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facebook
/
wav2vec2-large-960h

Automatic Speech Recognition
Transformers
PyTorch
English
wav2vec2
speech
Eval Results
Model card Files Files and versions
xet
Community
7

Instructions to use facebook/wav2vec2-large-960h with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use facebook/wav2vec2-large-960h with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="facebook/wav2vec2-large-960h")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForCTC
    
    processor = AutoProcessor.from_pretrained("facebook/wav2vec2-large-960h")
    model = AutoModelForCTC.from_pretrained("facebook/wav2vec2-large-960h")
  • Notebooks
  • Google Colab
  • Kaggle
wav2vec2-large-960h
1.26 GB
Ctrl+K
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  • 2 contributors
History: 19 commits
patrickvonplaten's picture
patrickvonplaten
Update README.md
bdeaacd about 4 years ago
  • .gitattributes
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    allow flax almost 5 years ago
  • README.md
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  • config.json
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  • preprocessor_config.json
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  • pytorch_model.bin

    Detected Pickle imports (3)

    • "collections.OrderedDict",
    • "torch._utils._rebuild_tensor_v2",
    • "torch.FloatStorage"

    What is a pickle import?

    1.26 GB
    xet
    add files over 5 years ago
  • special_tokens_map.json
    85 Bytes
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  • tokenizer_config.json
    163 Bytes
    Update tokenizer_config.json over 5 years ago
  • vocab.json
    291 Bytes
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