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microsoft
/
paza-whisper-large-v3-turbo

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

Instructions to use microsoft/paza-whisper-large-v3-turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use microsoft/paza-whisper-large-v3-turbo with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="microsoft/paza-whisper-large-v3-turbo")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForMultimodalLM
    
    processor = AutoProcessor.from_pretrained("microsoft/paza-whisper-large-v3-turbo")
    model = AutoModelForMultimodalLM.from_pretrained("microsoft/paza-whisper-large-v3-turbo")
  • Notebooks
  • Google Colab
  • Kaggle
paza-whisper-large-v3-turbo
6.47 GB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 1 commit
KevChege's picture
KevChege
muchai-mercy's picture
muchai-mercy
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8a0bd24 4 months ago
  • figures
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  • .gitattributes
    1.94 kB
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  • README.md
    19.2 kB
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  • added_tokens.json
    34.7 kB
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  • config.json
    1.34 kB
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  • generation_config.json
    2.94 kB
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  • merges.txt
    494 kB
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  • model.safetensors
    3.24 GB
    xet
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  • normalizer.json
    52.7 kB
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  • preprocessor_config.json
    340 Bytes
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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?

    3.24 GB
    xet
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  • special_tokens_map.json
    2.19 kB
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  • tokenizer_config.json
    284 kB
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  • vocab.json
    1.04 MB
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