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efficient-speech
/
lite-whisper-large-v3

Automatic Speech Recognition
Transformers
Safetensors
lite-whisper
feature-extraction
audio
whisper
hf-asr-leaderboard
custom_code
Eval Results
Model card Files Files and versions
xet
Community
4

Instructions to use efficient-speech/lite-whisper-large-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use efficient-speech/lite-whisper-large-v3 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="efficient-speech/lite-whisper-large-v3", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("efficient-speech/lite-whisper-large-v3", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
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Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Add Open ASR Leaderboard evaluation results

#4 opened about 1 month ago by
SaylorTwift

Add Open ASR Leaderboard evaluation results

#3 opened about 1 month ago by
SaylorTwift

Improve model card: Add Acknowledgement and Citation sections

#2 opened 9 months ago by
nielsr
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