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Ramnathan
/
wav2vec2

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

Instructions to use Ramnathan/wav2vec2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Ramnathan/wav2vec2 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="Ramnathan/wav2vec2")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForCTC
    
    processor = AutoProcessor.from_pretrained("Ramnathan/wav2vec2")
    model = AutoModelForCTC.from_pretrained("Ramnathan/wav2vec2", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
wav2vec2
1.1 GB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 11 commits
Ramnathan's picture
Ramnathan
Create special_tokens_map.json
5d3f5cf about 5 years ago
  • .gitattributes
    737 Bytes
    initial commit about 5 years ago
  • config.json
    1.91 kB
    Update from about 5 years ago
  • optimizer.pt
    722 MB
    xet
    Update from about 5 years ago
  • preprocessor_config.json
    215 Bytes
    Update from about 5 years ago
  • pytorch_model.bin
    378 MB
    xet
    Update from about 5 years ago
  • rng_state.pth
    13.7 kB
    xet
    Update from about 5 years ago
  • scheduler.pt
    623 Bytes
    xet
    Update from about 5 years ago
  • special_tokens_map.json
    86 Bytes
    Create special_tokens_map.json about 5 years ago
  • tokenizer_config.json
    379 Bytes
    Create tokenizer_config.json about 5 years ago
  • trainer_state.json
    9.87 kB
    Update from about 5 years ago
  • training_args.bin
    2.67 kB
    xet
    Update from about 5 years ago