+
    œ°³jŠ	  ã                   ól   € R t ^ RIHt ^RIHt ^RIHt ]! RR7      ] ! R R]4      4       4       tR.tR# )	zLiLT configuration)Ústrict)ÚPreTrainedConfig)Úauto_docstringz!SCUT-DLVCLab/lilt-roberta-en-base)Ú
checkpointc                   ó|   a € ] tR t^t o RtRtRtRt^t^t	Rt
RtRtRtRt^tR	tR
t^ tRtRtRt^tRtV 3R ltRtV tR# )Ú
LiltConfiga  
channel_shrink_ratio (`int`, *optional*, defaults to 4):
    The shrink ratio compared to the `hidden_size` for the channel dimension of the layout embeddings.
max_2d_position_embeddings (`int`, *optional*, defaults to 1024):
    The maximum value that the 2D position embedding might ever be used with. Typically set this to something
    large just in case (e.g., 1024).

Examples:

```python
>>> from transformers import LiltConfig, LiltModel

>>> # Initializing a LiLT SCUT-DLVCLab/lilt-roberta-en-base style configuration
>>> configuration = LiltConfig()
>>> # Randomly initializing a model from the SCUT-DLVCLab/lilt-roberta-en-base style configuration
>>> model = LiltModel(configuration)
>>> # Accessing the model configuration
>>> configuration = model.config
```Úlilti:w  i   i   Úgelugš™™™™™¹?i   g{®Gáz”?gê-�™—q=Ni   c                óz  <€ V ^8„  d   Qh/ S[ ;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[;R&   S[S[ ,          ;R&   S[S[ ,          ;R&   S[ ;R	&   S[ ;R
&   S[;R&   S[;R&   S[ R,          ;R&   S[ R,          ;R&   S[ S[S[ ,          ,          R,          ;R&   S[S[ ,          R,          ;R&   S[ ;R&   S[ ;R&   # )é   Ú
vocab_sizeÚhidden_sizeÚnum_hidden_layersÚnum_attention_headsÚintermediate_sizeÚ
hidden_actÚhidden_dropout_probÚattention_probs_dropout_probÚmax_position_embeddingsÚtype_vocab_sizeÚinitializer_rangeÚlayer_norm_epsNÚpad_token_idÚbos_token_idÚeos_token_idÚclassifier_dropoutÚchannel_shrink_ratioÚmax_2d_position_embeddings)ÚintÚstrÚfloatÚlist)ÚformatÚ__classdict__s   "€Úl/home/luca/screen-checking/.venv/lib/python3.14/site-packages/transformers/models/lilt/configuration_lilt.pyÚ__annotate__ÚLiltConfig.__annotate__   s+  ø‡ ‚ ñ2 Ññ3 ñ4 Ññ5 ñ6 Ññ7 ñ8 Ñ!ñ9 ñ: Ñ!ñ; ñ< Ññ= ñ> ¡�Ñ*ñ? ñ@ #(©#¥+Ñ3ñA ñB !Ñ&ñC ñD ÑñE ñF Ñ#ñG ñH Ñ!ñI ñJ ˜•*Ñ ñK ñL ˜•*Ñ#ñM ñN ™™S�	•/ DÕ(Ñ/ñO ñP ¡� dÕ*Ñ1ñQ ñR Ñ!ñS ñT !$Ñ*òU ó    © )Ú__name__Ú
__module__Ú__qualname__Ú__firstlineno__Ú__doc__Ú
model_typer   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   Ú__annotate_func__Ú__static_attributes__Ú__classdictcell__)r#   s   @r$   r   r      s}   ø‡ € ñð( €Jà€JØ€KØÐØ!ÐØ!ÐØ€JØ'*ÐØ03Ð Ø#&ÐØ€OØ#ÐØ!€NØ €LØ#€LØ+/€LØ-1ÐØ !ÐØ&*Ð÷U ƒ r'   r   N)	r-   Úhuggingface_hub.dataclassesr   Úconfiguration_utilsr   Úutilsr   r   Ú__all__r(   r'   r$   Ú<module>r6      sH   ðñ å .å 3Ý #ñ Ð>Ô?Øô(+Ð!ó (+ó ó @ð(+ðV ˆ.‚r'   