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sharpcoder
/
wav2vec2_bjorn

Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
Model card Files Files and versions
xet
Community
1

Instructions to use sharpcoder/wav2vec2_bjorn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use sharpcoder/wav2vec2_bjorn with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="sharpcoder/wav2vec2_bjorn")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForCTC
    
    processor = AutoProcessor.from_pretrained("sharpcoder/wav2vec2_bjorn")
    model = AutoModelForCTC.from_pretrained("sharpcoder/wav2vec2_bjorn")
  • Notebooks
  • Google Colab
  • Kaggle
wav2vec2_bjorn
378 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 4 commits
Josh Cole
refactor
a363672 almost 4 years ago
  • .gitattributes
    1.17 kB
    initial commit almost 4 years ago
  • .gitignore
    20 Bytes
    initial commit almost 4 years ago
  • Generate.ipynb
    22.5 kB
    initial commit almost 4 years ago
  • README.md
    143 Bytes
    Create README.md almost 4 years ago
  • config.json
    1.94 kB
    refactor almost 4 years ago
  • preprocessor_config.json
    215 Bytes
    refactor almost 4 years ago
  • pytorch_model.bin
    378 MB
    xet
    refactor almost 4 years ago
  • training_args.bin
    2.8 kB
    xet
    refactor almost 4 years ago
  • vocab.json
    178 Bytes
    initial commit almost 4 years ago