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anton-l
/
wav2vec2-random-tiny-classifier

Audio Classification
Transformers
PyTorch
wav2vec2
Model card Files Files and versions
xet
Community
1

Instructions to use anton-l/wav2vec2-random-tiny-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use anton-l/wav2vec2-random-tiny-classifier with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("audio-classification", model="anton-l/wav2vec2-random-tiny-classifier")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForAudioClassification
    
    processor = AutoProcessor.from_pretrained("anton-l/wav2vec2-random-tiny-classifier")
    model = AutoModelForAudioClassification.from_pretrained("anton-l/wav2vec2-random-tiny-classifier")
  • Notebooks
  • Google Colab
  • Kaggle
wav2vec2-random-tiny-classifier
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  • 1 contributor
History: 2 commits
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speech-test
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2838dc5 over 4 years ago
  • .gitattributes
    1.18 kB
    initial commit over 4 years ago
  • config.json
    2.05 kB
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  • preprocessor_config.json
    215 Bytes
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  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    94.6 kB
    xet
    Upload over 4 years ago