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hts98
/
demo_model

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

Instructions to use hts98/demo_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use hts98/demo_model with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="hts98/demo_model")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("hts98/demo_model")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("hts98/demo_model")
  • Notebooks
  • Google Colab
  • Kaggle
demo_model
3.06 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 10 commits
hts98's picture
hts98
update model card README.md
6f3cae8 about 3 years ago
  • runs
    Training in progress, step 280 about 3 years ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • .gitignore
    13 Bytes
    Training in progress, step 40 about 3 years ago
  • README.md
    1.3 kB
    update model card README.md about 3 years ago
  • config.json
    1.3 kB
    Training in progress, step 40 about 3 years ago
  • generation_config.json
    3.52 kB
    End of training about 3 years ago
  • preprocessor_config.json
    339 Bytes
    Training in progress, step 40 about 3 years ago
  • pytorch_model.bin
    3.06 GB
    xet
    End of training about 3 years ago
  • training_args.bin
    4.03 kB
    xet
    Training in progress, step 40 about 3 years ago