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cloudwalkerw
/
wavlm-base_5

Audio Classification
Transformers
PyTorch
wavlm
Generated from Trainer
Model card Files Files and versions
xet
Community

Instructions to use cloudwalkerw/wavlm-base_5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use cloudwalkerw/wavlm-base_5 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("audio-classification", model="cloudwalkerw/wavlm-base_5")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForAudioClassification
    
    processor = AutoProcessor.from_pretrained("cloudwalkerw/wavlm-base_5")
    model = AutoModelForAudioClassification.from_pretrained("cloudwalkerw/wavlm-base_5", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
wavlm-base_5
378 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 42 commits
cloudwalkerw's picture
cloudwalkerw
End of training
c098c70 almost 3 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 3 years ago
  • README.md
    3.82 kB
    End of training almost 3 years ago
  • all_results.json
    352 Bytes
    End of training almost 3 years ago
  • config.json
    2.52 kB
    Training in progress, step 100 almost 3 years ago
  • eval_results.json
    204 Bytes
    End of training almost 3 years ago
  • preprocessor_config.json
    216 Bytes
    Training in progress, step 100 almost 3 years ago
  • pytorch_model.bin
    378 MB
    xet
    Model save almost 3 years ago
  • train_results.json
    169 Bytes
    End of training almost 3 years ago
  • trainer_state.json
    15.1 kB
    End of training almost 3 years ago
  • training_args.bin
    4.09 kB
    xet
    Training in progress, step 100 almost 3 years ago