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superb
/
wav2vec2-base-superb-er

Audio Classification
Transformers
PyTorch
English
wav2vec2
speech
audio
Model card Files Files and versions
xet
Community
2

Instructions to use superb/wav2vec2-base-superb-er with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use superb/wav2vec2-base-superb-er with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("audio-classification", model="superb/wav2vec2-base-superb-er")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForAudioClassification
    
    processor = AutoProcessor.from_pretrained("superb/wav2vec2-base-superb-er")
    model = AutoModelForAudioClassification.from_pretrained("superb/wav2vec2-base-superb-er")
  • Notebooks
  • Google Colab
  • Kaggle
wav2vec2-base-superb-er
378 MB
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  • 3 contributors
History: 5 commits
mishig's picture
mishig HF Staff
Upload README.md
441a759 over 4 years ago
  • .gitattributes
    737 Bytes
    initial commit over 4 years ago
  • README.md
    3.5 kB
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  • config.json
    2.15 kB
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  • preprocessor_config.json
    215 Bytes
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  • pytorch_model.bin
    378 MB
    xet
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