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Rorch
/
wav2vec2-finetuned

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use Rorch/wav2vec2-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Rorch/wav2vec2-finetuned with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="Rorch/wav2vec2-finetuned")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForCTC
    
    processor = AutoProcessor.from_pretrained("Rorch/wav2vec2-finetuned")
    model = AutoModelForCTC.from_pretrained("Rorch/wav2vec2-finetuned")
  • Notebooks
  • Google Colab
  • Kaggle
wav2vec2-finetuned
1.26 GB
Ctrl+K
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  • 1 contributor
History: 38 commits
Rorch's picture
Rorch
Update vocab.json
6b76e36 verified almost 2 years ago
  • runs
    Training in progress, step 12924 almost 2 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • README.md
    3.48 kB
    End of training almost 2 years ago
  • added_tokens.json
    45 Bytes
    Upload 4 files almost 2 years ago
  • config.json
    2.1 kB
    Training in progress, step 400 almost 2 years ago
  • model.safetensors
    1.26 GB
    xet
    Training in progress, step 6000 almost 2 years ago
  • preprocessor_config.json
    214 Bytes
    Training in progress, step 400 almost 2 years ago
  • special_tokens_map.json
    96 Bytes
    Upload 4 files almost 2 years ago
  • tokenizer_config.json
    1.05 kB
    Upload 4 files almost 2 years ago
  • training_args.bin
    5.18 kB
    xet
    Training in progress, step 400 almost 2 years ago
  • vocab.json
    428 Bytes
    Update vocab.json almost 2 years ago