U ,-e@sDdZddlmZddlmZeeZdddZGdddeZ d S) z Mistral model configuration)PretrainedConfig)loggingzIhttps://huggingface.co/mistralai/Mistral-7B-v0.1/resolve/main/config.jsonzRhttps://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1/resolve/main/config.json)zmistralai/Mistral-7B-v0.1z"mistralai/Mistral-7B-Instruct-v0.1cs,eZdZdZdZdgZdfdd ZZS) MistralConfiga> This is the configuration class to store the configuration of a [`MistralModel`]. It is used to instantiate an Mistral model according to the specified arguments, defining the model architecture. Instantiating a configuration with the defaults will yield a similar configuration to that of the Mistral-7B-v0.1 or Mistral-7B-Instruct-v0.1. [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PretrainedConfig`] for more information. Args: vocab_size (`int`, *optional*, defaults to 32000): Vocabulary size of the Mistral model. Defines the number of different tokens that can be represented by the `inputs_ids` passed when calling [`MistralModel`] hidden_size (`int`, *optional*, defaults to 4096): Dimension of the hidden representations. intermediate_size (`int`, *optional*, defaults to 14336): Dimension of the MLP representations. num_hidden_layers (`int`, *optional*, defaults to 32): Number of hidden layers in the Transformer encoder. num_attention_heads (`int`, *optional*, defaults to 32): Number of attention heads for each attention layer in the Transformer encoder. num_key_value_heads (`int`, *optional*, defaults to 8): This is the number of key_value heads that should be used to implement Grouped Query Attention. If `num_key_value_heads=num_attention_heads`, the model will use Multi Head Attention (MHA), if `num_key_value_heads=1 the model will use Multi Query Attention (MQA) otherwise GQA is used. When converting a multi-head checkpoint to a GQA checkpoint, each group key and value head should be constructed by meanpooling all the original heads within that group. For more details checkout [this paper](https://arxiv.org/pdf/2305.13245.pdf). If it is not specified, will default to `8`. hidden_act (`str` or `function`, *optional*, defaults to `"silu"`): The non-linear activation function (function or string) in the decoder. max_position_embeddings (`int`, *optional*, defaults to 4096*32): The maximum sequence length that this model might ever be used with. Mistral's sliding window attention allows sequence of up to 4096*32 tokens. initializer_range (`float`, *optional*, defaults to 0.02): The standard deviation of the truncated_normal_initializer for initializing all weight matrices. rms_norm_eps (`float`, *optional*, defaults to 1e-12): The epsilon used by the rms normalization layers. use_cache (`bool`, *optional*, defaults to `True`): Whether or not the model should return the last key/values attentions (not used by all models). Only relevant if `config.is_decoder=True`. tie_word_embeddings(`bool`, *optional*, defaults to `False`): Whether to tie weight embeddings rope_theta (`float`, *optional*, defaults to 10000.0): The base period of the RoPE embeddings. sliding_window (`int`, *optional*, defaults to 4096): Sliding window attention window size. If not specified, will default to `4096`. Example: ```python >>> from transformers import MistralModel, MistralConfig >>> # Initializing a Mistral 7B style configuration >>> configuration = MistralConfig() >>> # Initializing a model from the Mistral 7B style configuration >>> model = MistralModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```ZmistralZpast_key_values}8 silu{Gz?ư>TNF@c sz||_||_||_||_||_||_||_|dkr6|}||_||_| |_ | |_ | |_ ||_ t jf| | ||d|dS)N) pad_token_id bos_token_id eos_token_idtie_word_embeddings) vocab_sizemax_position_embeddings hidden_sizeintermediate_sizenum_hidden_layersnum_attention_headssliding_windownum_key_value_heads hidden_actinitializer_range rms_norm_eps use_cache rope_thetasuper__init__)selfrrrrrrrrrrr rrrrr!rkwargs __class__r/var/www/html/Darija-Ai-Train/env/lib/python3.8/site-packages/transformers/models/mistral/configuration_mistral.pyr#bs.zMistralConfig.__init__)rrrrrr r r r r TNrrFrr)__name__ __module__ __qualname____doc__Z model_typeZkeys_to_ignore_at_inferencer# __classcell__r(r(r&r)rs*ArN) r-Zconfiguration_utilsrutilsrZ get_loggerr*loggerZ%MISTRAL_PRETRAINED_CONFIG_ARCHIVE_MAPrr(r(r(r)s