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MMars
/
whisper-small-ar

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
whisper-event
Generated from Trainer
hf-asr-leaderboard
Eval Results (legacy)
Model card Files Files and versions
xet
Metrics Training metrics Community
1

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

  • Libraries
  • Transformers

    How to use MMars/whisper-small-ar with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="MMars/whisper-small-ar")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("MMars/whisper-small-ar")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("MMars/whisper-small-ar")
  • Notebooks
  • Google Colab
  • Kaggle
whisper-small-ar
14.5 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 16 commits
MMars's picture
MMars
Update README.md
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  • added_tokens.json
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  • tokenizer_config.json
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  • vocab.json
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