# 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. """ALBERT model configuration""" from huggingface_hub.dataclasses import strict from ...configuration_utils import PreTrainedConfig from ...utils import auto_docstring @auto_docstring(checkpoint="albert/albert-xxlarge-v2") @strict class AlbertConfig(PreTrainedConfig): r""" num_hidden_groups (`int`, *optional*, defaults to 1): Number of groups for the hidden layers, parameters in the same group are shared. inner_group_num (`int`, *optional*, defaults to 1): The number of inner repetition of attention and ffn. Examples: ```python >>> from transformers import AlbertConfig, AlbertModel >>> # Initializing an ALBERT-xxlarge style configuration >>> albert_xxlarge_configuration = AlbertConfig() >>> # Initializing an ALBERT-base style configuration >>> albert_base_configuration = AlbertConfig( ... hidden_size=768, ... num_attention_heads=12, ... intermediate_size=3072, ... ) >>> # Initializing a model (with random weights) from the ALBERT-base style configuration >>> model = AlbertModel(albert_xxlarge_configuration) >>> # Accessing the model configuration >>> configuration = model.config ```""" model_type = "albert" vocab_size: int = 30000 embedding_size: int = 128 hidden_size: int = 4096 num_hidden_layers: int = 12 num_hidden_groups: int = 1 num_attention_heads: int = 64 intermediate_size: int = 16384 inner_group_num: int = 1 hidden_act: str = "gelu_new" hidden_dropout_prob: int | float = 0.0 attention_probs_dropout_prob: int | float = 0.0 max_position_embeddings: int = 512 type_vocab_size: int = 2 initializer_range: float = 0.02 layer_norm_eps: float = 1e-12 classifier_dropout_prob: int | float = 0.1 pad_token_id: int | None = 0 bos_token_id: int | None = 2 eos_token_id: int | list[int] | None = 3 tie_word_embeddings: bool = True __all__ = ["AlbertConfig"]