# Copyright 2022 Salesforce authors, The EleutherAI, and HuggingFace Teams. 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. """CodeGen model configuration""" from huggingface_hub.dataclasses import strict from ...configuration_utils import PreTrainedConfig from ...utils import auto_docstring @auto_docstring(checkpoint="Salesforce/codegen-2B-mono") @strict class CodeGenConfig(PreTrainedConfig): r""" n_ctx (`int`, *optional*, defaults to 2048): This attribute is used in `CodeGenModel.__init__` without any real effect. The dropout probability for all fully connected layers in the embeddings, encoder, and pooler. rotary_dim (`int`, *optional*, defaults to 64): Number of dimensions in the embedding that Rotary Position Embedding is applied to. n_inner (`int`, *optional*): Dimensionality of the inner feed-forward layers. `None` will set it to 4 times n_embd Example: ```python >>> from transformers import CodeGenConfig, CodeGenModel >>> # Initializing a CodeGen 6B configuration >>> configuration = CodeGenConfig() >>> # Initializing a model (with random weights) from the configuration >>> model = CodeGenModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```""" model_type = "codegen" attribute_map = { "max_position_embeddings": "n_positions", "hidden_size": "n_embd", "num_attention_heads": "n_head", "num_hidden_layers": "n_layer", } vocab_size: int = 50400 n_positions: int = 2048 n_ctx: int = 2048 n_embd: int = 4096 n_layer: int = 28 n_head: int = 16 rotary_dim: int = 64 n_inner: int | None = None activation_function: str = "gelu_new" resid_pdrop: float | int = 0.0 embd_pdrop: float | int = 0.0 attn_pdrop: float | int = 0.0 layer_norm_epsilon: float = 1e-5 initializer_range: float = 0.02 use_cache: bool = True bos_token_id: int | None = 50256 eos_token_id: int | list[int] | None = 50256 tie_word_embeddings: bool = False __all__ = ["CodeGenConfig"]