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DrishtiSharma
/
wav2vec2-xls-r-300m-rm-sursilv-d11

Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
hf-asr-leaderboard
robust-speech-event
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use DrishtiSharma/wav2vec2-xls-r-300m-rm-sursilv-d11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use DrishtiSharma/wav2vec2-xls-r-300m-rm-sursilv-d11 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="DrishtiSharma/wav2vec2-xls-r-300m-rm-sursilv-d11")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForCTC
    
    processor = AutoProcessor.from_pretrained("DrishtiSharma/wav2vec2-xls-r-300m-rm-sursilv-d11")
    model = AutoModelForCTC.from_pretrained("DrishtiSharma/wav2vec2-xls-r-300m-rm-sursilv-d11")
  • Notebooks
  • Google Colab
  • Kaggle
wav2vec2-xls-r-300m-rm-sursilv-d11
1.26 GB
Ctrl+K
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  • 2 contributors
History: 18 commits
anton-l's picture
anton-l HF Staff
Upload README.md
c18e911 about 4 years ago
  • .ipynb_checkpoints
    Training in progress, step 1500 over 4 years ago
  • .gitattributes
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  • .gitignore
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  • README.md
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  • added_tokens.json
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  • all_results.json
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  • config.json
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  • eval_results.json
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  • preprocessor_config.json
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  • pytorch_model.bin
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  • run.sh
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  • run_speech_recognition_ctc.py
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  • special_tokens_map.json
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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
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  • vocab.json
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