§
    ‚Štj¾  ã                   ó„   — d Z ddlmZ ddlmZ ddlmZ  ed¬¦  «        e G d„ d	e¦  «        ¦   «         ¦   «         Zd	gZd
S )zOPT model configurationé    )Ústricté   )ÚPreTrainedConfig)Úauto_docstringzfacebook/opt-350m)Ú
checkpointc                   ó�  ‡ — e Zd ZU dZdZdgZdZeed<   dZ	eed<   dZ
eed	<   d
Zeed<   dZeed<   dZeed<   dZeed<   dZedz  ed<   dZeez  ed<   dZeez  ed<   dZeed<   dZeed<   dZeez  ed<   dZeed<   dZeed<   dZedz  ed <   d!Zedz  ed"<   d!Zeee         z  dz  ed#<   dZeed$<   dZeed%<   dZ eed&<   ˆ fd'„Z!ˆ xZ"S )(Ú	OPTConfiga  
    do_layer_norm_before (`bool`, *optional*, defaults to `True`):
        Whether to perform layer normalization before the attention block.
    word_embed_proj_dim (`int`, *optional*):
        `word_embed_proj_dim` can be set to down-project word embeddings, *e.g.* `opt-350m`. Defaults to
        `hidden_size`.
    enable_bias (`bool`, *optional*, defaults to `True`):
        Whether or not if the linear layers in the attention blocks should use the bias term.
    layer_norm_elementwise_affine (`bool`, *optional*, defaults to `True`):
        Whether or not if the layer norms should have learnable parameters.

    Example:

    ```python
    >>> from transformers import OPTConfig, OPTModel

    >>> # Initializing a OPT facebook/opt-large style configuration
    >>> configuration = OPTConfig()

    >>> # Initializing a model (with random weights) from the facebook/opt-large style configuration
    >>> model = OPTModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```ÚoptÚpast_key_valuesi`Ä  Ú
vocab_sizei   Úhidden_sizeé   Únum_hidden_layersi   Úffn_dimi   Úmax_position_embeddingsTÚdo_layer_norm_beforeFÚ_remove_final_layer_normNÚword_embed_proj_dimgš™™™™™¹?Údropoutg        Úattention_dropoutÚnum_attention_headsÚreluÚactivation_functionÚ	layerdropg{®Gáz”?Úinit_stdÚ	use_cacheé   Úpad_token_idé   Úbos_token_idÚeos_token_idÚenable_biasÚlayer_norm_elementwise_affineÚtie_word_embeddingsc                 ón   •— | j         �| j         n| j        | _          t          ¦   «         j        di |¤Ž d S )N© )r   r   ÚsuperÚ__post_init__)ÚselfÚkwargsÚ	__class__s     €úg/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/transformers/models/opt/configuration_opt.pyr(   zOPTConfig.__post_init__L   sG   ø€ à(,Ô(@Ð(LˆDÔ$Ð$ÐRVÔRbð 	Ô ð 	�‰ŒÔÐ'Ð' Ð'Ð'Ð'Ð'Ð'ó    )#Ú__name__Ú
__module__Ú__qualname__Ú__doc__Ú
model_typeÚkeys_to_ignore_at_inferencer   ÚintÚ__annotations__r   r   r   r   r   Úboolr   r   r   Úfloatr   r   r   Ústrr   r   r   r   r    r!   Úlistr"   r#   r$   r(   Ú__classcell__)r+   s   @r,   r	   r	      sÓ  ø€ € € € € € ðð ð4 €JØ#4Ð"5Ðà€J�ÐÐÑØ€K�ÐÐÑØÐ�sÐÐÑØ€GˆSÐÐÑØ#'Ð˜SÐ'Ð'Ñ'Ø!%Ð˜$Ð%Ð%Ñ%Ø%*Ð˜dÐ*Ð*Ñ*Ø&*Ð˜˜t™Ð*Ð*Ñ*Ø€GˆU�S‰[ÐÐÑØ%(Ð�u˜s‘{Ð(Ð(Ñ(Ø!Ð˜Ð!Ð!Ñ!Ø%Ð˜Ð%Ð%Ñ%Ø €Iˆu�s‰{Ð Ð Ñ Ø€HˆeÐÐÑØ€IˆtÐÐÑØ €L�#˜‘*Ð Ð Ñ Ø €L�#˜‘*Ð Ð Ñ Ø+,€L�#˜˜Sœ	‘/ DÑ(Ð,Ð,Ñ,Ø€K�ÐÐÑØ*.Ð! 4Ð.Ð.Ñ.Ø $Ð˜Ð$Ð$Ñ$ð(ð (ð (ð (ð (ð (ð (ð (ð (r-   r	   N)	r1   Úhuggingface_hub.dataclassesr   Úconfiguration_utilsr   Úutilsr   r	   Ú__all__r&   r-   r,   ú<module>r?      s¡   ðð Ð à .Ð .Ð .Ð .Ð .Ð .à 3Ð 3Ð 3Ð 3Ð 3Ð 3Ø #Ð #Ð #Ð #Ð #Ð #ð €Ð.Ð/Ñ/Ô/Øð8(ð 8(ð 8(ð 8(ð 8(Ð ñ 8(ô 8(ñ „ñ 0Ô/ð8(ðv ˆ-€€€r-   