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    ‚ŠtjŽ  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LED model configurationé    )Ústricté   )ÚPreTrainedConfig)Úauto_docstringzallenai/led-base-16384)Ú
checkpointc                   óî  — e Zd ZU dZdZd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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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z  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         ez  ed,<   dZ%eed-<   d&S ).Ú	LEDConfigaú  
    max_encoder_position_embeddings (`int`, *optional*, defaults to 16384):
        The maximum sequence length that the encoder might ever be used with.
    max_decoder_position_embeddings (`int`, *optional*, defaults to 16384):
        The maximum sequence length that the decoder might ever be used with.
    attention_window (`int` or `list[int]`, *optional*, defaults to 512):
        Size of an attention window around each token. If an `int`, use the same size for all layers. To specify a
        different window size for each layer, use a `list[int]` where `len(attention_window) == num_hidden_layers`.

    Example:

    ```python
    >>> from transformers import LEDModel, LEDConfig

    >>> # Initializing a LED allenai/led-base-16384 style configuration
    >>> configuration = LEDConfig()

    >>> # Initializing a model from the allenai/led-base-16384 style configuration
    >>> model = LEDModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```ÚledÚencoder_attention_headsÚd_modelÚattention_dropoutÚinit_stdÚencoder_layers)Únum_attention_headsÚhidden_sizeÚattention_probs_dropout_probÚinitializer_rangeÚnum_hidden_layersiYÄ  Ú
vocab_sizei @  Úmax_encoder_position_embeddingsi   Úmax_decoder_position_embeddingsé   i   Úencoder_ffn_dimé   Údecoder_layersÚdecoder_ffn_dimÚdecoder_attention_headsg        Úencoder_layerdropÚdecoder_layerdropTÚ	use_cacheÚis_encoder_decoderÚgeluÚactivation_functiongš™™™™™¹?ÚdropoutÚactivation_dropoutg{®Gáz”?é   Údecoder_start_token_idÚclassifier_dropouté   NÚpad_token_idr   Úbos_token_idÚeos_token_idi   Úattention_windowÚ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   r   Úfloatr   r    Úboolr!   r#   Ústrr   r$   r   r%   r   r'   r(   r*   r+   r,   Úlistr-   r.   © ó    úg/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/transformers/models/led/configuration_led.pyr	   r	      s#  € € € € € € ðð ð0 €Jà8Ø Ø(;Ø'Ø-ðð €Mð €J�ÐÐÑØ+0Ð# SÐ0Ð0Ñ0Ø+/Ð# SÐ/Ð/Ñ/Ø€N�CÐÐÑØ€O�SÐÐÑØ#%Ð˜SÐ%Ð%Ñ%Ø€N�CÐÐÑØ€O�SÐÐÑØ#%Ð˜SÐ%Ð%Ñ%Ø%(Ð�u˜s‘{Ð(Ð(Ñ(Ø%(Ð�u˜s‘{Ð(Ð(Ñ(Ø€IˆtÐÐÑØ#Ð˜Ð#Ð#Ñ#Ø%Ð˜Ð%Ð%Ñ%Ø€GˆSÐÐÑØ€GˆU�S‰[ÐÐÑØ%(Ð�u˜s‘{Ð(Ð(Ñ(Ø&)Ð˜ ™Ð)Ð)Ñ)Ø€HˆeÐÐÑØ"#Ð˜CÐ#Ð#Ñ#Ø&)Ð˜ ™Ð)Ð)Ñ)Ø €L�#˜‘*Ð Ð Ñ Ø €L�#˜‘*Ð Ð Ñ Ø+,€L�#˜˜Sœ	‘/ DÑ(Ð,Ð,Ñ,Ø(+Ð�d˜3”i #‘oÐ+Ð+Ñ+Ø $Ð˜Ð$Ð$Ñ$Ð$Ð$r<   r	   N)	r2   Úhuggingface_hub.dataclassesr   Úconfiguration_utilsr   Úutilsr   r	   Ú__all__r;   r<   r=   ú<module>rB      s¡   ðð Ð à .Ð .Ð .Ð .Ð .Ð .à 3Ð 3Ð 3Ð 3Ð 3Ð 3Ø #Ð #Ð #Ð #Ð #Ð #ð €Ð3Ð4Ñ4Ô4Øð;%ð ;%ð ;%ð ;%ð ;%Ð ñ ;%ô ;%ñ „ñ 5Ô4ð;%ð| ˆ-€€€r<   