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guynich
/
distil-whisper-large-v2-hi

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use guynich/distil-whisper-large-v2-hi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use guynich/distil-whisper-large-v2-hi with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="guynich/distil-whisper-large-v2-hi")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForMultimodalLM
    
    processor = AutoProcessor.from_pretrained("guynich/distil-whisper-large-v2-hi")
    model = AutoModelForMultimodalLM.from_pretrained("guynich/distil-whisper-large-v2-hi")
  • Notebooks
  • Google Colab
  • Kaggle
distil-whisper-large-v2-hi / distil-large-v2-hi-init
3.03 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
guynich's picture
guynich
Saving train state of step 1000
fe38d8c over 2 years ago
  • added_tokens.json
    34.6 kB
    Saving train state of step 1000 over 2 years ago
  • config.json
    2.28 kB
    Saving train state of step 1000 over 2 years ago
  • generation_config.json
    4.29 kB
    Saving train state of step 1000 over 2 years ago
  • merges.txt
    494 kB
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  • model.safetensors
    3.02 GB
    xet
    Saving train state of step 1000 over 2 years ago
  • normalizer.json
    52.7 kB
    Saving train state of step 1000 over 2 years ago
  • preprocessor_config.json
    339 Bytes
    Saving train state of step 1000 over 2 years ago
  • special_tokens_map.json
    2.19 kB
    Saving train state of step 1000 over 2 years ago
  • tokenizer_config.json
    283 kB
    Saving train state of step 1000 over 2 years ago
  • vocab.json
    1.04 MB
    Saving train state of step 1000 over 2 years ago