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mg5812
/
whisper-tiny-zh

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Chinese
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Model card Files Files and versions
xet
Metrics Training metrics Community
1

Instructions to use mg5812/whisper-tiny-zh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use mg5812/whisper-tiny-zh with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="mg5812/whisper-tiny-zh")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("mg5812/whisper-tiny-zh")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("mg5812/whisper-tiny-zh", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
whisper-tiny-zh
153 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 11 commits
mg5812's picture
mg5812
Training in progress, step 4000
3f49b8d over 3 years ago
  • runs
    Training in progress, step 4000 over 3 years ago
  • .gitattributes
    1.48 kB
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  • .gitignore
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  • README.md
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    update model card README.md over 3 years ago
  • added_tokens.json
    2.08 kB
    Training in progress, step 1000 over 3 years ago
  • config.json
    1.28 kB
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  • generation_config.json
    3.5 kB
    End of training over 3 years ago
  • merges.txt
    494 kB
    Training in progress, step 1000 over 3 years ago
  • normalizer.json
    52.7 kB
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  • preprocessor_config.json
    339 Bytes
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  • pytorch_model.bin
    151 MB
    xet
    Training in progress, step 4000 over 3 years ago
  • special_tokens_map.json
    2.08 kB
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  • tokenizer_config.json
    805 Bytes
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  • training_args.bin
    3.77 kB
    xet
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  • vocab.json
    1.04 MB
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