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efficient-speech
/
lite-whisper-tiny

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 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use efficient-speech/lite-whisper-tiny 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", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("efficient-speech/lite-whisper-tiny", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
lite-whisper-tiny
Ctrl+K
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  • 1 contributor
History: 4 commits
eyoel-gebre's picture
eyoel-gebre
Update README.md
ef17f27 verified about 1 year ago
  • .gitattributes
    1.52 kB
    initial commit about 1 year ago
  • README.md
    3.11 kB
    Update README.md about 1 year ago
  • config.json
    1.92 kB
    Upload LiteWhisperForConditionalGeneration about 1 year ago
  • configuration_lite_whisper.py
    307 Bytes
    Upload LiteWhisperForConditionalGeneration about 1 year ago
  • generation_config.json
    1.27 kB
    Upload LiteWhisperForConditionalGeneration about 1 year ago
  • model.safetensors
    228 MB
    xet
    Upload LiteWhisperForConditionalGeneration about 1 year ago
  • modeling_lite_whisper.py
    2.86 kB
    Upload LiteWhisperForConditionalGeneration about 1 year ago