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spencer
/
wav2vec2-base-960h

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

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

  • Libraries
  • Transformers

    How to use spencer/wav2vec2-base-960h with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="spencer/wav2vec2-base-960h")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForCTC
    
    processor = AutoProcessor.from_pretrained("spencer/wav2vec2-base-960h")
    model = AutoModelForCTC.from_pretrained("spencer/wav2vec2-base-960h")
  • Notebooks
  • Google Colab
  • Kaggle
wav2vec2-base-960h
423 MB
Ctrl+K
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  • 1 contributor
History: 2 commits
spencer's picture
spencer
Upload lm-boosted decoder
3eae345 about 4 years ago
  • language_model
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  • .gitattributes
    1.22 kB
    initial commit about 4 years ago
  • alphabet.json
    198 Bytes
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  • config.json
    1.6 kB
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  • feature_extractor_config.json
    158 Bytes
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  • preprocessor_config.json
    263 Bytes
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  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    378 MB
    xet
    Upload lm-boosted decoder about 4 years ago
  • special_tokens_map.json
    85 Bytes
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  • tokenizer_config.json
    616 Bytes
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  • vocab.json
    291 Bytes
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