+
    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MVP model configuration)Ústrict)ÚPreTrainedConfig)Úauto_docstringzRUCAIBox/mvp)Ú
checkpointc                   ó¾   a € ] tR t^t o RtRtR.tRRRRRR	/tR
tRt	^t
Rt^t^tRt^tRtRtRtRtRtRtRtRtRtRtRt^t^ t^tRt^tRt ^dt!Rt"Rt#Rt$V 3R lt%Rt&V t'R# )Ú	MvpConfiga„  
use_prompt (`bool`, *optional*, defaults to `False`):
    Whether or not to use prompt.
prompt_length (`int`, *optional*, defaults to 100):
    The length of prompt.
prompt_mid_dim (`int`, *optional*, defaults to 800):
    Dimensionality of the "intermediate" layer in prompt.

Example:

```python
>>> from transformers import MvpConfig, MvpModel

>>> # Initializing a MVP RUCAIBox/mvp style configuration
>>> configuration = MvpConfig()

>>> # Initializing a model (with random weights) from the RUCAIBox/mvp style configuration
>>> model = MvpModel(configuration)

>>> # Accessing the model configuration
>>> configuration = model.config
```ÚmvpÚpast_key_valuesÚnum_attention_headsÚencoder_attention_headsÚhidden_sizeÚd_modelÚnum_hidden_layersÚencoder_layersi[Ä  i   i   g        Úgelugš™™™™™¹?g{®Gáz”?FTi   c                ó.  <€ V ^8„  d   Qh/ S[ ;R&   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[S[ ,          ;R&   S[;R&   S[S[ ,          ;R&   S[;R&   S[;R&   S[ R,          ;R&   S[ R,          ;R&   S[ S[S[ ,          ,          R,          ;R&   S[;R&   S[ R,          ;R&   S[;R&   S[ ;R&   S[ ;R&   S[;R&   S[;R&   # )é   Ú
vocab_sizeÚmax_position_embeddingsr   Úencoder_ffn_dimr   Údecoder_layersÚdecoder_ffn_dimÚdecoder_attention_headsÚencoder_layerdropÚdecoder_layerdropÚactivation_functionr   ÚdropoutÚattention_dropoutÚactivation_dropoutÚinit_stdÚclassifier_dropoutÚscale_embeddingÚ	use_cacheNÚpad_token_idÚbos_token_idÚeos_token_idÚis_encoder_decoderÚdecoder_start_token_idÚ
use_promptÚprompt_lengthÚprompt_mid_dimÚ
is_decoderÚtie_word_embeddings)ÚintÚfloatÚstrÚboolÚlist)ÚformatÚ__classdict__s   "€Új/home/luca/screen-checking/.venv/lib/python3.14/site-packages/transformers/models/mvp/configuration_mvp.pyÚ__annotate__ÚMvpConfig.__annotate__   sé  ø‡ ‚ ñD ÑñE ñF !Ñ'ñG ñH ÑñI ñJ ÑñK ñL !Ñ%ñM ñN ÑñO ñP ÑñQ ñR !Ñ%ñS ñT ™s•{Ñ(ñU ñV ™s•{Ñ(ñW ñX Ñ%ñY ñZ Ññ[ ñ\ ‘S�[Ññ] ñ^ ™s•{Ñ(ñ_ ñ` ¡�Ñ)ña ñb Ññc ñd ¡�Ñ)ñe ñf Ñ!ñg ñh Ññi ñj ˜•*Ñ ñk ñl ˜•*Ñ ñm ñn ™™S�	•/ DÕ(Ñ,ño ñp Ñ#ñq ñr   $�JÑ*ñs ñt Ññu ñv Ññw ñx Ññy ñz Ññ{ ñ| Ñ$ò} ó    © N)(Ú__name__Ú
__module__Ú__qualname__Ú__firstlineno__Ú__doc__Ú
model_typeÚkeys_to_ignore_at_inferenceÚattribute_mapr   r   r   r   r   r   r   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__)r3   s   @r4   r   r      sÙ   ø‡ € ñð. €JØ#4Ð"5ÐàÐ8Ø�yØÐ-ð€Mð €JØ#'ÐØ€NØ€OØ#%ÐØ€NØ€OØ#%ÐØ%(ÐØ%(ÐØ%ÐØ€GØ€GØ%(ÐØ&)ÐØ€HØ&)ÐØ!€OØ€IØ €LØ €LØ+,€LØ#ÐØ)*ÐØ€JØ€MØ€NØ€JØ $Ð÷} ƒ r7   r   N)	r=   Úhuggingface_hub.dataclassesr   Úconfiguration_utilsr   Úutilsr   r   Ú__all__r8   r7   r4   Ú<module>rH      sF   ðñ å .å 3Ý #ñ ˜>Ô*Øô<%Ð ó <%ó ó +ð<%ð~ ˆ-‚r7   