+
    œ°³j  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MarkupLM model configuration)Ústrict)ÚPreTrainedConfig)Úauto_docstringzmicrosoft/markuplm-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^ t^tRtRt^ØtRt^ t^2tRtRtV 3R ltRtV tR# )ÚMarkupLMConfiga¸  
max_xpath_tag_unit_embeddings (`int`, *optional*, defaults to 256):
    The maximum value that the xpath tag unit embedding might ever use. Typically set this to something large
    just in case (e.g., 256).
max_xpath_subs_unit_embeddings (`int`, *optional*, defaults to 1024):
    The maximum value that the xpath subscript unit embedding might ever use. Typically set this to something
    large just in case (e.g., 1024).
tag_pad_id (`int`, *optional*, defaults to 216):
    The id of the padding token in the xpath tags.
subs_pad_id (`int`, *optional*, defaults to 1001):
    The id of the padding token in the xpath subscripts.
xpath_unit_hidden_size (`int`, *optional*, defaults to 32):
    The hidden size of each unit in xpath.
max_depth (`int`, *optional*, defaults to 50):
    The maximum depth in xpath.

Examples:

```python
>>> from transformers import MarkupLMModel, MarkupLMConfig

>>> # Initializing a MarkupLM microsoft/markuplm-base style configuration
>>> configuration = MarkupLMConfig()

>>> # Initializing a model from the microsoft/markuplm-base style configuration
>>> model = MarkupLMModel(configuration)

>>> # Accessing the model configuration
>>> configuration = model.config
```Úmarkuplmi:w  i   i   Úgelugš™™™™™¹?i   g{®Gáz”?gê-�™—q=é   i   ié  TNc                ó¶  <€ 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[ ;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[;R&   S[S[ ,          R,          ;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max_xpath_tag_unit_embeddingsÚmax_xpath_subs_unit_embeddingsÚ
tag_pad_idÚsubs_pad_idÚxpath_unit_hidden_sizeÚ	max_depthÚ	use_cacheÚclassifier_dropout)ÚintÚstrÚfloatÚlistÚbool)ÚformatÚ__classdict__s   "€Út/home/luca/screen-checking/.venv/lib/python3.14/site-packages/transformers/models/markuplm/configuration_markuplm.pyÚ__annotate__ÚMarkupLMConfig.__annotate__   s„  ø‡ ‚ ñH ÑñI ñJ ÑñK ñL ÑñM ñN Ñ!ñO ñP Ñ!ñQ ñR ÑñS ñT ¡�Ñ*ñU ñV #(©#¥+Ñ3ñW ñX !Ñ&ñY ñZ Ññ[ ñ\ Ñ#ñ] ñ^ Ñ!ñ_ ñ` ˜•*Ñ ña ñb ˜•*Ñ ñc ñd ™™S�	•/ DÕ(Ñ,ñe ñf $'Ñ,ñg ñh %(Ñ.ñi ñj Ññk ñl Ññm ñn  Ñ$ño ñp Ññq ñr Ññs ñt ¡� dÕ*Ñ1òu 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   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),Ð!Ø*.Ð"Ø€JØ€KØ"$ÐØ€IØ€IØ-1Ð÷u ƒ r.   r   N)	r4   Úhuggingface_hub.dataclassesr   Úconfiguration_utilsr   Úutilsr   r   Ú__all__r/   r.   r+   Ú<module>r=      sH   ðñ #å .å 3Ý #ñ Ð4Ô5Øô82Ð%ó 82ó ó 6ð82ðv Ð
‚r.   