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nrshoudi
/
wav2vec2_l2arctic

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

Instructions to use nrshoudi/wav2vec2_l2arctic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use nrshoudi/wav2vec2_l2arctic with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="nrshoudi/wav2vec2_l2arctic")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForCTC
    
    processor = AutoProcessor.from_pretrained("nrshoudi/wav2vec2_l2arctic")
    model = AutoModelForCTC.from_pretrained("nrshoudi/wav2vec2_l2arctic", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
wav2vec2_l2arctic
1.26 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
nrshoudi's picture
nrshoudi
End of training
f954dc8 verified over 2 years ago
  • runs
    End of training over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    2.92 kB
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  • added_tokens.json
    30 Bytes
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  • config.json
    2.34 kB
    End of training over 2 years ago
  • model.safetensors
    1.26 GB
    xet
    End of training over 2 years ago
  • preprocessor_config.json
    212 Bytes
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  • special_tokens_map.json
    96 Bytes
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  • tokenizer_config.json
    1.09 kB
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  • training_args.bin
    4.98 kB
    xet
    End of training over 2 years ago
  • vocab.json
    499 Bytes
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