+
    œ°³j³
  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DistilBERT model configuration)Ústrict)ÚPreTrainedConfig)Úauto_docstringzgoogle/distilbert-base-uncased)Ú
checkpointc                   óˆ   a € ] tR t^t o RtRtRRRRRR/tR	tR
tRt	^t
^tRtRtRtRtRtRtRtRt^ tRtRtRtV 3R ltRtV tR# )ÚDistilBertConfiga±  
sinusoidal_pos_embds (`boolean`, *optional*, defaults to `False`):
    Whether to use sinusoidal positional embeddings.
dim (`int`, *optional*, defaults to 768):
    Dimensionality of the encoder layers and the pooler layer.
qa_dropout (`float`, *optional*, defaults to 0.1):
    The dropout probabilities used in the question answering model [`DistilBertForQuestionAnswering`].
seq_classif_dropout (`float`, *optional*, defaults to 0.2):
    The dropout probabilities used in the sequence classification and the multiple choice model
    [`DistilBertForSequenceClassification`].

Examples:

```python
>>> from transformers import DistilBertConfig, DistilBertModel

>>> # Initializing a DistilBERT configuration
>>> configuration = DistilBertConfig()

>>> # Initializing a model (with random weights) from the configuration
>>> model = DistilBertModel(configuration)

>>> # Accessing the model configuration
>>> configuration = model.config
```Ú
distilbertÚhidden_sizeÚdimÚnum_attention_headsÚn_headsÚnum_hidden_layersÚn_layersi:w  i   Fi   gš™™™™™¹?Úgelug{®Gáz”?gš™™™™™É?NTc                óp  <€ V ^8„  d   Qh/ S[ ;R&   S[ ;R&   S[;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[S[ ,          ;R&   S[S[ ,          ;R	&   S[;R
&   S[;R&   S[S[ ,          ;R&   S[S[ ,          ;R&   S[ R,          ;R&   S[ S[S[ ,          ,          R,          ;R&   S[ R,          ;R&   S[;R&   # )é   Ú
vocab_sizeÚmax_position_embeddingsÚsinusoidal_pos_embdsr   r   r
   Ú
hidden_dimÚdropoutÚattention_dropoutÚ
activationÚinitializer_rangeÚ
qa_dropoutÚseq_classif_dropoutNÚpad_token_idÚeos_token_idÚbos_token_idÚtie_word_embeddings)ÚintÚboolÚfloatÚstrÚlist)ÚformatÚ__classdict__s   "€Úx/home/luca/screen-checking/.venv/lib/python3.14/site-packages/transformers/models/distilbert/configuration_distilbert.pyÚ__annotate__ÚDistilBertConfig.__annotate__   s(  ø‡ ‚ ñH ÑñI ñJ !Ñ&ñK ñL Ñ&ñM ñN ÑñO ñP ÑñQ ñR 
�NñS ñT ÑñU ñV ‘S�[ÑñW ñX ™s•{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$òi ó    © i   )Ú__name__Ú
__module__Ú__qualname__Ú__firstlineno__Ú__doc__Ú
model_typeÚattribute_mapr   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      sŒ   ø‡ € ñð4 €Jà�uØ˜yØ˜Zð€Mð €JØ#&ÐØ!&ÐØ€HØ€GØ€CØ€JØ€GØ%(ÐØ€JØ#ÐØ!€JØ'*ÐØ €LØ+/€LØ#€LØ $Ð÷i ƒ r*   r   N)	r0   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;Ô<Øô2%Ð'ó 2%ó ó =ð2%ðj Ð
‚r*   