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bagasshw
/
ASR_Results

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Javanese
whisper
javanese
asr
Generated from Trainer
Eval Results (legacy)
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use bagasshw/ASR_Results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use bagasshw/ASR_Results with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="bagasshw/ASR_Results")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("bagasshw/ASR_Results")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("bagasshw/ASR_Results")
  • Notebooks
  • Google Colab
  • Kaggle
ASR_Results
157 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
bagasshw's picture
bagasshw
End of training
a2f5904 verified over 1 year ago
  • runs
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  • .gitattributes
    1.52 kB
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  • README.md
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  • added_tokens.json
    34.6 kB
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  • all_results.json
    449 Bytes
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  • config.json
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  • eval_results.json
    237 Bytes
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  • generation_config.json
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  • merges.txt
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  • model.safetensors
    151 MB
    xet
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  • normalizer.json
    52.7 kB
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  • preprocessor_config.json
    356 Bytes
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  • special_tokens_map.json
    2.17 kB
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  • tokenizer.json
    3.86 MB
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  • tokenizer_config.json
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  • train_results.json
    247 Bytes
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  • trainer_state.json
    3.13 kB
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  • training_args.bin
    5.5 kB
    xet
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  • vocab.json
    798 kB
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