 |
+
self.num_key_value_heads = num_key_value_heads
|
| 153 |
+
self.resid_pdrop = resid_pdrop
|
| 154 |
+
self.embd_pdrop = embd_pdrop
|
| 155 |
+
self.attention_dropout = attention_dropout
|
| 156 |
+
self.hidden_act = hidden_act
|
| 157 |
+
self.max_position_embeddings = max_position_embeddings
|
| 158 |
+
self.original_max_position_embeddings = original_max_position_embeddings
|
| 159 |
+
self.initializer_range = initializer_range
|
| 160 |
+
self.rms_norm_eps = rms_norm_eps
|
| 161 |
+
self.use_cache = use_cache
|
| 162 |
+
self.rope_theta = rope_theta
|
| 163 |
+
self.rope_scaling = rope_scaling
|
| 164 |
+
self._rope_scaling_adjustment()
|
| 165 |
+
self._rope_scaling_validation()
|
| 166 |
+
self.sliding_window = sliding_window
|
| 167 |
+
|
| 168 |
+
super().__init__(
|
| 169 |
+
bos_token_id=bos_token_id,
|
| 170 |
+
eos_token_id=eos_token_id,
|
| 171 |
+
pad_token_id=pad_token_id,
|
| 172 |
+
tie_word_embeddings=tie_word_embeddings,
|
| 173 |
+
**kwargs,
|
| 174 |
+
)
|
| 175 |
+
|
| 176 |
+
def _rope_scaling_adjustment(self):
|
| 177 |
+
"""
|
| 178 |
+
Adjust the `type` of the `rope_scaling` configuration for backward compatibility.
|
| 179 |
+
"""
|
| 180 |
+
if self.rope_scaling is None:
|
| 181 |
+
return
|
| 182 |
+
|
| 183 |
+
rope_scaling_type = self.rope_scaling.get("type", None)
|
| 184 |
+
|
| 185 |
+
# For backward compatibility if previous version used "su" or "yarn"
|
| 186 |
+
if rope_scaling_type is not None and rope_scaling_type in ["su", "yarn"]:
|
| 187 |
+
self.rope_scaling["type"] = "longrope"
|
| 188 |
+
|
| 189 |
+
def _rope_scaling_validation(self):
|
| 190 |
+
"""
|
| 191 |
+
Validate the `rope_scaling` configuration.
|
| 192 |
+
"""
|
| 193 |
+
if self.rope_scaling is None:
|
| 194 |
+
return
|
| 195 |
+
|
| 196 |
+
if not isinstance(self.rope_scaling, dict) or len(self.rope_scaling) != 3:
|
| 197 |
+
raise ValueError(
|
| 198 |
+
"`rope_scaling` must be a dictionary with three fields, `type`, `short_factor` and `long_factor`, "
|
| 199 |
+
f"got {self.rope_scaling}"
|
| 200 |
+
)
|
| 201 |
+
rope_scaling_type = self.rope_scaling.get("type", None)
|
| 202 |
+
rope_scaling_short_factor = self.rope_scaling.get("short_factor", None)
|
| 203 |
+
rope_scaling_long_factor = self.rope_scaling.get("long_factor", None)
|
| 204 |
+
if rope_scaling_type is None or rope_scaling_type not in ["longrope"]:
|
| 205 |
+
raise ValueError(f"`rope_scaling`'s type field must be one of ['longrope'], got {rope_scaling_type}")
|
| 206 |
+
if not (
|
| 207 |
+
isinstance(rope_scaling_short_factor, list)
|
| 208 |
+
and all(isinstance(x, (int, float)) for x in rope_scaling_short_factor)
|
| 209 |
+
):
|
| 210 |
+
raise ValueError(
|
| 211 |
+
f"`rope_scaling`'s short_factor field must be a list of numbers, got {rope_scaling_short_factor}"
|
| 212 |
+
)
|
| 213 |
+
if not len(rope_scaling_short_factor) == self.hidden_size // self.num_attention_heads // 2:
|
| 214 |
+
raise ValueError(
|
| 215 |
+
f"`rope_scaling`'s short_factor field must have length {self.hidden_size // self.num_attention_heads // 2}, got {len(rope_scaling_short_factor)}"
|
| 216 |
+
)
|
| 217 |
+
if not (
|
| 218 |
+
isinstance(rope_scaling_long_factor, list)
|
| 219 |
+
and all(isinstance(x, (int, float)) for x in rope_scaling_long_factor)
|
| 220 |
+
):
|
| 221 |
+
raise ValueError(
|
| 222 |
+
f"`rope_scaling`'s long_factor field must be a list of numbers, got {rope_scaling_long_factor}"
|
| 223 |
+
)
|
| 224 |
+
if not len(rope_scaling_long_factor) == self.hidden_size // self.num_attention_heads // 2:
|
| 225 |
+
raise ValueError(
|
| 226 |
+
f"`rope_scaling`'s long_factor field must have length {self.hidden_size // self.num_attention_heads // 2}, got {len(rope_scaling_long_factor)}"
|
| 227 |
+
)
|
cuda/cuda-fp16/genai_config.json
CHANGED
|
@@ -56,4 +56,4 @@
|
|
| 56 |
"top_k": 1,
|
| 57 |
"top_p": 1.0
|
| 58 |
}
|
| 59 |
-
}
|
|
|
|
| 56 |
"top_k": 1,
|
| 57 |
"top_p": 1.0
|
| 58 |
}
|
| 59 |
+
}
|
cuda/cuda-fp16/phi3-mini-128k-instruct-cuda-fp16.onnx
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 26125048
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:4dbca73cb8028d23334505480149ad9c2083ce88d4dafb340e336e1886f3832f
|
| 3 |
size 26125048
|
cuda/cuda-fp16/phi3-mini-128k-instruct-cuda-fp16.onnx.data
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 7642159104
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:48f1f9dc4029c5c2b1a2ad548e364c8a942726fa5f88bcfa7f7075d722036331
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| 3 |
size 7642159104
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cuda/cuda-fp16/special_tokens_map.json
CHANGED
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@@ -1,30 +1,30 @@
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| 1 |
-
{
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| 2 |
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| 3 |
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| 4 |
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| 5 |
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| 6 |
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| 7 |
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| 8 |
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| 9 |
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| 10 |
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| 11 |
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| 12 |
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| 13 |
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| 14 |
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| 15 |
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| 16 |
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| 17 |
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| 18 |
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| 19 |
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| 22 |
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| 23 |
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| 24 |
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| 25 |
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| 27 |
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| 28 |
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| 29 |
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| 1 |
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{
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| 2 |
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| 3 |
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| 4 |
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| 7 |
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|
| 8 |
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| 9 |
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| 10 |
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| 30 |
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}
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cuda/cuda-fp16/tokenizer.json
CHANGED
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cuda/cuda-fp16/tokenizer_config.json
CHANGED
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@@ -1,130 +1,130 @@
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| 1 |
-
{
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| 2 |
-
"add_bos_token":
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| 3 |
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|
| 4 |
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| 5 |
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"0": {
|
| 6 |
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|
| 7 |
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|
| 8 |
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|
| 9 |
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"rstrip": false,
|
| 10 |
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"single_word": false,
|
| 11 |
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"special": true
|
| 12 |
-
},
|
| 13 |
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"1": {
|
| 14 |
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|
| 15 |
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|
| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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|
| 20 |
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|
| 21 |
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"2": {
|
| 22 |
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|
| 23 |
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|
| 24 |
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|
| 25 |
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|
| 26 |
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|
| 27 |
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|
| 28 |
-
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|
| 29 |
-
"32000": {
|
| 30 |
-
"content": "<|endoftext|>",
|
| 31 |
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|
| 32 |
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|
| 33 |
-
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|
| 34 |
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|
| 35 |
-
"special": true
|
| 36 |
-
},
|
| 37 |
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"32001": {
|
| 38 |
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"content": "<|assistant|>",
|
| 39 |
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|
| 40 |
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|
| 41 |
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|
| 42 |
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|
| 43 |
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|
| 44 |
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|
| 45 |
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|
| 46 |
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|
| 47 |
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|
| 48 |
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|
| 49 |
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|
| 50 |
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|
| 51 |
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|
| 52 |
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|
| 53 |
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|
| 54 |
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|
| 55 |
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| 56 |
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|
| 57 |
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|
| 58 |
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|
| 59 |
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|
| 60 |
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|
| 61 |
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|
| 62 |
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|
| 63 |
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|
| 64 |
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|
| 65 |
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|
| 66 |
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|
| 67 |
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|
| 68 |
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|
| 69 |
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|
| 70 |
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"content": "<|placeholder4|>",
|
| 71 |
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|
| 72 |
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|
| 73 |
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|
| 74 |
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|
| 75 |
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|
| 76 |
-
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|
| 77 |
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|
| 78 |
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|
| 79 |
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|
| 80 |
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|
| 81 |
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|
| 82 |
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|
| 83 |
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|
| 84 |
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|
| 85 |
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|
| 86 |
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|
| 87 |
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|
| 88 |
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|
| 89 |
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|
| 90 |
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|
| 91 |
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|
| 92 |
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|
| 93 |
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|
| 94 |
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|
| 95 |
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|
| 96 |
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| 97 |
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|
| 98 |
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|
| 99 |
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|
| 100 |
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|
| 101 |
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|
| 102 |
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| 103 |
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| 104 |
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|
| 105 |
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|
| 106 |
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|
| 107 |
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|
| 108 |
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|
| 109 |
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|
| 110 |
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|
| 111 |
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|
| 112 |
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|
| 113 |
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|
| 114 |
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|
| 115 |
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|
| 116 |
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|
| 117 |
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|
| 118 |
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|
| 119 |
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|
| 120 |
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|
| 121 |
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| 122 |
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|
| 123 |
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|
| 124 |
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| 125 |
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|
| 126 |
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|
| 127 |
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|
| 128 |
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|
| 129 |
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|
| 130 |
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|
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|
| 1 |
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{
|
| 2 |
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| 4 |
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| 5 |
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| 6 |
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| 7 |
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| 8 |
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|
| 11 |
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| 12 |
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| 14 |
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|
| 15 |
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|
| 19 |
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|
| 20 |
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|
| 21 |
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"2": {
|
| 22 |
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| 23 |
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|
| 24 |
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|
| 25 |
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|
| 26 |
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|
| 27 |
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|
| 28 |
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|
| 29 |
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"32000": {
|
| 30 |
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| 31 |
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| 32 |
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|
| 33 |
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|
| 34 |
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|
| 35 |
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|
| 36 |
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|
| 37 |
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|
| 38 |
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| 39 |
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|
| 40 |
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|
| 41 |
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|
| 42 |
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|
| 43 |
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|
| 44 |
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| 45 |
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| 46 |
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| 47 |
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| 48 |
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| 49 |
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|
| 50 |
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|
| 51 |
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|
| 52 |
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| 53 |
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|
| 54 |
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| 55 |
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| 56 |
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|
| 57 |
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|
| 58 |
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|
| 59 |
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|
| 60 |
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|
| 61 |
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|
| 62 |
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|
| 63 |
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|
| 64 |
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|
| 65 |
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"rstrip": true,
|
| 66 |
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"single_word": false,
|
| 67 |
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"special": true
|
| 68 |
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},
|
| 69 |
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"32005": {
|
| 70 |
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"content": "<|placeholder4|>",
|
| 71 |
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"lstrip": false,
|
| 72 |
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"normalized": false,
|
| 73 |
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"rstrip": true,
|
| 74 |
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"single_word": false,
|
| 75 |
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"special": true
|
| 76 |
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},
|
| 77 |
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"32006": {
|
| 78 |
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"content": "<|system|>",
|
| 79 |
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"lstrip": false,
|
| 80 |
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"normalized": false,
|
| 81 |
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"rstrip": true,
|
| 82 |
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"single_word": false,
|
| 83 |
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"special": true
|
| 84 |
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},
|
| 85 |
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"32007": {
|
| 86 |
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"content": "<|end|>",
|
| 87 |
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"lstrip": false,
|
| 88 |
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"normalized": false,
|
| 89 |
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"rstrip": true,
|
| 90 |
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"single_word": false,
|
| 91 |
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"special": true
|
| 92 |
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},
|
| 93 |
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"32008": {
|
| 94 |
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"content": "<|placeholder5|>",
|
| 95 |
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"lstrip": false,
|
| 96 |
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"normalized": false,
|
| 97 |
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"rstrip": true,
|
| 98 |
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"single_word": false,
|
| 99 |
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"special": true
|
| 100 |
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},
|
| 101 |
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"32009": {
|
| 102 |
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"content": "<|placeholder6|>",
|
| 103 |
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"lstrip": false,
|
| 104 |
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"normalized": false,
|
| 105 |
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"rstrip": true,
|
| 106 |
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"single_word": false,
|
| 107 |
+
"special": true
|
| 108 |
+
},
|
| 109 |
+
"32010": {
|
| 110 |
+
"content": "<|user|>",
|
| 111 |
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"lstrip": false,
|
| 112 |
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"normalized": false,
|
| 113 |
+
"rstrip": true,
|
| 114 |
+
"single_word": false,
|
| 115 |
+
"special": true
|
| 116 |
+
}
|
| 117 |
+
},
|
| 118 |
+
"bos_token": "<s>",
|
| 119 |
+
"chat_template": "{% for message in messages %}{% if message['role'] == 'system' %}{{'<|system|>\n' + message['content'] + '<|end|>\n'}}{% elif message['role'] == 'user' %}{{'<|user|>\n' + message['content'] + '<|end|>\n'}}{% elif message['role'] == 'assistant' %}{{'<|assistant|>\n' + message['content'] + '<|end|>\n'}}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|assistant|>\n' }}{% else %}{{ eos_token }}{% endif %}",
|
| 120 |
+
"clean_up_tokenization_spaces": false,
|
| 121 |
+
"eos_token": "<|endoftext|>",
|
| 122 |
+
"legacy": false,
|
| 123 |
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"model_max_length": 131072,
|
| 124 |
+
"pad_token": "<|endoftext|>",
|
| 125 |
+
"padding_side": "left",
|
| 126 |
+
"sp_model_kwargs": {},
|
| 127 |
+
"tokenizer_class": "LlamaTokenizer",
|
| 128 |
+
"unk_token": "<unk>",
|
| 129 |
+
"use_default_system_prompt": false
|
| 130 |
+
}
|
cuda/cuda-int4-awq-block-32/added_tokens.json
ADDED
|
@@ -0,0 +1,13 @@
|
|
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|
| 1 |
+
{
|
| 2 |
+
"<|endoftext|>": 32000,
|
| 3 |
+
"<|assistant|>": 32001,
|
| 4 |
+
"<|placeholder1|>": 32002,
|
| 5 |
+
"<|placeholder2|>": 32003,
|
| 6 |
+
"<|placeholder3|>": 32004,
|
| 7 |
+
"<|placeholder4|>": 32005,
|
| 8 |
+
"<|system|>": 32006,
|
| 9 |
+
"<|end|>": 32007,
|
| 10 |
+
"<|placeholder5|>": 32008,
|
| 11 |
+
"<|placeholder6|>": 32009,
|
| 12 |
+
"<|user|>": 32010
|
| 13 |
+
}
|
cuda/cuda-int4-awq-block-32/config.json
ADDED
|
@@ -0,0 +1,138 @@
|
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|
| 1 |
+
{
|
| 2 |
+
"_name_or_path": "Phi-3-mini-128k-instruct",
|
| 3 |
+
"architectures": [
|
| 4 |
+
"Phi3ForCausalLM"
|
| 5 |
+
],
|
| 6 |
+
"attention_dropout": 0.0,
|
| 7 |
+
"auto_map": {
|
| 8 |
+
"AutoConfig": "configuration_phi3.Phi3Config",
|
| 9 |
+
"AutoModelForCausalLM": "modeling_phi3.Phi3ForCausalLM"
|
| 10 |
+
},
|
| 11 |
+
"bos_token_id": 1,
|
| 12 |
+
"embd_pdrop": 0.0,
|
| 13 |
+
"eos_token_id": 32000,
|
| 14 |
+
"hidden_act": "silu",
|
| 15 |
+
"hidden_size": 3072,
|
| 16 |
+
"initializer_range": 0.02,
|
| 17 |
+
"intermediate_size": 8192,
|
| 18 |
+
"max_position_embeddings": 131072,
|
| 19 |
+
"model_type": "phi3",
|
| 20 |
+
"num_attention_heads": 32,
|
| 21 |
+
"num_hidden_layers": 32,
|
| 22 |
+
"num_key_value_heads": 32,
|
| 23 |
+
"original_max_position_embeddings": 4096,
|
| 24 |
+
"pad_token_id": 32000,
|
| 25 |
+
"resid_pdrop": 0.0,
|
| 26 |
+
"rms_norm_eps": 1e-05,
|
| 27 |
+
"rope_scaling": {
|
| 28 |
+
"long_factor": [
|
| 29 |
+
1.0700000524520874,
|
| 30 |
+
1.1200000047683716,
|
| 31 |
+
1.149999976158142,
|
| 32 |
+
1.4199999570846558,
|
| 33 |
+
1.5699999332427979,
|
| 34 |
+
1.7999999523162842,
|
| 35 |
+
2.129999876022339,
|
| 36 |
+
2.129999876022339,
|
| 37 |
+
3.009999990463257,
|
| 38 |
+
5.910000324249268,
|
| 39 |
+
6.950000286102295,
|
| 40 |
+
9.070000648498535,
|
| 41 |
+
9.930000305175781,
|
| 42 |
+
10.710000038146973,
|
| 43 |
+
11.130000114440918,
|
| 44 |
+
14.609999656677246,
|
| 45 |
+
15.409998893737793,
|
| 46 |
+
19.809999465942383,
|
| 47 |
+
37.279998779296875,
|
| 48 |
+
38.279998779296875,
|
| 49 |
+
38.599998474121094,
|
| 50 |
+
40.12000274658203,
|
| 51 |
+
46.20000457763672,
|
| 52 |
+
50.940006256103516,
|
| 53 |
+
53.66000747680664,
|
| 54 |
+
54.9373893737793,
|
| 55 |
+
56.89738845825195,
|
| 56 |
+
57.28738784790039,
|
| 57 |
+
59.98738479614258,
|
| 58 |
+
60.86738586425781,
|
| 59 |
+
60.887386322021484,
|
| 60 |
+
61.71739196777344,
|
| 61 |
+
62.91739273071289,
|
| 62 |
+
62.957393646240234,
|
| 63 |
+
63.41739273071289,
|
| 64 |
+
63.8173942565918,
|
| 65 |
+
63.83739471435547,
|
| 66 |
+
63.897396087646484,
|
| 67 |
+
63.93739700317383,
|
| 68 |
+
64.06739807128906,
|
| 69 |
+
64.11434936523438,
|
| 70 |
+
64.12435150146484,
|
| 71 |
+
64.15435028076172,
|
| 72 |
+
64.19435119628906,
|
| 73 |
+
64.24435424804688,
|
| 74 |
+
64.57435607910156,
|
| 75 |
+
64.69000244140625,
|
| 76 |
+
64.76000213623047
|
| 77 |
+
],
|
| 78 |
+
"short_factor": [
|
| 79 |
+
1.1,
|
| 80 |
+
1.1,
|
| 81 |
+
1.1,
|
| 82 |
+
1.3000000000000003,
|
| 83 |
+
1.3500000000000003,
|
| 84 |
+
1.3500000000000003,
|
| 85 |
+
1.4000000000000004,
|
| 86 |
+
1.5500000000000005,
|
| 87 |
+
2.000000000000001,
|
| 88 |
+
2.000000000000001,
|
| 89 |
+
2.000000000000001,
|
| 90 |
+
2.000000000000001,
|
| 91 |
+
2.000000000000001,
|
| 92 |
+
2.000000000000001,
|
| 93 |
+
2.000000000000001,
|
| 94 |
+
2.000000000000001,
|
| 95 |
+
2.000000000000001,
|
| 96 |
+
2.000000000000001,
|
| 97 |
+
2.000000000000001,
|
| 98 |
+
2.000000000000001,
|
| 99 |
+
2.000000000000001,
|
| 100 |
+
2.000000000000001,
|
| 101 |
+
2.000000000000001,
|
| 102 |
+
2.000000000000001,
|
| 103 |
+
2.000000000000001,
|
| 104 |
+
2.0500000000000007,
|
| 105 |
+
2.0500000000000007,
|
| 106 |
+
2.0500000000000007,
|
| 107 |
+
2.0500000000000007,
|
| 108 |
+
2.0500000000000007,
|
| 109 |
+
2.0500000000000007,
|
| 110 |
+
2.1000000000000005,
|
| 111 |
+
2.1000000000000005,
|
| 112 |
+
2.1500000000000004,
|
| 113 |
+
2.25,
|
| 114 |
+
2.25,
|
| 115 |
+
2.25,
|
| 116 |
+
2.25,
|
| 117 |
+
2.25,
|
| 118 |
+
2.3999999999999995,
|
| 119 |
+
2.4499999999999993,
|
| 120 |
+
2.499999999999999,
|
| 121 |
+
2.6999999999999984,
|
| 122 |
+
2.6999999999999984,
|
| 123 |
+
2.7499999999999982,
|
| 124 |
+
2.799999999999998,
|
| 125 |
+
2.8999999999999977,
|
| 126 |
+
3.049999999999997
|
| 127 |
+
],
|
| 128 |
+
"type": "longrope"
|
| 129 |
+
},
|
| 130 |
+
"rope_theta": 10000.0,
|
| 131 |
+
"sliding_window": 262144,
|
| 132 |
+
"tie_word_embeddings": false,
|
| 133 |
+
"torch_dtype": "bfloat16",
|
| 134 |
+
"transformers_version": "4.40.2",
|
| 135 |
+
"use_cache": true,
|
| 136 |
+
"attention_bias": false,
|
| 137 |
+
"vocab_size": 32064
|
| 138 |
+
}
|
cuda/cuda-int4-awq-block-32/configuration_phi3.py
ADDED
|
@@ -0,0 +1,227 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# coding=utf-8
|
| 2 |
+
# Copyright 2024 Microsoft and the HuggingFace Inc. team. All rights reserved.
|
| 3 |
+
#
|
| 4 |
+
# Licensed under the Apache License, Version 2.0 (the "License");
|
| 5 |
+
# you may not use this file except in compliance with the License.
|
| 6 |
+
# You may obtain a copy of the License at
|
| 7 |
+
#
|
| 8 |
+
# http://www.apache.org/licenses/LICENSE-2.0
|
| 9 |
+
#
|
| 10 |
+
# Unless required by applicable law or agreed to in writing, software
|
| 11 |
+
# distributed under the License is distributed on an "AS IS" BASIS,
|
| 12 |
+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
| 13 |
+
# See the License for the specific language governing permissions and
|
| 14 |
+
# limitations under the License.
|
| 15 |
+
|
| 16 |
+
""" Phi-3 model configuration"""
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
from transformers.configuration_utils import PretrainedConfig
|
| 20 |
+
from transformers.utils import logging
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
logger = logging.get_logger(__name__)
|
| 24 |
+
|
| 25 |
+
PHI3_PRETRAINED_CONFIG_ARCHIVE_MAP = {
|
| 26 |
+
"microsoft/Phi-3-mini-4k-instruct": "https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/resolve/main/config.json",
|
| 27 |
+
"microsoft/Phi-3-mini-128k-instruct": "https://huggingface.co/microsoft/Phi-3-mini-128k-instruct/resolve/main/config.json",
|
| 28 |
+
}
|
| 29 |
+
|
| 30 |
+
|
| 31 |
+
class Phi3Config(PretrainedConfig):
|
| 32 |
+
r"""
|
| 33 |
+
This is the configuration class to store the configuration of a [`Phi3Model`]. It is used to instantiate a Phi-3
|
| 34 |
+
model according to the specified arguments, defining the model architecture. Instantiating a configuration with the
|
| 35 |
+
defaults will yield a similar configuration to that of the
|
| 36 |
+
[microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct).
|
| 37 |
+
|
| 38 |
+
Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
|
| 39 |
+
documentation from [`PretrainedConfig`] for more information.
|
| 40 |
+
|
| 41 |
+
Args:
|
| 42 |
+
vocab_size (`int`, *optional*, defaults to 32064):
|
| 43 |
+
Vocabulary size of the Phi-3 model. Defines the number of different tokens that can be represented by the
|
| 44 |
+
`inputs_ids` passed when calling [`Phi3Model`].
|
| 45 |
+
hidden_size (`int`, *optional*, defaults to 3072):
|
| 46 |
+
Dimension of the hidden representations.
|
| 47 |
+
intermediate_size (`int`, *optional*, defaults to 8192):
|
| 48 |
+
Dimension of the MLP representations.
|
| 49 |
+
num_hidden_layers (`int`, *optional*, defaults to 32):
|
| 50 |
+
Number of hidden layers in the Transformer decoder.
|
| 51 |
+
num_attention_heads (`int`, *optional*, defaults to 32):
|
| 52 |
+
Number of attention heads for each attention layer in the Transformer decoder.
|
| 53 |
+
num_key_value_heads (`int`, *optional*):
|
| 54 |
+
This is the number of key_value heads that should be used to implement Grouped Query Attention. If
|
| 55 |
+
`num_key_value_heads=num_attention_heads`, the model will use Multi Head Attention (MHA), if
|
| 56 |
+
`num_key_value_heads=1 the model will use Multi Query Attention (MQA) otherwise GQA is used. When
|
| 57 |
+
converting a multi-head checkpoint to a GQA checkpoint, each group key and value head should be constructed
|
| 58 |
+
by meanpooling all the original heads within that group. For more details checkout [this
|
| 59 |
+
paper](https://arxiv.org/pdf/2305.13245.pdf). If it is not specified, will default to
|
| 60 |
+
`num_attention_heads`.
|
| 61 |
+
resid_pdrop (`float`, *optional*, defaults to 0.0):
|
| 62 |
+
Dropout probability for mlp outputs.
|
| 63 |
+
embd_pdrop (`int`, *optional*, defaults to 0.0):
|
| 64 |
+
The dropout ratio for the embeddings.
|
| 65 |
+
attention_dropout (`float`, *optional*, defaults to 0.0):
|
| 66 |
+
The dropout ratio after computing the attention scores.
|
| 67 |
+
hidden_act (`str` or `function`, *optional*, defaults to `"silu"`):
|
| 68 |
+
The non-linear activation function (function or string) in the decoder.
|
| 69 |
+
max_position_embeddings (`int`, *optional*, defaults to 4096):
|
| 70 |
+
The maximum sequence length that this model might ever be used with.
|
| 71 |
+
original_max_position_embeddings (`int`, *optional*, defaults to 4096):
|
| 72 |
+
The maximum sequence length that this model was trained with. This is used to determine the size of the
|
| 73 |
+
original RoPE embeddings when using long scaling.
|
| 74 |
+
initializer_range (`float`, *optional*, defaults to 0.02):
|
| 75 |
+
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
|
| 76 |
+
rms_norm_eps (`float`, *optional*, defaults to 1e-05):
|
| 77 |
+
The epsilon value used for the RMSNorm.
|
| 78 |
+
use_cache (`bool`, *optional*, defaults to `True`):
|
| 79 |
+
Whether or not the model should return the last key/values attentions (not used by all models). Only
|
| 80 |
+
relevant if `config.is_decoder=True`. Whether to tie weight embeddings or not.
|
| 81 |
+
tie_word_embeddings (`bool`, *optional*, defaults to `False`):
|
| 82 |
+
Whether to tie weight embeddings
|
| 83 |
+
rope_theta (`float`, *optional*, defaults to 10000.0):
|
| 84 |
+
The base period of the RoPE embeddings.
|
| 85 |
+
rope_scaling (`dict`, *optional*):
|
| 86 |
+
The scaling strategy for the RoPE embeddings. If `None`, no scaling is applied. If a dictionary, it must
|
| 87 |
+
contain the following keys: `type`, `short_factor` and `long_factor`. The `type` must be `longrope` and
|
| 88 |
+
the `short_factor` and `long_factor` must be lists of numbers with the same length as the hidden size
|
| 89 |
+
divided by the number of attention heads divided by 2.
|
| 90 |
+
bos_token_id (`int`, *optional*, defaults to 1):
|
| 91 |
+
The id of the "beginning-of-sequence" token.
|
| 92 |
+
eos_token_id (`int`, *optional*, defaults to 32000):
|
| 93 |
+
The id of the "end-of-sequence" token.
|
| 94 |
+
pad_token_id (`int`, *optional*, defaults to 32000):
|
| 95 |
+
The id of the padding token.
|
| 96 |
+
sliding_window (`int`, *optional*):
|
| 97 |
+
Sliding window attention window size. If `None`, no sliding window is applied.
|
| 98 |
+
|
| 99 |
+
Example:
|
| 100 |
+
|
| 101 |
+
```python
|
| 102 |
+
>>> from transformers import Phi3Model, Phi3Config
|
| 103 |
+
|
| 104 |
+
>>> # Initializing a Phi-3 style configuration
|
| 105 |
+
>>> configuration = Phi3Config.from_pretrained("microsoft/Phi-3-mini-4k-instruct")
|
| 106 |
+
|
| 107 |
+
>>> # Initializing a model from the configuration
|
| 108 |
+
>>> model = Phi3Model(configuration)
|
| 109 |
+
|
| 110 |
+
>>> # Accessing the model configuration
|
| 111 |
+
>>> configuration = model.config
|
| 112 |
+
```"""
|
| 113 |
+
|
| 114 |
+
model_type = "phi3"
|
| 115 |
+
keys_to_ignore_at_inference = ["past_key_values"]
|
| 116 |
+
|
| 117 |
+
def __init__(
|
| 118 |
+
self,
|
| 119 |
+
vocab_size=32064,
|
| 120 |
+
hidden_size=3072,
|
| 121 |
+
intermediate_size=8192,
|
| 122 |
+
num_hidden_layers=32,
|
| 123 |
+
num_attention_heads=32,
|
| 124 |
+
num_key_value_heads=None,
|
| 125 |
+
resid_pdrop=0.0,
|
| 126 |
+
embd_pdrop=0.0,
|
| 127 |
+
attention_dropout=0.0,
|
| 128 |
+
hidden_act="silu",
|
| 129 |
+
max_position_embeddings=4096,
|
| 130 |
+
original_max_position_embeddings=4096,
|
| 131 |
+
initializer_range=0.02,
|
| 132 |
+
rms_norm_eps=1e-5,
|
| 133 |
+
use_cache=True,
|
| 134 |
+
tie_word_embeddings=False,
|
| 135 |
+
rope_theta=10000.0,
|
| 136 |
+
rope_scaling=None,
|
| 137 |
+
bos_token_id=1,
|
| 138 |
+
eos_token_id=32000,
|
| 139 |
+
pad_token_id=32000,
|
| 140 |
+
sliding_window=None,
|
| 141 |
+
**kwargs,
|
| 142 |
+
):
|
| 143 |
+
self.vocab_size = vocab_size
|
| 144 |
+
self.hidden_size = hidden_size
|
| 145 |
+
self.intermediate_size = intermediate_size
|
| 146 |
+
self.num_hidden_layers = num_hidden_layers
|
| 147 |
+
self.num_attention_heads = num_attention_heads
|
| 148 |
+
|
| 149 |
+
if num_key_value_heads is None:
|
| 150 |
+
num_key_value_heads = num_attention_heads
|
| 151 |
+
|
| 152 |
+
self.num_key_value_heads = num_key_value_heads
|
| 153 |
+
self.resid_pdrop = resid_pdrop
|
| 154 |
+
self.embd_pdrop = embd_pdrop
|
| 155 |
+
self.attention_dropout = attention_dropout
|
| 156 |
+
self.hidden_act = hidden_act
|
| 157 |
+
self.max_position_embeddings = max_position_embeddings
|
| 158 |
+
self.original_max_position_embeddings = original_max_position_embeddings
|
| 159 |
+
self.initializer_range = initializer_range
|
| 160 |
+
self.rms_norm_eps = rms_norm_eps
|
| 161 |
+
self.use_cache = use_cache
|
| 162 |
+
self.rope_theta = rope_theta
|
| 163 |
+
self.rope_scaling = rope_scaling
|
| 164 |
+
self._rope_scaling_adjustment()
|
| 165 |
+
self._rope_scaling_validation()
|
| 166 |
+
self.sliding_window = sliding_window
|
| 167 |
+
|
| 168 |
+
super().__init__(
|
| 169 |
+
bos_token_id=bos_token_id,
|
| 170 |
+
eos_token_id=eos_token_id,
|
| 171 |
+
pad_token_id=pad_token_id,
|
| 172 |
+
tie_word_embeddings=tie_word_embeddings,
|
| 173 |
+
**kwargs,
|
| 174 |
+
)
|
| 175 |
+
|
| 176 |
+
def _rope_scaling_adjustment(self):
|
| 177 |
+
"""
|
| 178 |
+
Adjust the `type` of the `rope_scaling` configuration for backward compatibility.
|
| 179 |
+
"""
|
| 180 |
+
if self.rope_scaling is None:
|
| 181 |
+
return
|
| 182 |
+
|
| 183 |
+
rope_scaling_type = self.rope_scaling.get("type", None)
|
| 184 |
+
|
| 185 |
+
# For backward compatibility if previous version used "su" or "yarn"
|
| 186 |
+
if rope_scaling_type is not None and rope_scaling_type in ["su", "yarn"]:
|
| 187 |
+
self.rope_scaling["type"] = "longrope"
|
| 188 |
+
|
| 189 |
+
def _rope_scaling_validation(self):
|
| 190 |
+
"""
|
| 191 |
+
Validate the `rope_scaling` configuration.
|
| 192 |
+
"""
|
| 193 |
+
if self.rope_scaling is None:
|
| 194 |
+
return
|
| 195 |
+
|
| 196 |
+
if not isinstance(self.rope_scaling, dict) or len(self.rope_scaling) != 3:
|
| 197 |
+
raise ValueError(
|
| 198 |
+
"`rope_scaling` must be a dictionary with three fields, `type`, `short_factor` and `long_factor`, "
|
| 199 |
+
f"got {self.rope_scaling}"
|
| 200 |
+
)
|
| 201 |
+
rope_scaling_type = self.rope_scaling.get("type", None)
|
| 202 |
+
rope_scaling_short_factor = self.rope_scaling.get("short_factor", None)
|
| 203 |
+
rope_scaling_long_factor = self.rope_scaling.get("long_factor", None)
|
| 204 |
+
if rope_scaling_type is None or rope_scaling_type not in ["longrope"]:
|
| 205 |
+
raise ValueError(f"`rope_scaling`'s type field must be one of ['longrope'], got {rope_scaling_type}")
|
| 206 |
+
if not (
|
| 207 |
+
isinstance(rope_scaling_short_factor, list)
|
| 208 |
+
and all(isinstance(x, (int, float)) for x in rope_scaling_short_factor)
|
| 209 |
+
):
|
| 210 |
+
raise ValueError(
|
| 211 |
+
f"`rope_scaling`'s short_factor field must be a list of numbers, got {rope_scaling_short_factor}"
|
| 212 |
+
)
|
| 213 |
+
if not len(rope_scaling_short_factor) == self.hidden_size // self.num_attention_heads // 2:
|
| 214 |
+
raise ValueError(
|
| 215 |
+
f"`rope_scaling`'s short_factor field must have length {self.hidden_size // self.num_attention_heads // 2}, got {len(rope_scaling_short_factor)}"
|
| 216 |
+
)
|
| 217 |
+
if not (
|
| 218 |
+
isinstance(rope_scaling_long_factor, list)
|
| 219 |
+
and all(isinstance(x, (int, float)) for x in rope_scaling_long_factor)
|
| 220 |
+
):
|
| 221 |
+
raise ValueError(
|
| 222 |
+
f"`rope_scaling`'s long_factor field must be a list of numbers, got {rope_scaling_long_factor}"
|
| 223 |
+
)
|
| 224 |
+
if not len(rope_scaling_long_factor) == self.hidden_size // self.num_attention_heads // 2:
|
| 225 |
+
raise ValueError(
|
| 226 |
+
f"`rope_scaling`'s long_factor field must have length {self.hidden_size // self.num_attention_heads // 2}, got {len(rope_scaling_long_factor)}"
|
| 227 |
+
)
|
cuda/cuda-int4-awq-block-32/genai_config.json
ADDED
|
@@ -0,0 +1,59 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"model": {
|
| 3 |
+
"bos_token_id": 1,
|
| 4 |
+
"context_length": 131072,
|
| 5 |
+
"decoder": {
|
| 6 |
+
"session_options": {
|
| 7 |
+
"log_id": "onnxruntime-genai",
|
| 8 |
+
"provider_options": [
|
| 9 |
+
{
|
| 10 |
+
"cuda": {
|
| 11 |
+
"enable_cuda_graph": "0"
|
| 12 |
+
}
|
| 13 |
+
}
|
| 14 |
+
]
|
| 15 |
+
},
|
| 16 |
+
"filename": "phi3-mini-128k-instruct-cuda-int4-awq-block-128.onnx",
|
| 17 |
+
"head_size": 96,
|
| 18 |
+
"hidden_size": 3072,
|
| 19 |
+
"inputs": {
|
| 20 |
+
"input_ids": "input_ids",
|
| 21 |
+
"attention_mask": "attention_mask",
|
| 22 |
+
"past_key_names": "past_key_values.%d.key",
|
| 23 |
+
"past_value_names": "past_key_values.%d.value"
|
| 24 |
+
},
|
| 25 |
+
"outputs": {
|
| 26 |
+
"logits": "logits",
|
| 27 |
+
"present_key_names": "present.%d.key",
|
| 28 |
+
"present_value_names": "present.%d.value"
|
| 29 |
+
},
|
| 30 |
+
"num_attention_heads": 32,
|
| 31 |
+
"num_hidden_layers": 32,
|
| 32 |
+
"num_key_value_heads": 32
|
| 33 |
+
},
|
| 34 |
+
"eos_token_id": [
|
| 35 |
+
32000,
|
| 36 |
+
32001,
|
| 37 |
+
32007
|
| 38 |
+
],
|
| 39 |
+
"pad_token_id": 32000,
|
| 40 |
+
"type": "phi3",
|
| 41 |
+
"vocab_size": 32064
|
| 42 |
+
},
|
| 43 |
+
"search": {
|
| 44 |
+
"diversity_penalty": 0.0,
|
| 45 |
+
"do_sample": false,
|
| 46 |
+
"early_stopping": true,
|
| 47 |
+
"length_penalty": 1.0,
|
| 48 |
+
"max_length": 131072,
|
| 49 |
+
"min_length": 0,
|
| 50 |
+
"no_repeat_ngram_size": 0,
|
| 51 |
+
"num_beams": 1,
|
| 52 |
+
"num_return_sequences": 1,
|
| 53 |
+
"past_present_share_buffer": true,
|
| 54 |
+
"repetition_penalty": 1.0,
|
| 55 |
+
"temperature": 1.0,
|
| 56 |
+
"top_k": 1,
|
| 57 |
+
"top_p": 1.0
|
| 58 |
+
}
|
| 59 |
+
}
|
cuda/cuda-int4-awq-block-32/phi3-mini-128k-instruct-cuda-int4-awq-block-128.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:589d74bc36056fe730e574d3c4274d1d3b99d7c6420b21e52e82d418fe5b2a2a
|
| 3 |
+
size 26215627
|
cuda/cuda-int4-awq-block-32/phi3-mini-128k-instruct-cuda-int4-awq-block-128.onnx.data
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:7f30c056e81ce840cd2527e448ac3dfc55e38b8143b78bf3f3169805f779f35d
|
| 3 |
+
size 2277120000
|
cuda/cuda-int4-awq-block-32/special_tokens_map.json
ADDED
|
@@ -0,0 +1,30 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bos_token": {
|
| 3 |
+
"content": "<s>",
|
| 4 |
+
"lstrip": false,
|
| 5 |
+
"normalized": false,
|
| 6 |
+
"rstrip": false,
|
| 7 |
+
"single_word": false
|
| 8 |
+
},
|
| 9 |
+
"eos_token": {
|
| 10 |
+
"content": "<|endoftext|>",
|
| 11 |
+
"lstrip": false,
|
| 12 |
+
"normalized": false,
|
| 13 |
+
"rstrip": false,
|
| 14 |
+
"single_word": false
|
| 15 |
+
},
|
| 16 |
+
"pad_token": {
|
| 17 |
+
"content": "<|endoftext|>",
|
| 18 |
+
"lstrip": false,
|
| 19 |
+
"normalized": false,
|
| 20 |
+
"rstrip": false,
|
| 21 |
+
"single_word": false
|
| 22 |
+
},
|
| 23 |
+
"unk_token": {
|
| 24 |
+
"content": "<unk>",
|
| 25 |
+
"lstrip": false,
|
| 26 |
+
"normalized": false,
|
| 27 |
+
"rstrip": false,
|
| 28 |
+
"single_word": false
|
| 29 |
+
}
|
| 30 |
+
}
|
cuda/cuda-int4-awq-block-32/tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
cuda/cuda-int4-awq-block-32/tokenizer.model
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
|
| 3 |
+
size 499723
|
cuda/cuda-int4-awq-block-32/tokenizer_config.json
ADDED
|
@@ -0,0 +1,130 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_bos_token": false,
|
| 3 |
+
"add_eos_token": false,
|
| 4 |
+
"added_tokens_decoder": {
|
| 5 |
+
"0": {
|
| 6 |
+
"content": "<unk>",
|
| 7 |
+
"lstrip": false,
|
| 8 |
+
"normalized": false,
|
| 9 |
+
"rstrip": false,
|
| 10 |
+
"single_word": false,
|
| 11 |
+
"special": true
|
| 12 |
+
},
|
| 13 |
+
"1": {
|
| 14 |
+
"content": "<s>",
|
| 15 |
+
"lstrip": false,
|
| 16 |
+
"normalized": false,
|
| 17 |
+
"rstrip": false,
|
| 18 |
+
"single_word": false,
|
| 19 |
+
"special": true
|
| 20 |
+
},
|
| 21 |
+
"2": {
|
| 22 |
+
"content": "</s>",
|
| 23 |
+
"lstrip": false,
|
| 24 |
+
"normalized": false,
|
| 25 |
+
"rstrip": true,
|
| 26 |
+
"single_word": false,
|
| 27 |
+
"special": false
|
| 28 |
+
},
|
| 29 |
+
"32000": {
|
| 30 |
+
"content": "<|endoftext|>",
|
| 31 |
+
"lstrip": false,
|
| 32 |
+
"normalized": false,
|
| 33 |
+
"rstrip": false,
|
| 34 |
+
"single_word": false,
|
| 35 |
+
"special": true
|
| 36 |
+
},
|
| 37 |
+
"32001": {
|
| 38 |
+
"content": "<|assistant|>",
|
| 39 |
+
"lstrip": false,
|
| 40 |
+
"normalized": false,
|
| 41 |
+
"rstrip": true,
|
| 42 |
+
"single_word": false,
|
| 43 |
+
"special": true
|
| 44 |
+
},
|
| 45 |
+
"32002": {
|
| 46 |
+
"content": "<|placeholder1|>",
|
| 47 |
+
"lstrip": false,
|
| 48 |
+
"normalized": false,
|
| 49 |
+
"rstrip": true,
|
| 50 |
+
"single_word": false,
|
| 51 |
+
"special": true
|
| 52 |
+
},
|
| 53 |
+
"32003": {
|
| 54 |
+
"content": "<|placeholder2|>",
|
| 55 |
+
"lstrip": false,
|
| 56 |
+
"normalized": false,
|
| 57 |
+
"rstrip": true,
|
| 58 |
+
"single_word": false,
|
| 59 |
+
"special": true
|
| 60 |
+
},
|
| 61 |
+
"32004": {
|
| 62 |
+
"content": "<|placeholder3|>",
|
| 63 |
+
"lstrip": false,
|
| 64 |
+
"normalized": false,
|
| 65 |
+
"rstrip": true,
|
| 66 |
+
"single_word": false,
|
| 67 |
+
"special": true
|
| 68 |
+
},
|
| 69 |
+
"32005": {
|
| 70 |
+
"content": "<|placeholder4|>",
|
| 71 |
+
"lstrip": false,
|
| 72 |
+
"normalized": false,
|
| 73 |
+
"rstrip": true,
|
| 74 |
+
"single_word": false,
|
| 75 |
+
"special": true
|
| 76 |
+
},
|
| 77 |
+
"32006": {
|
| 78 |
+
"content": "<|system|>",
|
| 79 |
+
"lstrip": false,
|
| 80 |
+
"normalized": false,
|
| 81 |
+
"rstrip": true,
|
| 82 |
+
"single_word": false,
|
| 83 |
+
"special": true
|
| 84 |
+
},
|
| 85 |
+
"32007": {
|
| 86 |
+
"content": "<|end|>",
|
| 87 |
+
"lstrip": false,
|
| 88 |
+
"normalized": false,
|
| 89 |
+
"rstrip": true,
|
| 90 |
+
"single_word": false,
|
| 91 |
+
"special": true
|
| 92 |
+
},
|
| 93 |
+
"32008": {
|
| 94 |
+
"content": "<|placeholder5|>",
|
| 95 |
+
"lstrip": false,
|
| 96 |
+
"normalized": false,
|
| 97 |
+
"rstrip": true,
|
| 98 |
+
"single_word": false,
|
| 99 |
+
"special": true
|
| 100 |
+
},
|
| 101 |
+
"32009": {
|
| 102 |
+
"content": "<|placeholder6|>",
|
| 103 |
+
"lstrip": false,
|
| 104 |
+
"normalized": false,
|
| 105 |
+
"rstrip": true,
|
| 106 |
+
"single_word": false,
|
| 107 |
+
"special": true
|
| 108 |
+
},
|
| 109 |
+
"32010": {
|
| 110 |
+
"content": "<|user|>",
|
| 111 |
+
"lstrip": false,
|
| 112 |
+
"normalized": false,
|
| 113 |
+
"rstrip": true,
|
| 114 |
+
"single_word": false,
|
| 115 |
+
"special": true
|
| 116 |
+
}
|
| 117 |
+
},
|
| 118 |
+
"bos_token": "<s>",
|
| 119 |
+
"chat_template": "{% for message in messages %}{% if message['role'] == 'system' %}{{'<|system|>\n' + message['content'] + '<|end|>\n'}}{% elif message['role'] == 'user' %}{{'<|user|>\n' + message['content'] + '<|end|>\n'}}{% elif message['role'] == 'assistant' %}{{'<|assistant|>\n' + message['content'] + '<|end|>\n'}}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|assistant|>\n' }}{% else %}{{ eos_token }}{% endif %}",
|
| 120 |
+
"clean_up_tokenization_spaces": false,
|
| 121 |
+
"eos_token": "<|endoftext|>",
|
| 122 |
+
"legacy": false,
|
| 123 |
+
"model_max_length": 131072,
|
| 124 |
+
"pad_token": "<|endoftext|>",
|
| 125 |
+
"padding_side": "left",
|
| 126 |
+
"sp_model_kwargs": {},
|
| 127 |
+
"tokenizer_class": "LlamaTokenizer",
|
| 128 |
+
"unk_token": "<unk>",
|
| 129 |
+
"use_default_system_prompt": false
|
| 130 |
+
}
|
cuda/cuda-int4-rtn-block-32/added_tokens.json
CHANGED
|
@@ -1,13 +1,13 @@
|
|
| 1 |
-
{
|
| 2 |
-
"<|endoftext|>": 32000,
|
| 3 |
-
"<|assistant|>": 32001,
|
| 4 |
-
"<|placeholder1|>": 32002,
|
| 5 |
-
"<|placeholder2|>": 32003,
|
| 6 |
-
"<|placeholder3|>": 32004,
|
| 7 |
-
"<|placeholder4|>": 32005,
|
| 8 |
-
"<|system|>": 32006,
|
| 9 |
-
"<|end|>": 32007,
|
| 10 |
-
"<|placeholder5|>": 32008,
|
| 11 |
-
"<|placeholder6|>": 32009,
|
| 12 |
-
"<|user|>": 32010
|
| 13 |
-
}
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"<|endoftext|>": 32000,
|
| 3 |
+
"<|assistant|>": 32001,
|
| 4 |
+
"<|placeholder1|>": 32002,
|
| 5 |
+
"<|placeholder2|>": 32003,
|
| 6 |
+
"<|placeholder3|>": 32004,
|
| 7 |
+
"<|placeholder4|>": 32005,
|
| 8 |
+
"<|system|>": 32006,
|
| 9 |
+
"<|end|>": 32007,
|
| 10 |
+
"<|placeholder5|>": 32008,
|
| 11 |
+
"<|placeholder6|>": 32009,
|
| 12 |
+
"<|user|>": 32010
|
| 13 |
+
}
|
cuda/cuda-int4-rtn-block-32/config.json
CHANGED
|
@@ -1,137 +1,138 @@
|
|
| 1 |
-
{
|
| 2 |
-
"_name_or_path": "
|
| 3 |
-
"architectures": [
|
| 4 |
-
"Phi3ForCausalLM"
|
| 5 |
-
],
|
| 6 |
-
"attention_dropout": 0.0,
|
| 7 |
-
"auto_map": {
|
| 8 |
-
"AutoConfig": "configuration_phi3.Phi3Config",
|
| 9 |
-
"AutoModelForCausalLM": "modeling_phi3.Phi3ForCausalLM"
|
| 10 |
-
},
|
| 11 |
-
"bos_token_id": 1,
|
| 12 |
-
"embd_pdrop": 0.0,
|
| 13 |
-
"eos_token_id": 32000,
|
| 14 |
-
"hidden_act": "silu",
|
| 15 |
-
"hidden_size": 3072,
|
| 16 |
-
"initializer_range": 0.02,
|
| 17 |
-
"intermediate_size": 8192,
|
| 18 |
-
"max_position_embeddings": 131072,
|
| 19 |
-
"model_type": "phi3",
|
| 20 |
-
"num_attention_heads": 32,
|
| 21 |
-
"num_hidden_layers": 32,
|
| 22 |
-
"num_key_value_heads": 32,
|
| 23 |
-
"original_max_position_embeddings": 4096,
|
| 24 |
-
"pad_token_id": 32000,
|
| 25 |
-
"resid_pdrop": 0.0,
|
| 26 |
-
"rms_norm_eps": 1e-05,
|
| 27 |
-
"rope_scaling": {
|
| 28 |
-
"long_factor": [
|
| 29 |
-
1.
|
| 30 |
-
1.
|
| 31 |
-
1.
|
| 32 |
-
1.
|
| 33 |
-
1.
|
| 34 |
-
1.
|
| 35 |
-
|
| 36 |
-
|
| 37 |
-
|
| 38 |
-
|
| 39 |
-
|
| 40 |
-
|
| 41 |
-
|
| 42 |
-
|
| 43 |
-
|
| 44 |
-
|
| 45 |
-
|
| 46 |
-
|
| 47 |
-
|
| 48 |
-
|
| 49 |
-
|
| 50 |
-
|
| 51 |
-
|
| 52 |
-
|
| 53 |
-
|
| 54 |
-
|
| 55 |
-
|
| 56 |
-
|
| 57 |
-
|
| 58 |
-
|
| 59 |
-
|
| 60 |
-
|
| 61 |
-
|
| 62 |
-
|
| 63 |
-
|
| 64 |
-
|
| 65 |
-
|
| 66 |
-
|
| 67 |
-
63.
|
| 68 |
-
|
| 69 |
-
|
| 70 |
-
|
| 71 |
-
|
| 72 |
-
64.
|
| 73 |
-
64.
|
| 74 |
-
64.
|
| 75 |
-
64.
|
| 76 |
-
64.
|
| 77 |
-
],
|
| 78 |
-
"short_factor": [
|
| 79 |
-
1.
|
| 80 |
-
1.
|
| 81 |
-
1.
|
| 82 |
-
1.
|
| 83 |
-
1.
|
| 84 |
-
1.
|
| 85 |
-
1.
|
| 86 |
-
1.
|
| 87 |
-
|
| 88 |
-
|
| 89 |
-
|
| 90 |
-
2.000000000000001,
|
| 91 |
-
2.000000000000001,
|
| 92 |
-
2.000000000000001,
|
| 93 |
-
2.000000000000001,
|
| 94 |
-
2.000000000000001,
|
| 95 |
-
2.000000000000001,
|
| 96 |
-
2.000000000000001,
|
| 97 |
-
2.000000000000001,
|
| 98 |
-
2.000000000000001,
|
| 99 |
-
2.000000000000001,
|
| 100 |
-
2.000000000000001,
|
| 101 |
-
2.000000000000001,
|
| 102 |
-
2.000000000000001,
|
| 103 |
-
2.000000000000001,
|
| 104 |
-
2.
|
| 105 |
-
2.
|
| 106 |
-
2.
|
| 107 |
-
2.
|
| 108 |
-
2.
|
| 109 |
-
2.
|
| 110 |
-
2.
|
| 111 |
-
2.
|
| 112 |
-
2.
|
| 113 |
-
2.
|
| 114 |
-
2.
|
| 115 |
-
2.
|
| 116 |
-
2.
|
| 117 |
-
2.
|
| 118 |
-
2.
|
| 119 |
-
2.
|
| 120 |
-
2.
|
| 121 |
-
2.
|
| 122 |
-
2.
|
| 123 |
-
2.7499999999999982,
|
| 124 |
-
2.
|
| 125 |
-
2.
|
| 126 |
-
|
| 127 |
-
],
|
| 128 |
-
|
| 129 |
-
},
|
| 130 |
-
"rope_theta": 10000.0,
|
| 131 |
-
"sliding_window": 262144,
|
| 132 |
-
"tie_word_embeddings": false,
|
| 133 |
-
"torch_dtype": "bfloat16",
|
| 134 |
-
"transformers_version": "4.
|
| 135 |
-
"use_cache": true,
|
| 136 |
-
"
|
| 137 |
-
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_name_or_path": "Phi-3-mini-128k-instruct",
|
| 3 |
+
"architectures": [
|
| 4 |
+
"Phi3ForCausalLM"
|
| 5 |
+
],
|
| 6 |
+
"attention_dropout": 0.0,
|
| 7 |
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"auto_map": {
|
| 8 |
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"AutoConfig": "configuration_phi3.Phi3Config",
|
| 9 |
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"AutoModelForCausalLM": "modeling_phi3.Phi3ForCausalLM"
|
| 10 |
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},
|
| 11 |
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"bos_token_id": 1,
|
| 12 |
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"embd_pdrop": 0.0,
|
| 13 |
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"eos_token_id": 32000,
|
| 14 |
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"hidden_act": "silu",
|
| 15 |
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"hidden_size": 3072,
|
| 16 |
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"initializer_range": 0.02,
|
| 17 |
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"intermediate_size": 8192,
|
| 18 |
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"max_position_embeddings": 131072,
|
| 19 |
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"model_type": "phi3",
|
| 20 |
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"num_attention_heads": 32,
|
| 21 |
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"num_hidden_layers": 32,
|
| 22 |
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"num_key_value_heads": 32,
|
| 23 |
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|
| 24 |
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|
| 25 |
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|
| 26 |
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|
| 27 |
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"rope_scaling": {
|
| 28 |
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"long_factor": [
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| 29 |
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1.0700000524520874,
|
| 30 |
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1.1200000047683716,
|
| 31 |
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1.149999976158142,
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| 32 |
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1.4199999570846558,
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| 33 |
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1.5699999332427979,
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| 34 |
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1.7999999523162842,
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2.129999876022339,
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| 36 |
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2.129999876022339,
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| 37 |
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3.009999990463257,
|
| 38 |
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5.910000324249268,
|
| 39 |
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6.950000286102295,
|
| 40 |
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9.070000648498535,
|
| 41 |
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9.930000305175781,
|
| 42 |
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10.710000038146973,
|
| 43 |
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11.130000114440918,
|
| 44 |
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14.609999656677246,
|
| 45 |
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15.409998893737793,
|
| 46 |
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19.809999465942383,
|
| 47 |
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37.279998779296875,
|
| 48 |
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38.279998779296875,
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|
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|
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46.20000457763672,
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50.940006256103516,
|
| 53 |
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53.66000747680664,
|
| 54 |
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54.9373893737793,
|
| 55 |
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56.89738845825195,
|
| 56 |
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| 57 |
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|
| 58 |
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| 59 |
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60.887386322021484,
|
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61.71739196777344,
|
| 61 |
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62.91739273071289,
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| 62 |
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62.957393646240234,
|
| 63 |
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63.41739273071289,
|
| 64 |
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63.8173942565918,
|
| 65 |
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63.83739471435547,
|
| 66 |
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63.897396087646484,
|
| 67 |
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63.93739700317383,
|
| 68 |
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64.06739807128906,
|
| 69 |
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64.11434936523438,
|
| 70 |
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64.12435150146484,
|
| 71 |
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64.15435028076172,
|
| 72 |
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64.19435119628906,
|
| 73 |
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|
| 74 |
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64.57435607910156,
|
| 75 |
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64.69000244140625,
|
| 76 |
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64.76000213623047
|
| 77 |
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],
|
| 78 |
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"short_factor": [
|
| 79 |
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1.1,
|
| 80 |
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1.1,
|
| 81 |
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1.1,
|
| 82 |
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1.3000000000000003,
|
| 83 |
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1.3500000000000003,
|
| 84 |
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1.3500000000000003,
|
| 85 |
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1.4000000000000004,
|
| 86 |
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1.5500000000000005,
|
| 87 |
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2.000000000000001,
|
| 88 |
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2.000000000000001,
|
| 89 |
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2.000000000000001,
|
| 90 |
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2.000000000000001,
|
| 91 |
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2.000000000000001,
|
| 92 |
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2.000000000000001,
|
| 93 |
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2.000000000000001,
|
| 94 |
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2.000000000000001,
|
| 95 |
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2.000000000000001,
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| 96 |
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2.000000000000001,
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| 97 |
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2.000000000000001,
|
| 98 |
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2.000000000000001,
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| 99 |
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2.000000000000001,
|
| 100 |
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2.000000000000001,
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2.000000000000001,
|
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2.000000000000001,
|
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2.0500000000000007,
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2.0500000000000007,
|
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2.0500000000000007,
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| 107 |
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2.0500000000000007,
|
| 108 |
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2.0500000000000007,
|
| 109 |
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2.0500000000000007,
|
| 110 |
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2.1000000000000005,
|
| 111 |
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2.1000000000000005,
|
| 112 |
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2.1500000000000004,
|
| 113 |
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2.25,
|
| 114 |
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2.25,
|
| 115 |
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2.25,
|
| 116 |
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2.25,
|
| 117 |
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2.25,
|
| 118 |
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2.3999999999999995,
|
| 119 |
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2.4499999999999993,
|
| 120 |
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2.499999999999999,
|
| 121 |
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2.6999999999999984,
|
| 122 |
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2.6999999999999984,
|
| 123 |
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2.7499999999999982,
|
| 124 |
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2.799999999999998,
|
| 125 |
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2.8999999999999977,
|
| 126 |
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3.049999999999997
|
| 127 |
+
],
|
| 128 |
+
"type": "longrope"
|
| 129 |
+
},
|
| 130 |
+
"rope_theta": 10000.0,
|
| 131 |
+
"sliding_window": 262144,
|
| 132 |
+
"tie_word_embeddings": false,
|
| 133 |
+
"torch_dtype": "bfloat16",
|
| 134 |
+
"transformers_version": "4.40.2",
|
| 135 |
+
"use_cache": true,
|
| 136 |
+
"attention_bias": false,
|
| 137 |
+
"vocab_size": 32064
|
| 138 |
+
}
|
cuda/cuda-int4-rtn-block-32/configuration_phi3.py
CHANGED
|
@@ -1,213 +1,227 @@
|
|
| 1 |
-
# coding=utf-8
|
| 2 |
-
# Copyright 2024 Microsoft and the HuggingFace Inc. team. All rights reserved.
|
| 3 |
-
#
|
| 4 |
-
# Licensed under the Apache License, Version 2.0 (the "License");
|
| 5 |
-
# you may not use this file except in compliance with the License.
|
| 6 |
-
# You may obtain a copy of the License at
|
| 7 |
-
#
|
| 8 |
-
# http://www.apache.org/licenses/LICENSE-2.0
|
| 9 |
-
#
|
| 10 |
-
# Unless required by applicable law or agreed to in writing, software
|
| 11 |
-
# distributed under the License is distributed on an "AS IS" BASIS,
|
| 12 |
-
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
| 13 |
-
# See the License for the specific language governing permissions and
|
| 14 |
-
# limitations under the License.
|
| 15 |
-
|
| 16 |
-
""" Phi-3 model configuration"""
|
| 17 |
-
|
| 18 |
-
|
| 19 |
-
from transformers.configuration_utils import PretrainedConfig
|
| 20 |
-
from transformers.utils import logging
|
| 21 |
-
|
| 22 |
-
|
| 23 |
-
logger = logging.get_logger(__name__)
|
| 24 |
-
|
| 25 |
-
PHI3_PRETRAINED_CONFIG_ARCHIVE_MAP = {
|
| 26 |
-
"microsoft/Phi-3-mini-4k-instruct": "https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/resolve/main/config.json",
|
| 27 |
-
"microsoft/Phi-3-mini-128k-instruct": "https://huggingface.co/microsoft/Phi-3-mini-128k-instruct/resolve/main/config.json",
|
| 28 |
-
}
|
| 29 |
-
|
| 30 |
-
|
| 31 |
-
class Phi3Config(PretrainedConfig):
|
| 32 |
-
r"""
|
| 33 |
-
This is the configuration class to store the configuration of a [`Phi3Model`]. It is used to instantiate a Phi-3
|
| 34 |
-
model according to the specified arguments, defining the model architecture. Instantiating a configuration with the
|
| 35 |
-
defaults will yield a similar configuration to that of the
|
| 36 |
-
[microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct).
|
| 37 |
-
|
| 38 |
-
Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
|
| 39 |
-
documentation from [`PretrainedConfig`] for more information.
|
| 40 |
-
|
| 41 |
-
Args:
|
| 42 |
-
vocab_size (`int`, *optional*, defaults to 32064):
|
| 43 |
-
Vocabulary size of the Phi-3 model. Defines the number of different tokens that can be represented by the
|
| 44 |
-
`inputs_ids` passed when calling [`Phi3Model`].
|
| 45 |
-
hidden_size (`int`, *optional*, defaults to 3072):
|
| 46 |
-
Dimension of the hidden representations.
|
| 47 |
-
intermediate_size (`int`, *optional*, defaults to 8192):
|
| 48 |
-
Dimension of the MLP representations.
|
| 49 |
-
num_hidden_layers (`int`, *optional*, defaults to 32):
|
| 50 |
-
Number of hidden layers in the Transformer decoder.
|
| 51 |
-
num_attention_heads (`int`, *optional*, defaults to 32):
|
| 52 |
-
Number of attention heads for each attention layer in the Transformer decoder.
|
| 53 |
-
num_key_value_heads (`int`, *optional*):
|
| 54 |
-
This is the number of key_value heads that should be used to implement Grouped Query Attention. If
|
| 55 |
-
`num_key_value_heads=num_attention_heads`, the model will use Multi Head Attention (MHA), if
|
| 56 |
-
`num_key_value_heads=1 the model will use Multi Query Attention (MQA) otherwise GQA is used. When
|
| 57 |
-
converting a multi-head checkpoint to a GQA checkpoint, each group key and value head should be constructed
|
| 58 |
-
by meanpooling all the original heads within that group. For more details checkout [this
|
| 59 |
-
paper](https://arxiv.org/pdf/2305.13245.pdf). If it is not specified, will default to
|
| 60 |
-
`num_attention_heads`.
|
| 61 |
-
resid_pdrop (`float`, *optional*, defaults to 0.0):
|
| 62 |
-
Dropout probability for mlp outputs.
|
| 63 |
-
embd_pdrop (`int`, *optional*, defaults to 0.0):
|
| 64 |
-
The dropout ratio for the embeddings.
|
| 65 |
-
attention_dropout (`float`, *optional*, defaults to 0.0):
|
| 66 |
-
The dropout ratio after computing the attention scores.
|
| 67 |
-
hidden_act (`str` or `function`, *optional*, defaults to `"silu"`):
|
| 68 |
-
The non-linear activation function (function or string) in the decoder.
|
| 69 |
-
max_position_embeddings (`int`, *optional*, defaults to 4096):
|
| 70 |
-
The maximum sequence length that this model might ever be used with.
|
| 71 |
-
original_max_position_embeddings (`int`, *optional*, defaults to 4096):
|
| 72 |
-
The maximum sequence length that this model was trained with. This is used to determine the size of the
|
| 73 |
-
original RoPE embeddings when using long scaling.
|
| 74 |
-
initializer_range (`float`, *optional*, defaults to 0.02):
|
| 75 |
-
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
|
| 76 |
-
rms_norm_eps (`float`, *optional*, defaults to 1e-05):
|
| 77 |
-
The epsilon value used for the RMSNorm.
|
| 78 |
-
use_cache (`bool`, *optional*, defaults to `True`):
|
| 79 |
-
Whether or not the model should return the last key/values attentions (not used by all models). Only
|
| 80 |
-
relevant if `config.is_decoder=True`. Whether to tie weight embeddings or not.
|
| 81 |
-
tie_word_embeddings (`bool`, *optional*, defaults to `False`):
|
| 82 |
-
Whether to tie weight embeddings
|
| 83 |
-
rope_theta (`float`, *optional*, defaults to 10000.0):
|
| 84 |
-
The base period of the RoPE embeddings.
|
| 85 |
-
rope_scaling (`dict`, *optional*):
|
| 86 |
-
The scaling strategy for the RoPE embeddings. If `None`, no scaling is applied. If a dictionary, it must
|
| 87 |
-
contain the following keys: `type`, `short_factor` and `long_factor`. The `type` must be
|
| 88 |
-
the `short_factor` and `long_factor` must be lists of numbers with the same length as the hidden size
|
| 89 |
-
divided by the number of attention heads divided by 2.
|
| 90 |
-
bos_token_id (`int`, *optional*, defaults to 1):
|
| 91 |
-
The id of the "beginning-of-sequence" token.
|
| 92 |
-
eos_token_id (`int`, *optional*, defaults to 32000):
|
| 93 |
-
The id of the "end-of-sequence" token.
|
| 94 |
-
pad_token_id (`int`, *optional*, defaults to 32000):
|
| 95 |
-
The id of the padding token.
|
| 96 |
-
sliding_window (`int`, *optional*):
|
| 97 |
-
Sliding window attention window size. If `None`, no sliding window is applied.
|
| 98 |
-
|
| 99 |
-
Example:
|
| 100 |
-
|
| 101 |
-
```python
|
| 102 |
-
>>> from transformers import Phi3Model, Phi3Config
|
| 103 |
-
|
| 104 |
-
>>> # Initializing a Phi-3 style configuration
|
| 105 |
-
>>> configuration = Phi3Config.from_pretrained("microsoft/Phi-3-mini-4k-instruct")
|
| 106 |
-
|
| 107 |
-
>>> # Initializing a model from the configuration
|
| 108 |
-
>>> model = Phi3Model(configuration)
|
| 109 |
-
|
| 110 |
-
>>> # Accessing the model configuration
|
| 111 |
-
>>> configuration = model.config
|
| 112 |
-
```"""
|
| 113 |
-
|
| 114 |
-
model_type = "phi3"
|
| 115 |
-
keys_to_ignore_at_inference = ["past_key_values"]
|
| 116 |
-
|
| 117 |
-
def __init__(
|
| 118 |
-
self,
|
| 119 |
-
vocab_size=32064,
|
| 120 |
-
hidden_size=3072,
|
| 121 |
-
intermediate_size=8192,
|
| 122 |
-
num_hidden_layers=32,
|
| 123 |
-
num_attention_heads=32,
|
| 124 |
-
num_key_value_heads=None,
|
| 125 |
-
resid_pdrop=0.0,
|
| 126 |
-
embd_pdrop=0.0,
|
| 127 |
-
attention_dropout=0.0,
|
| 128 |
-
hidden_act="silu",
|
| 129 |
-
max_position_embeddings=4096,
|
| 130 |
-
original_max_position_embeddings=4096,
|
| 131 |
-
initializer_range=0.02,
|
| 132 |
-
rms_norm_eps=1e-5,
|
| 133 |
-
use_cache=True,
|
| 134 |
-
tie_word_embeddings=False,
|
| 135 |
-
rope_theta=10000.0,
|
| 136 |
-
rope_scaling=None,
|
| 137 |
-
bos_token_id=1,
|
| 138 |
-
eos_token_id=32000,
|
| 139 |
-
pad_token_id=32000,
|
| 140 |
-
sliding_window=None,
|
| 141 |
-
**kwargs,
|
| 142 |
-
):
|
| 143 |
-
self.vocab_size = vocab_size
|
| 144 |
-
self.hidden_size = hidden_size
|
| 145 |
-
self.intermediate_size = intermediate_size
|
| 146 |
-
self.num_hidden_layers = num_hidden_layers
|
| 147 |
-
self.num_attention_heads = num_attention_heads
|
| 148 |
-
|
| 149 |
-
if num_key_value_heads is None:
|
| 150 |
-
num_key_value_heads = num_attention_heads
|
| 151 |
-
|
| 152 |
-
self.num_key_value_heads = num_key_value_heads
|
| 153 |
-
self.resid_pdrop = resid_pdrop
|
| 154 |
-
self.embd_pdrop = embd_pdrop
|
| 155 |
-
self.attention_dropout = attention_dropout
|
| 156 |
-
self.hidden_act = hidden_act
|
| 157 |
-
self.max_position_embeddings = max_position_embeddings
|
| 158 |
-
self.original_max_position_embeddings = original_max_position_embeddings
|
| 159 |
-
self.initializer_range = initializer_range
|
| 160 |
-
self.rms_norm_eps = rms_norm_eps
|
| 161 |
-
self.use_cache = use_cache
|
| 162 |
-
self.rope_theta = rope_theta
|
| 163 |
-
self.rope_scaling = rope_scaling
|
| 164 |
-
self.
|
| 165 |
-
self.
|
| 166 |
-
|
| 167 |
-
|
| 168 |
-
|
| 169 |
-
|
| 170 |
-
|
| 171 |
-
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-
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-
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-
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| 175 |
-
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-
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| 177 |
-
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| 178 |
-
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| 179 |
-
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| 180 |
-
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| 181 |
-
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| 182 |
-
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| 183 |
-
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| 184 |
-
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| 185 |
-
|
| 186 |
-
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| 187 |
-
|
| 188 |
-
|
| 189 |
-
|
| 190 |
-
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| 191 |
-
|
| 192 |
-
|
| 193 |
-
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| 194 |
-
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| 195 |
-
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| 196 |
-
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| 197 |
-
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| 198 |
-
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-
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| 200 |
-
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| 201 |
-
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| 202 |
-
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-
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-
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-
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-
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-
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-
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|
|
| 1 |
+
# coding=utf-8
|
| 2 |
+
# Copyright 2024 Microsoft and the HuggingFace Inc. team. All rights reserved.
|
| 3 |
+
#
|
| 4 |
+
# Licensed under the Apache License, Version 2.0 (the "License");
|
| 5 |
+
# you may not use this file except in compliance with the License.
|
| 6 |
+
# You may obtain a copy of the License at
|
| 7 |
+
#
|
| 8 |
+
# http://www.apache.org/licenses/LICENSE-2.0
|
| 9 |
+
#
|
| 10 |
+
# Unless required by applicable law or agreed to in writing, software
|
| 11 |
+
# distributed under the License is distributed on an "AS IS" BASIS,
|
| 12 |
+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
| 13 |
+
# See the License for the specific language governing permissions and
|
| 14 |
+
# limitations under the License.
|
| 15 |
+
|
| 16 |
+
""" Phi-3 model configuration"""
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
from transformers.configuration_utils import PretrainedConfig
|
| 20 |
+
from transformers.utils import logging
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
logger = logging.get_logger(__name__)
|
| 24 |
+
|
| 25 |
+
PHI3_PRETRAINED_CONFIG_ARCHIVE_MAP = {
|
| 26 |
+
"microsoft/Phi-3-mini-4k-instruct": "https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/resolve/main/config.json",
|
| 27 |
+
"microsoft/Phi-3-mini-128k-instruct": "https://huggingface.co/microsoft/Phi-3-mini-128k-instruct/resolve/main/config.json",
|
| 28 |
+
}
|
| 29 |
+
|
| 30 |
+
|
| 31 |
+
class Phi3Config(PretrainedConfig):
|
| 32 |
+
r"""
|
| 33 |
+
This is the configuration class to store the configuration of a [`Phi3Model`]. It is used to instantiate a Phi-3
|
| 34 |
+
model according to the specified arguments, defining the model architecture. Instantiating a configuration with the
|
| 35 |
+
defaults will yield a similar configuration to that of the
|
| 36 |
+
[microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct).
|
| 37 |
+
|
| 38 |
+
Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
|
| 39 |
+
documentation from [`PretrainedConfig`] for more information.
|
| 40 |
+
|
| 41 |
+
Args:
|
| 42 |
+
vocab_size (`int`, *optional*, defaults to 32064):
|
| 43 |
+
Vocabulary size of the Phi-3 model. Defines the number of different tokens that can be represented by the
|
| 44 |
+
`inputs_ids` passed when calling [`Phi3Model`].
|
| 45 |
+
hidden_size (`int`, *optional*, defaults to 3072):
|
| 46 |
+
Dimension of the hidden representations.
|
| 47 |
+
intermediate_size (`int`, *optional*, defaults to 8192):
|
| 48 |
+
Dimension of the MLP representations.
|
| 49 |
+
num_hidden_layers (`int`, *optional*, defaults to 32):
|
| 50 |
+
Number of hidden layers in the Transformer decoder.
|
| 51 |
+
num_attention_heads (`int`, *optional*, defaults to 32):
|
| 52 |
+
Number of attention heads for each attention layer in the Transformer decoder.
|
| 53 |
+
num_key_value_heads (`int`, *optional*):
|
| 54 |
+
This is the number of key_value heads that should be used to implement Grouped Query Attention. If
|
| 55 |
+
`num_key_value_heads=num_attention_heads`, the model will use Multi Head Attention (MHA), if
|
| 56 |
+
`num_key_value_heads=1 the model will use Multi Query Attention (MQA) otherwise GQA is used. When
|
| 57 |
+
converting a multi-head checkpoint to a GQA checkpoint, each group key and value head should be constructed
|
| 58 |
+
by meanpooling all the original heads within that group. For more details checkout [this
|
| 59 |
+
paper](https://arxiv.org/pdf/2305.13245.pdf). If it is not specified, will default to
|
| 60 |
+
`num_attention_heads`.
|
| 61 |
+
resid_pdrop (`float`, *optional*, defaults to 0.0):
|
| 62 |
+
Dropout probability for mlp outputs.
|
| 63 |
+
embd_pdrop (`int`, *optional*, defaults to 0.0):
|
| 64 |
+
The dropout ratio for the embeddings.
|
| 65 |
+
attention_dropout (`float`, *optional*, defaults to 0.0):
|
| 66 |
+
The dropout ratio after computing the attention scores.
|
| 67 |
+
hidden_act (`str` or `function`, *optional*, defaults to `"silu"`):
|
| 68 |
+
The non-linear activation function (function or string) in the decoder.
|
| 69 |
+
max_position_embeddings (`int`, *optional*, defaults to 4096):
|
| 70 |
+
The maximum sequence length that this model might ever be used with.
|
| 71 |
+
original_max_position_embeddings (`int`, *optional*, defaults to 4096):
|
| 72 |
+
The maximum sequence length that this model was trained with. This is used to determine the size of the
|
| 73 |
+
original RoPE embeddings when using long scaling.
|
| 74 |
+
initializer_range (`float`, *optional*, defaults to 0.02):
|
| 75 |
+
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
|
| 76 |
+
rms_norm_eps (`float`, *optional*, defaults to 1e-05):
|
| 77 |
+
The epsilon value used for the RMSNorm.
|
| 78 |
+
use_cache (`bool`, *optional*, defaults to `True`):
|
| 79 |
+
Whether or not the model should return the last key/values attentions (not used by all models). Only
|
| 80 |
+
relevant if `config.is_decoder=True`. Whether to tie weight embeddings or not.
|
| 81 |
+
tie_word_embeddings (`bool`, *optional*, defaults to `False`):
|
| 82 |
+
Whether to tie weight embeddings
|
| 83 |
+
rope_theta (`float`, *optional*, defaults to 10000.0):
|
| 84 |
+
The base period of the RoPE embeddings.
|
| 85 |
+
rope_scaling (`dict`, *optional*):
|
| 86 |
+
The scaling strategy for the RoPE embeddings. If `None`, no scaling is applied. If a dictionary, it must
|
| 87 |
+
contain the following keys: `type`, `short_factor` and `long_factor`. The `type` must be `longrope` and
|
| 88 |
+
the `short_factor` and `long_factor` must be lists of numbers with the same length as the hidden size
|
| 89 |
+
divided by the number of attention heads divided by 2.
|
| 90 |
+
bos_token_id (`int`, *optional*, defaults to 1):
|
| 91 |
+
The id of the "beginning-of-sequence" token.
|
| 92 |
+
eos_token_id (`int`, *optional*, defaults to 32000):
|
| 93 |
+
The id of the "end-of-sequence" token.
|
| 94 |
+
pad_token_id (`int`, *optional*, defaults to 32000):
|
| 95 |
+
The id of the padding token.
|
| 96 |
+
sliding_window (`int`, *optional*):
|
| 97 |
+
Sliding window attention window size. If `None`, no sliding window is applied.
|
| 98 |
+
|
| 99 |
+
Example:
|
| 100 |
+
|
| 101 |
+
```python
|
| 102 |
+
>>> from transformers import Phi3Model, Phi3Config
|
| 103 |
+
|
| 104 |
+
>>> # Initializing a Phi-3 style configuration
|
| 105 |
+
>>> configuration = Phi3Config.from_pretrained("microsoft/Phi-3-mini-4k-instruct")
|
| 106 |
+
|
| 107 |
+
>>> # Initializing a model from the configuration
|
| 108 |
+
>>> model = Phi3Model(configuration)
|
| 109 |
+
|
| 110 |
+
>>> # Accessing the model configuration
|
| 111 |
+
>>> configuration = model.config
|
| 112 |
+
```"""
|
| 113 |
+
|
| 114 |
+
model_type = "phi3"
|
| 115 |
+
keys_to_ignore_at_inference = ["past_key_values"]
|
| 116 |
+
|
| 117 |
+
def __init__(
|
| 118 |
+
self,
|
| 119 |
+
vocab_size=32064,
|
| 120 |
+
hidden_size=3072,
|
| 121 |
+
intermediate_size=8192,
|
| 122 |
+
num_hidden_layers=32,
|
| 123 |
+
num_attention_heads=32,
|
| 124 |
+
num_key_value_heads=None,
|
| 125 |
+
resid_pdrop=0.0,
|
| 126 |
+
embd_pdrop=0.0,
|
| 127 |
+
attention_dropout=0.0,
|
| 128 |
+
hidden_act="silu",
|
| 129 |
+
max_position_embeddings=4096,
|
| 130 |
+
original_max_position_embeddings=4096,
|
| 131 |
+
initializer_range=0.02,
|
| 132 |
+
rms_norm_eps=1e-5,
|
| 133 |
+
use_cache=True,
|
| 134 |
+
tie_word_embeddings=False,
|
| 135 |
+
rope_theta=10000.0,
|
| 136 |
+
rope_scaling=None,
|
| 137 |
+
bos_token_id=1,
|
| 138 |
+
eos_token_id=32000,
|
| 139 |
+
pad_token_id=32000,
|
| 140 |
+
sliding_window=None,
|
| 141 |
+
**kwargs,
|
| 142 |
+
):
|
| 143 |
+
self.vocab_size = vocab_size
|
| 144 |
+
self.hidden_size = hidden_size
|
| 145 |
+
self.intermediate_size = intermediate_size
|
| 146 |
+
self.num_hidden_layers = num_hidden_layers
|
| 147 |
+
self.num_attention_heads = num_attention_heads
|
| 148 |
+
|
| 149 |
+
if num_key_value_heads is None:
|
| 150 |
+
num_key_value_heads = num_attention_heads
|
| 151 |
+
|
| 152 |
+
self.num_key_value_heads = num_key_value_heads
|
| 153 |
+
self.resid_pdrop = resid_pdrop
|
| 154 |
+
self.embd_pdrop = embd_pdrop
|
| 155 |
+
self.attention_dropout = attention_dropout
|
| 156 |
+
self.hidden_act = hidden_act
|
| 157 |
+
self.max_position_embeddings = max_position_embeddings
|
| 158 |
+
self.original_max_position_embeddings = original_max_position_embeddings
|
| 159 |
+
self.initializer_range = initializer_range
|
| 160 |
+
self.rms_norm_eps = rms_norm_eps
|
| 161 |
+
self.use_cache = use_cache
|
| 162 |
+
self.rope_theta = rope_theta
|
| 163 |
+
self.rope_scaling = rope_scaling
|
| 164 |
+
self._rope_scaling_adjustment()
|
| 165 |
+
self._rope_scaling_validation()
|
| 166 |
+
self.sliding_window = sliding_window
|
| 167 |
+
|
| 168 |
+
super().__init__(
|
| 169 |
+
bos_token_id=bos_token_id,
|
| 170 |
+
eos_token_id=eos_token_id,
|
| 171 |
+
pad_token_id=pad_token_id,
|
| 172 |
+
tie_word_embeddings=tie_word_embeddings,
|
| 173 |
+
**kwargs,
|
| 174 |
+
)
|
| 175 |
+
|
| 176 |
+
def _rope_scaling_adjustment(self):
|
| 177 |
+
"""
|
| 178 |
+
Adjust the `type` of the `rope_scaling` configuration for backward compatibility.
|
| 179 |
+
"""
|
| 180 |
+
if self.rope_scaling is None:
|
| 181 |
+
return
|
| 182 |
+
|
| 183 |
+
rope_scaling_type = self.rope_scaling.get("type", None)
|
| 184 |
+
|
| 185 |
+
# For backward compatibility if previous version used "su" or "yarn"
|
| 186 |
+
if rope_scaling_type is not None and rope_scaling_type in ["su", "yarn"]:
|
| 187 |
+
self.rope_scaling["type"] = "longrope"
|
| 188 |
+
|
| 189 |
+
def _rope_scaling_validation(self):
|
| 190 |
+
"""
|
| 191 |
+
Validate the `rope_scaling` configuration.
|
| 192 |
+
"""
|
| 193 |
+
if self.rope_scaling is None:
|
| 194 |
+
return
|
| 195 |
+
|
| 196 |
+
if not isinstance(self.rope_scaling, dict) or len(self.rope_scaling) != 3:
|
| 197 |
+
raise ValueError(
|
| 198 |
+
"`rope_scaling` must be a dictionary with three fields, `type`, `short_factor` and `long_factor`, "
|
| 199 |
+
f"got {self.rope_scaling}"
|
| 200 |
+
)
|
| 201 |
+
rope_scaling_type = self.rope_scaling.get("type", None)
|
| 202 |
+
rope_scaling_short_factor = self.rope_scaling.get("short_factor", None)
|
| 203 |
+
rope_scaling_long_factor = self.rope_scaling.get("long_factor", None)
|
| 204 |
+
if rope_scaling_type is None or rope_scaling_type not in ["longrope"]:
|
| 205 |
+
raise ValueError(f"`rope_scaling`'s type field must be one of ['longrope'], got {rope_scaling_type}")
|
| 206 |
+
if not (
|
| 207 |
+
isinstance(rope_scaling_short_factor, list)
|
| 208 |
+
and all(isinstance(x, (int, float)) for x in rope_scaling_short_factor)
|
| 209 |
+
):
|
| 210 |
+
raise ValueError(
|
| 211 |
+
f"`rope_scaling`'s short_factor field must be a list of numbers, got {rope_scaling_short_factor}"
|
| 212 |
+
)
|
| 213 |
+
if not len(rope_scaling_short_factor) == self.hidden_size // self.num_attention_heads // 2:
|
| 214 |
+
raise ValueError(
|
| 215 |
+
f"`rope_scaling`'s short_factor field must have length {self.hidden_size // self.num_attention_heads // 2}, got {len(rope_scaling_short_factor)}"
|
| 216 |
+
)
|
| 217 |
+
if not (
|
| 218 |
+
isinstance(rope_scaling_long_factor, list)
|
| 219 |
+
and all(isinstance(x, (int, float)) for x in rope_scaling_long_factor)
|
| 220 |
+
):
|
| 221 |
+
raise ValueError(
|
| 222 |
+
f"`rope_scaling`'s long_factor field must be a list of numbers, got {rope_scaling_long_factor}"
|
| 223 |
+
)
|
| 224 |
+
if not len(rope_scaling_long_factor) == self.hidden_size // self.num_attention_heads // 2:
|
| 225 |
+
raise ValueError(
|
| 226 |
+
f"`rope_scaling`'s long_factor field must have length {self.hidden_size // self.num_attention_heads // 2}, got {len(rope_scaling_long_factor)}"
|
| 227 |
+
)
|