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BUT-FIT
/
DiCoW_v3_2

Automatic Speech Recognition
Transformers
Safetensors
DiCoW
speech
whisper
multilingual
speaker-diarization
meeting-transcription
BUT-FIT
custom_code
Model card Files Files and versions
xet
Community
2

Instructions to use BUT-FIT/DiCoW_v3_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use BUT-FIT/DiCoW_v3_2 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="BUT-FIT/DiCoW_v3_2", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModelForSpeechSeq2Seq
    model = AutoModelForSpeechSeq2Seq.from_pretrained("BUT-FIT/DiCoW_v3_2", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
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Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

fix: add compatibility with Transformers 4.55.0

1
#2 opened 28 days ago by
Yrooo

Original SE_DiCoW model missing from huggingface

1
#1 opened 3 months ago by
taavi223
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