Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing

  • Log In
  • Sign Up

efficient-speech
/
lite-whisper-tiny-fast

Automatic Speech Recognition
Transformers
Safetensors
lite-whisper
feature-extraction
audio
whisper
hf-asr-leaderboard
custom_code
Model card Files Files and versions
xet
Community
1

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

  • Libraries
  • Transformers

    How to use efficient-speech/lite-whisper-tiny-fast with Transformers:

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

Improve model card with abstract, detailed usage, and comprehensive benchmarks

#1 opened 8 months ago by
nielsr
Company
TOS Privacy About Careers
Website
Models Datasets Spaces Pricing Docs