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njeffrie
/
moonshine-tiny

Feature Extraction
Transformers
Safetensors
moonshine
custom_code
Model card Files Files and versions
xet
Community

Instructions to use njeffrie/moonshine-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use njeffrie/moonshine-tiny with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="njeffrie/moonshine-tiny", trust_remote_code=True)
    # Load model directly
    from transformers import AutoProcessor, AutoModel
    
    processor = AutoProcessor.from_pretrained("njeffrie/moonshine-tiny", trust_remote_code=True)
    model = AutoModel.from_pretrained("njeffrie/moonshine-tiny", trust_remote_code=True)
  • Notebooks
  • Google Colab
  • Kaggle
moonshine-tiny
190 MB
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  • 1 contributor
History: 6 commits
njeffrie's picture
njeffrie
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94ea1db verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • README.md
    5.17 kB
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  • config.json
    450 Bytes
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  • configuration_moonshine.py
    926 Bytes
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  • model.safetensors
    186 MB
    xet
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  • modeling_moonshine.py
    15.1 kB
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  • special_tokens_map.json
    3 Bytes
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  • tokenizer.json
    3.76 MB
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  • tokenizer_config.json
    136 kB
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