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Sangramsing
/
whisper-medium

Automatic Speech Recognition
Transformers
PyTorch
google-tensorflow TensorFlow
JAX
whisper
audio
hf-asr-leaderboard
Eval Results (legacy)
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use Sangramsing/whisper-medium with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="Sangramsing/whisper-medium")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("Sangramsing/whisper-medium")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("Sangramsing/whisper-medium")
  • Notebooks
  • Google Colab
  • Kaggle
whisper-medium
4 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
Sangramsing's picture
Sangramsing
Upload 14 files
fb3795e about 3 years ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • README.md
    19.6 kB
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  • added_tokens.json
    2.08 kB
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  • config.json
    1.97 kB
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  • flax_model.msgpack
    135 Bytes
    xet
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  • generation_config.json
    3.46 kB
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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
    135 Bytes
    xet
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  • special_tokens_map.json
    2.08 kB
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  • tf_model.h5
    135 Bytes
    xet
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  • tokenizer.json
    2.2 MB
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  • tokenizer_config.json
    843 Bytes
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  • vocab.json
    1.04 MB
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