§
    ‚Štj¶  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CANINE model configurationé    )Ústricté   )ÚPreTrainedConfig)Úauto_docstringzgoogle/canine-s)Ú
checkpointc                   óR  — e Zd ZU dZd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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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"<   dZeed#<   d$Zeed%<   dS )&ÚCanineConfiga.  
    downsampling_rate (`int`, *optional*, defaults to 4):
        The rate at which to downsample the original character sequence length before applying the deep Transformer
        encoder.
    upsampling_kernel_size (`int`, *optional*, defaults to 4):
        The kernel size (i.e. the number of characters in each window) of the convolutional projection layer when
        projecting back from `hidden_size`*2 to `hidden_size`.
    num_hash_functions (`int`, *optional*, defaults to 8):
        The number of hash functions to use. Each hash function has its own embedding matrix.
    num_hash_buckets (`int`, *optional*, defaults to 16384):
        The number of hash buckets to use.
    local_transformer_stride (`int`, *optional*, defaults to 128):
        The stride of the local attention of the first shallow Transformer encoder. Defaults to 128 for good
        TPU/XLA memory alignment.

    Example:

    ```python
    >>> from transformers import CanineConfig, CanineModel

    >>> # Initializing a CANINE google/canine-s style configuration
    >>> configuration = CanineConfig()

    >>> # Initializing a model (with random weights) from the google/canine-s style configuration
    >>> model = CanineModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```Úcaninei   Úhidden_sizeé   Únum_hidden_layersÚnum_attention_headsi   Úintermediate_sizeÚgeluÚ
hidden_actgš™™™™™¹?Úhidden_dropout_probÚattention_probs_dropout_probi @  Úmax_position_embeddingsé   Útype_vocab_sizeg{®Gáz”?Úinitializer_rangegê-�™—q=Úlayer_norm_epsr   NÚpad_token_idi à  Úbos_token_idià  Úeos_token_idé   Údownsampling_rateÚupsampling_kernel_sizeé   Únum_hash_functionsÚnum_hash_bucketsé€   Úlocal_transformer_stride)Ú__name__Ú
__module__Ú__qualname__Ú__doc__Ú
model_typer   ÚintÚ__annotations__r   r   r   r   Ústrr   Úfloatr   r   r   r   r   r   r   r   Úlistr   r   r    r!   r#   © ó    úm/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/transformers/models/canine/configuration_canine.pyr	   r	      s|  € € € € € € ðð ð< €Jà€K�ÐÐÑØÐ�sÐÐÑØ!Ð˜Ð!Ð!Ñ!Ø!Ð�sÐ!Ð!Ñ!Ø€J�ÐÐÑØ'*Ð˜ ™Ð*Ð*Ñ*Ø03Ð  %¨#¡+Ð3Ð3Ñ3Ø#(Ð˜SÐ(Ð(Ñ(Ø€O�SÐÐÑØ#Ð�uÐ#Ð#Ñ#Ø!€N�EÐ!Ð!Ñ!Ø €L�#˜‘*Ð Ð Ñ Ø%€L�#˜‘*Ð%Ð%Ñ%Ø+1€L�#˜˜Sœ	‘/ DÑ(Ð1Ð1Ñ1ØÐ�sÐÐÑØ"#Ð˜CÐ#Ð#Ñ#ØÐ˜ÐÐÑØ!Ð�cÐ!Ð!Ñ!Ø$'Ð˜cÐ'Ð'Ñ'Ð'Ð'r/   r	   N)	r'   Úhuggingface_hub.dataclassesr   Úconfiguration_utilsr   Úutilsr   r	   Ú__all__r.   r/   r0   ú<module>r5      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3(ð 3(ð 3(ð 3(ð 3(Ð#ñ 3(ô 3(ñ „ñ .Ô-ð3(ðl Ð
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