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fkov
/
wav2vec2-base-ft-keyword-spotting

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

Instructions to use fkov/wav2vec2-base-ft-keyword-spotting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use fkov/wav2vec2-base-ft-keyword-spotting with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("audio-classification", model="fkov/wav2vec2-base-ft-keyword-spotting")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForAudioClassification
    
    processor = AutoProcessor.from_pretrained("fkov/wav2vec2-base-ft-keyword-spotting")
    model = AutoModelForAudioClassification.from_pretrained("fkov/wav2vec2-base-ft-keyword-spotting")
  • Notebooks
  • Google Colab
  • Kaggle
wav2vec2-base-ft-keyword-spotting
378 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 7 commits

This model has 1 file scanned as unsafe.

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fkov
update model card README.md
7d0fb91 almost 3 years ago
  • .gitattributes
    1.48 kB
    initial commit almost 3 years ago
  • .gitignore
    13 Bytes
    Training in progress, epoch 0 almost 3 years ago
  • README.md
    1.8 kB
    update model card README.md almost 3 years ago
  • all_results.json
    351 Bytes
    End of training almost 3 years ago
  • config.json
    2.86 kB
    Training in progress, epoch 0 almost 3 years ago
  • eval_results.json
    204 Bytes
    End of training almost 3 years ago
  • preprocessor_config.json
    215 Bytes
    Training in progress, epoch 0 almost 3 years ago
  • pytorch_model.bin
    378 MB
    xet
    Training in progress, epoch 4 almost 3 years ago
  • train_results.json
    167 Bytes
    End of training almost 3 years ago
  • trainer_state.json
    25.7 kB
    End of training almost 3 years ago
  • training_args.bin
    4.03 kB
    xet
    Training in progress, epoch 0 almost 3 years ago