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vumichien
/
wav2vec2-xls-r-1b-japanese

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
Japanese
wav2vec2
common-voice
hf-asr-leaderboard
robust-speech-event
Eval Results (legacy)
Model card Files Files and versions
xet
Metrics Training metrics Community
1

Instructions to use vumichien/wav2vec2-xls-r-1b-japanese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use vumichien/wav2vec2-xls-r-1b-japanese with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="vumichien/wav2vec2-xls-r-1b-japanese")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForCTC
    
    processor = AutoProcessor.from_pretrained("vumichien/wav2vec2-xls-r-1b-japanese")
    model = AutoModelForCTC.from_pretrained("vumichien/wav2vec2-xls-r-1b-japanese", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
wav2vec2-xls-r-1b-japanese
3.85 GB
Ctrl+K
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  • 2 contributors
History: 21 commits
vumichien's picture
vumichien
End of training
cd1f931 over 4 years ago
  • runs
    End of training over 4 years ago
  • .gitattributes
    1.18 kB
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  • .gitignore
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  • added_tokens.json
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  • all_results.json
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  • config.json
    2.04 kB
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  • eval_results.json
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  • preprocessor_config.json
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  • pytorch_model.bin
    3.85 GB
    xet
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  • special_tokens_map.json
    309 Bytes
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  • tokenizer_config.json
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  • train_results.json
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  • trainer_state.json
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  • training_args.bin
    3.12 kB
    xet
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  • vocab.json
    1.23 kB
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