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allandclive
/
whisper-tiny-luganda

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

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

  • Libraries
  • Transformers

    How to use allandclive/whisper-tiny-luganda with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="allandclive/whisper-tiny-luganda")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("allandclive/whisper-tiny-luganda")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("allandclive/whisper-tiny-luganda")
  • Notebooks
  • Google Colab
  • Kaggle
whisper-tiny-luganda
153 MB
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  • 1 contributor
History: 11 commits
allandclive's picture
allandclive
Update README.md
11c69fe verified about 2 years ago
  • runs
    End of training about 2 years ago
  • .gitattributes
    1.52 kB
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  • README.md
    959 Bytes
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  • added_tokens.json
    34.6 kB
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  • config.json
    1.31 kB
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  • generation_config.json
    3.76 kB
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  • merges.txt
    494 kB
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  • model.safetensors
    151 MB
    xet
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  • preprocessor_config.json
    339 Bytes
    End of training about 2 years ago
  • special_tokens_map.json
    2.19 kB
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  • tokenizer_config.json
    828 Bytes
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  • training_args.bin
    5.05 kB
    xet
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  • vocab.json
    1.04 MB
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