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CLiC-UB
/
Casper

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

Instructions to use CLiC-UB/Casper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use CLiC-UB/Casper with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="CLiC-UB/Casper")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("CLiC-UB/Casper")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("CLiC-UB/Casper")
  • Notebooks
  • Google Colab
  • Kaggle
Casper
969 MB
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  • 1 contributor
History: 2 commits
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AlexK-PL
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  • .gitattributes
    1.52 kB
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  • README.md
    30 Bytes
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  • added_tokens.json
    2.08 kB
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  • config.json
    1.29 kB
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  • generation_config.json
    253 Bytes
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  • merges.txt
    494 kB
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  • normalizer.json
    52.7 kB
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  • preprocessor_config.json
    185 kB
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  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    967 MB
    xet
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  • special_tokens_map.json
    2.08 kB
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  • tokenizer_config.json
    862 Bytes
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  • vocab.json
    1.04 MB
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