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mlr2000
/
vocoder-large-watermark-detector

Feature Extraction
Transformers
Safetensors
cage_detector
audio
watermark
watermark-detection
provenance
vocbulwark
custom_code
Model card Files Files and versions
xet
Community

Instructions to use mlr2000/vocoder-large-watermark-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use mlr2000/vocoder-large-watermark-detector with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="mlr2000/vocoder-large-watermark-detector", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("mlr2000/vocoder-large-watermark-detector", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
vocoder-large-watermark-detector
2.67 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
mlr2000's picture
mlr2000
Update README.md
3114fa0 verified 8 days ago
  • .gitattributes
    1.52 kB
    initial commit 15 days ago
  • README.md
    3.73 kB
    Update README.md 8 days ago
  • __init__.py
    185 Bytes
    Upload folder using huggingface_hub 15 days ago
  • cage_config.py
    648 Bytes
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  • cage_extractor.py
    5.34 kB
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  • config.json
    720 Bytes
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  • configuration_detector.py
    398 Bytes
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  • example_roundtrip.ipynb
    5 kB
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  • model.safetensors
    2.65 MB
    xet
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  • modeling_detector.py
    3.74 kB
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