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oalz
/
wavefake-wav2vec2-model

Audio Classification
Transformers
Safetensors
English
wav2vec2
feature-extraction
Model card Files Files and versions
xet
Community

Instructions to use oalz/wavefake-wav2vec2-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use oalz/wavefake-wav2vec2-model with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("audio-classification", model="oalz/wavefake-wav2vec2-model")
    # Load model directly
    from transformers import AutoProcessor, AutoModel
    
    processor = AutoProcessor.from_pretrained("oalz/wavefake-wav2vec2-model")
    model = AutoModel.from_pretrained("oalz/wavefake-wav2vec2-model")
  • Notebooks
  • Google Colab
  • Kaggle
wavefake-wav2vec2-model
755 MB
Ctrl+K
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  • 1 contributor
History: 8 commits
oalz's picture
oalz
Update config.json
54ef67a verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • README.md
    161 Bytes
    Create README.md over 1 year ago
  • config.json
    2.37 kB
    Update config.json over 1 year ago
  • model.safetensors
    378 MB
    xet
    Upload 3 files over 1 year ago
  • preprocessor_config.json
    215 Bytes
    Upload 3 files over 1 year ago
  • wavefake_wav2vec2_model.pth

    Detected Pickle imports (3)

    • "collections.OrderedDict",
    • "torch.FloatStorage",
    • "torch._utils._rebuild_tensor_v2"

    What is a pickle import?

    378 MB
    xet
    Upload wavefake_wav2vec2_model.pth over 1 year ago