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- # Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
- # Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- """BERT model configuration"""
- from huggingface_hub.dataclasses import strict
- from ...configuration_utils import PreTrainedConfig
- from ...utils import auto_docstring
- @auto_docstring(checkpoint="google-bert/bert-base-uncased")
- @strict
- class BertConfig(PreTrainedConfig):
- r"""
- Examples:
- ```python
- >>> from transformers import BertConfig, BertModel
- >>> # Initializing a BERT google-bert/bert-base-uncased style configuration
- >>> configuration = BertConfig()
- >>> # Initializing a model (with random weights) from the google-bert/bert-base-uncased style configuration
- >>> model = BertModel(configuration)
- >>> # Accessing the model configuration
- >>> configuration = model.config
- ```"""
- model_type = "bert"
- vocab_size: int = 30522
- hidden_size: int = 768
- num_hidden_layers: int = 12
- num_attention_heads: int = 12
- intermediate_size: int = 3072
- hidden_act: str = "gelu"
- hidden_dropout_prob: float | int = 0.1
- attention_probs_dropout_prob: float | int = 0.1
- max_position_embeddings: int = 512
- type_vocab_size: int = 2
- initializer_range: float = 0.02
- layer_norm_eps: float = 1e-12
- pad_token_id: int | None = 0
- use_cache: bool = True
- classifier_dropout: float | int | None = None
- is_decoder: bool = False
- add_cross_attention: bool = False
- bos_token_id: int | None = None
- eos_token_id: int | list[int] | None = None
- tie_word_embeddings: bool = True
- __all__ = ["BertConfig"]
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