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readerbench
/
whisper-ro

Automatic Speech Recognition
Transformers
PyTorch
whisper
romanian
Eval Results (legacy)
Model card Files Files and versions
xet
Community
2

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

  • Libraries
  • Transformers

    How to use readerbench/whisper-ro with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="readerbench/whisper-ro")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("readerbench/whisper-ro")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("readerbench/whisper-ro")
  • Notebooks
  • Google Colab
  • Kaggle
whisper-ro
Ctrl+K
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  • 1 contributor
History: 1 commit
udan11's picture
udan11
initial commit
a2fd10c unverified almost 2 years ago
  • .gitattributes
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  • README.md
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  • added_tokens.json
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  • config.json
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  • generation_config.json
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  • merges.txt
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  • normalizer.json
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  • preprocessor_config.json
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  • pytorch_model.bin

    Detected Pickle imports (3)

    • "collections.OrderedDict",
    • "torch.FloatStorage",
    • "torch._utils._rebuild_tensor_v2"

    What is a pickle import?

    967 MB
    xet
    initial commit almost 2 years ago
  • special_tokens_map.json
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  • tokenizer.json
    2.48 MB
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  • tokenizer_config.json
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  • vocab.json
    836 kB
    initial commit almost 2 years ago