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dmmagdal
/
whisper-tiny-onnx

Automatic Speech Recognition
Transformers
ONNX
whisper
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use dmmagdal/whisper-tiny-onnx with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="dmmagdal/whisper-tiny-onnx")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("dmmagdal/whisper-tiny-onnx")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("dmmagdal/whisper-tiny-onnx")
  • Notebooks
  • Google Colab
  • Kaggle
whisper-tiny-onnx
1.25 GB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 2 commits
dmmagdal's picture
dmmagdal
upload onnx model files
3f85914 over 2 years ago
  • onnx
    upload onnx model files over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    28 Bytes
    initial commit over 2 years ago
  • added_tokens.json
    34.6 kB
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  • config.json
    2.24 kB
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  • decoder_model.onnx
    198 MB
    xet
    upload onnx model files over 2 years ago
  • decoder_model_merged.onnx
    198 MB
    xet
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  • decoder_with_past_model.onnx
    193 MB
    xet
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  • encoder_model.onnx
    32.9 MB
    xet
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  • generation_config.json
    3.71 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
    339 Bytes
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  • special_tokens_map.json
    2.19 kB
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  • tokenizer.json
    2.48 MB
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  • tokenizer_config.json
    283 kB
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  • vocab.json
    1.04 MB
    upload onnx model files over 2 years ago