+
    œ°³jd  ã                   ó²   € ^ RI Ht ^RIHt ^RIHt ^RIHtHt ]! RR7      ] ! R R]4      4       4       t	]! RR7      ] ! R	 R
]4      4       4       t
RR
.tR# )é    )Ústrict)ÚPreTrainedConfig)Úauto_docstring)ÚCONFIG_MAPPINGÚ
AutoConfigzmistralai/Voxtral-Mini-3B-2507)Ú
checkpointc            
       ó„   a € ] tR t^t o RtRtRRRRRRR	R
RR/tRtRtRt	^ t
^tRtRt^€tRtRtRtRtRtRtV 3R ltRtV tR# )ÚVoxtralEncoderConfigaü  
max_source_positions (`int`, *optional*, defaults to 1500):
    The maximum sequence length of log-mel filter-bank features that this model might ever be used with.

```python
>>> from transformers import VoxtralEncoderConfig, VoxtralEncoder

>>> # Initializing a VoxtralEncoderConfig
>>> configuration = VoxtralEncoderConfig()

>>> # Initializing a VoxtralEncoder (with random weights)
>>> model = VoxtralEncoder(configuration)

>>> # Accessing the model configuration
>>> configuration = model.config
```
Úvoxtral_encoderÚd_modelÚhidden_sizeÚencoder_layersÚnum_hidden_layersÚencoder_attention_headsÚnum_attention_headsÚencoder_ffn_dimÚintermediate_sizeÚencoder_layerdropÚ	layerdropišÊ  i   i   FÚgeluiÜ  g{®Gáz”?g        c                ó  <€ V ^8„  d   Qh/ S[ ;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[;R&   S[;R&   S[ ;R&   S[ ;R	&   S[;R
&   S[S[ ,          ;R&   S[S[ ,          ;R&   S[S[ ,          ;R&   S[S[ ,          ;R&   # )é   Ú
vocab_sizer   r   r   r   Úscale_embeddingÚactivation_functionÚnum_mel_binsÚmax_source_positionsÚinitializer_rangeÚattention_dropoutÚdropoutr   Úactivation_dropout)ÚintÚboolÚstrÚfloat)ÚformatÚ__classdict__s   "€Úr/home/luca/screen-checking/.venv/lib/python3.14/site-packages/transformers/models/voxtral/configuration_voxtral.pyÚ__annotate__Ú!VoxtralEncoderConfig.__annotate__   så   ø‡ ‚ ñ> Ññ? ñ@ ÑñA ñB Ñ!ñC ñD ÑñE ñF Ñ!ñG ñH Ñ!ñI ñJ Ñ%ñK ñL ÑñM ñN Ñ$ñO ñP Ñ#ñQ ñR ™s•{Ñ(ñS ñ\ ‘S�[Ññ] ñ^ ‘s�{Ñ ñ_ ñ` ¡�Ñ)òa ó    © N)Ú__name__Ú
__module__Ú__qualname__Ú__firstlineno__Ú__doc__Ú
model_typeÚattribute_mapr   r   r   r   r   r   r   r   r   r   r   r    r   r!   Ú__annotate_func__Ú__static_attributes__Ú__classdictcell__)r'   s   @r(   r
   r
      s�   ø‡ € ñð$ #€Jð 	�=ØÐ-Ø!Ð#8ØÐ.Ø˜[ð€Mð €JØ€KØ!ÐØÐØ!ÐØ!€OØ%ÐØ€LØ $ÐØ#ÐØ%(Ðð
 €GØ €IØ&)Ð÷a ƒ r+   r
   c                   óŽ   a a€ ] tR t^Jt oRtRtR]R]/tRRRRR	R
R^R^RRRRRRRRR^€/
tRt	Rt
RtRtV 3R ltV3R ltRtVtV ;t# )ÚVoxtralConfigaš  
Example:

```python
>>> from transformers import VoxtralForConditionalGeneration, VoxtralConfig

>>> # Initializing a Voxtral configuration
>>> configuration = VoxtralConfig(audio_token_id=24, projector_hidden_act="gelu")

>>> # Initializing a 3B model with random weights
>>> model = VoxtralForConditionalGeneration(configuration)

>>> # Accessing the model configuration
>>> configuration = model.config
```ÚvoxtralÚtext_configÚaudio_configr   i   r   i   r   i    r   Únum_key_value_headsÚmax_position_embeddingsÚrms_norm_epsgñhãˆµøä>Ú	use_cacheTÚ
rope_thetag    „×—AÚhead_dimNr   c                ó  <€ \        V P                  \        4      '       d^   V P                  P                  R R4      V P                  R &   \        V P                  R ,          ,          ! R/ V P                  B V n        M%V P                  f   \        R,          ! 4       V n        \        V P
                  \        4      '       dl   V P
                  P                  R R4      V P
                  R &   \        V P
                  R ,          ,          ! R/ / V P                  CV P
                  CB V n        M0V P
                  f#   \        R,          ! R/ V P                  B V n        V P
                  P                  V n        \        SV `$  ! R/ VB  R# )r2   r   NÚllamar,   )
Ú
isinstancer;   ÚdictÚgetr   r:   Ú_default_text_config_kwargsr   ÚsuperÚ__post_init__)ÚselfÚkwargsÚ	__class__s   &,€r(   rI   ÚVoxtralConfig.__post_init__r   s=  ø€ Ü�d×'Ñ'¬×.Ò.Ø.2×.?Ñ.?×.CÑ.CÀLÐRcÓ.dˆD×Ñ˜lÑ+Ü .¨t×/@Ñ/@ÀÕ/NÖ OÑ dÐRV×RcÑRcÑ dˆDÕØ×ÑÒ&Ü .Ð/@Ö AÓ CˆDÔä�d×&Ñ&¬×-Ò-Ø-1×-=Ñ-=×-AÑ-AÀ,ÐPWÓ-XˆD×Ñ˜\Ñ*Ü-¨d×.>Ñ.>¸|Õ.LÖMñ  ØJ�T×5Ñ5ÐJ¸×9IÑ9IÐJñ ˆDÕð ×ÑÒ%Ü-¨gÖ6ÑZ¸×9YÑ9YÑZˆDÔà×+Ñ+×7Ñ7ˆÔÜ‰ÒÑ' Ô'r+   c                ó”   <€ V ^8„  d   Qh/ S[ S[,          R,          ;R&   S[ S[,          R,          ;R&   S[R,          ;R&   S[;R&   # )r   Nr;   r:   Úaudio_token_idÚprojector_hidden_act)rE   r   r"   r$   )r&   r'   s   "€r(   r)   ÚVoxtralConfig.__annotate__J   s[   ø‡ ‚ ñF Ñ)Õ)¨DÕ0Ñ7ñG ñH Ñ(Õ(¨4Õ/Ñ6ñI ñJ ˜$•JÑ%ñK ñL Ñ&òM r+   )r;   r   r:   )r-   r.   r/   r0   r1   r2   r   Úsub_configsrG   r;   r:   rO   rP   rI   r4   r5   r6   Ú__classcell__)rL   r'   s   @@r(   r8   r8   J   s   ù‡ € ñð  €JØ  *¨n¸jÐI€Kð 	�fØ�tØ˜TØ˜RØ˜qØ! 6Ø˜Ø�TØ�kØ�Cð#Ðð 48€LØ26€KØ!%€NØ &Ðõ(÷Q … r+   r8   N)Úhuggingface_hub.dataclassesr   Úconfiguration_utilsr   Úutilsr   Úautor   r   r
   r8   Ú__all__r,   r+   r(   Ú<module>rY      su   ðõ  /å 3Ý #ß -ñ Ð;Ô<Øô.*Ð+ó .*ó ó =ð.*ñb Ð;Ô<Øô6(Ð$ó 6(ó ó =ð6(ðr " ?Ð
3‚r+   