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    ÜÓ^j†
  ã                   ój   — 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y
)zLUKE configurationé    )Ústricté   )ÚPreTrainedConfig)Úauto_docstringzstudio-ousia/luke-base)Ú
checkpointc                   ód  — 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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d<   dZeez  d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d&<   y)'Ú
LukeConfiga  
    entity_vocab_size (`int`, *optional*, defaults to 500000):
        Entity vocabulary size of the LUKE model. Defines the number of different entities that can be represented
        by the `entity_ids` passed when calling [`LukeModel`].
    entity_emb_size (`int`, *optional*, defaults to 256):
        The number of dimensions of the entity embedding.
    use_entity_aware_attention (`bool`, *optional*, defaults to `True`):
        Whether or not the model should use the entity-aware self-attention mechanism proposed in [LUKE: Deep
        Contextualized Entity Representations with Entity-aware Self-attention (Yamada et
        al.)](https://huggingface.co/papers/2010.01057).

    Examples:

    ```python
    >>> from transformers import LukeConfig, LukeModel

    >>> # Initializing a LUKE configuration
    >>> configuration = LukeConfig()

    >>> # Initializing a model from the configuration
    >>> model = LukeModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```Úlukei[Ä  Ú
vocab_sizei ¡ Úentity_vocab_sizei   Úhidden_sizeé   Úentity_emb_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_epsTÚuse_entity_aware_attentionNÚclassifier_dropouté   Úpad_token_idr   Úbos_token_idÚeos_token_idÚtie_word_embeddings)Ú__name__Ú
__module__Ú__qualname__Ú__doc__Ú
model_typer   ÚintÚ__annotations__r   r   r   r   r   r   r   Ústrr   Úfloatr   r   r   r   r   r   Úboolr   r    r!   r"   Úlistr#   © ó    úv/var/www/ramen.bs-engineer-server.com/venv/lib/python3.12/site-packages/transformers/models/luke/configuration_luke.pyr	   r	      s  … ñð4 €Jà€J�ÓØ#Ð�sÓ#Ø€K�ÓØ€O�SÓØÐ�sÓØ!Ð˜Ó!Ø!Ð�sÓ!Ø€J�ÓØ'*Ð˜ ™Ó*Ø03Ð  %¨#¡+Ó3Ø#&Ð˜SÓ&Ø€O�SÓØ#Ð�uÓ#Ø!€N�EÓ!Ø'+Ð Ó+Ø-1Ð˜ ™ dÑ*Ó1Ø €L�#˜‘*Ó Ø €L�#˜‘*Ó Ø+,€L�#˜˜S™	‘/ DÑ(Ó,Ø $Ð˜Ô$r0   r	   N)	r'   Úhuggingface_hub.dataclassesr   Úconfiguration_utilsr   Úutilsr   r	   Ú__all__r/   r0   r1   ú<module>r6      sG   ðñ å .å 3Ý #ñ Ð3Ô4Øô0%Ð!ó 0%ó ó 5ð0%ðf ˆ.�r0   