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lina-conti
/
wav2vec2-base-timit-eng

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

Instructions to use lina-conti/wav2vec2-base-timit-eng with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use lina-conti/wav2vec2-base-timit-eng with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="lina-conti/wav2vec2-base-timit-eng")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForCTC
    
    processor = AutoProcessor.from_pretrained("lina-conti/wav2vec2-base-timit-eng")
    model = AutoModelForCTC.from_pretrained("lina-conti/wav2vec2-base-timit-eng", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
wav2vec2-base-timit-eng
378 MB
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  • 1 contributor
History: 12 commits
lina-conti's picture
lina-conti
update model card README.md
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  • .gitattributes
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  • .gitignore
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  • README.md
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  • config.json
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  • preprocessor_config.json
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  • pytorch_model.bin
    378 MB
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  • special_tokens_map.json
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  • tokenizer_config.json
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  • training_args.bin
    3.45 kB
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  • vocab.json
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