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yip-i
/
wav2vec2-demo-M03-2

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

Instructions to use yip-i/wav2vec2-demo-M03-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use yip-i/wav2vec2-demo-M03-2 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="yip-i/wav2vec2-demo-M03-2")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForCTC
    
    processor = AutoProcessor.from_pretrained("yip-i/wav2vec2-demo-M03-2")
    model = AutoModelForCTC.from_pretrained("yip-i/wav2vec2-demo-M03-2")
  • Notebooks
  • Google Colab
  • Kaggle
wav2vec2-demo-M03-2
1.26 GB
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  • 1 contributor
History: 5 commits
yip-i's picture
yip-i
update model card README.md
8cf9735 over 3 years ago
  • .gitattributes
    1.48 kB
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  • .gitignore
    13 Bytes
    yip-i/wav2vec2-demo-M03-2 over 3 years ago
  • README.md
    3.26 kB
    update model card README.md over 3 years ago
  • config.json
    2.31 kB
    yip-i/wav2vec2-demo-M03-2 over 3 years ago
  • preprocessor_config.json
    214 Bytes
    yip-i/wav2vec2-demo-M03-2 over 3 years ago
  • pytorch_model.bin
    1.26 GB
    xet
    yip-i/wav2vec2-demo-M03-2 over 3 years ago
  • special_tokens_map.json
    96 Bytes
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  • tokenizer_config.json
    236 Bytes
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  • training_args.bin
    3.38 kB
    xet
    yip-i/wav2vec2-demo-M03-2 over 3 years ago
  • vocab.json
    331 Bytes
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