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FCameCode
/
whisper-tiny-it-8

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Italian
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 FCameCode/whisper-tiny-it-8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use FCameCode/whisper-tiny-it-8 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="FCameCode/whisper-tiny-it-8")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("FCameCode/whisper-tiny-it-8")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("FCameCode/whisper-tiny-it-8", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
whisper-tiny-it-8 / checkpoint-3000
454 MB
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  • 1 contributor
History: 1 commit
FCameCode's picture
FCameCode
Upload 48 files
c2ca7f9 over 3 years ago
  • config.json
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  • optimizer.pt
    302 MB
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  • preprocessor_config.json
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  • pytorch_model.bin
    151 MB
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  • rng_state.pth
    14.6 kB
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  • scaler.pt
    557 Bytes
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  • scheduler.pt
    627 Bytes
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  • trainer_state.json
    15.4 kB
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  • training_args.bin
    3.52 kB
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