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openai
/
whisper-large-v3-turbo

Automatic Speech Recognition
Transformers
Safetensors
whisper
audio
Eval Results
Model card Files Files and versions
xet
Community
88

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

  • Libraries
  • Transformers

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

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="openai/whisper-large-v3-turbo")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("openai/whisper-large-v3-turbo")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-large-v3-turbo")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
whisper-large-v3-turbo
1.62 GB
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  • 4 contributors
History: 14 commits
julien-c's picture
julien-c HF Staff
reach-vb's picture
reach-vb
Update README.md (#18)
41f01f3 verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • README.md
    21.2 kB
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  • added_tokens.json
    34.6 kB
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  • config.json
    1.26 kB
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  • generation_config.json
    3.77 kB
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  • merges.txt
    494 kB
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  • model.safetensors
    1.62 GB
    xet
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  • normalizer.json
    52.7 kB
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  • preprocessor_config.json
    340 Bytes
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  • special_tokens_map.json
    2.19 kB
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  • tokenizer.json
    2.71 MB
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  • tokenizer_config.json
    283 kB
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  • vocab.json
    1.04 MB
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