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  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CodeGen model configurationé    )Ústricté   )ÚPreTrainedConfig)Úauto_docstringzSalesforce/codegen-2B-mono)Ú
checkpointc                   óX  — e Zd ZU dZdZdddddœ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d<   dZee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d<   dZedz  ed <   dZeee         z  dz  ed!<   d"Zeed#<   dS )$ÚCodeGenConfiga‚  
    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
    ```ÚcodegenÚn_positionsÚn_embdÚn_headÚn_layer)Úmax_position_embeddingsÚhidden_sizeÚnum_attention_headsÚnum_hidden_layersiàÄ  Ú
vocab_sizei   Ún_ctxi   é   é   é@   Ú
rotary_dimNÚn_innerÚgelu_newÚactivation_functiong        Úresid_pdropÚ
embd_pdropÚ
attn_pdropgñhãˆµøä>Úlayer_norm_epsilong{®Gáz”?Úinitializer_rangeTÚ	use_cacheiPÄ  Úbos_token_idÚeos_token_idFÚtie_word_embeddings)Ú__name__Ú
__module__Ú__qualname__Ú__doc__Ú
model_typeÚattribute_mapr   ÚintÚ__annotations__r   r   r   r   r   r   r   r   Ústrr   Úfloatr   r   r   r    r!   Úboolr"   r#   Úlistr$   © ó    úo/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/transformers/models/codegen/configuration_codegen.pyr	   r	      s‚  € € € € € € ðð ð0 €Jà#0ØØ'Ø&ð	ð €Mð €J�ÐÐÑØ€K�ÐÐÑØ€Eˆ3ÐÐÑØ€FˆCÐÐÑØ€GˆSÐÐÑØ€FˆCÐÐÑØ€J�ÐÐÑØ€GˆS�4‰ZÐÐÑØ)Ð˜Ð)Ð)Ñ)Ø"€K�˜‘Ð"Ð"Ñ"Ø!€J�˜‘Ð!Ð!Ñ!Ø!€J�˜‘Ð!Ð!Ñ!Ø $Ð˜Ð$Ð$Ñ$Ø#Ð�uÐ#Ð#Ñ#Ø€IˆtÐÐÑØ$€L�#˜‘*Ð$Ð$Ñ$Ø+0€L�#˜˜Sœ	‘/ DÑ(Ð0Ð0Ñ0Ø %Ð˜Ð%Ð%Ñ%Ð%Ð%r2   r	   N)	r(   Úhuggingface_hub.dataclassesr   Úconfiguration_utilsr   Úutilsr   r	   Ú__all__r1   r2   r3   ú<module>r8      s¢   ðð "Ð !à .Ð .Ð .Ð .Ð .Ð .à 3Ð 3Ð 3Ð 3Ð 3Ð 3Ø #Ð #Ð #Ð #Ð #Ð #ð €Ð7Ð8Ñ8Ô8Øð2&ð 2&ð 2&ð 2&ð 2&Ð$ñ 2&ô 2&ñ „ñ 9Ô8ð2&ðj Ð
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