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ak3ra
/
wav2vec2-base-ach

Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
Model card Files Files and versions
xet
Community
1

Instructions to use ak3ra/wav2vec2-base-ach with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ak3ra/wav2vec2-base-ach with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="ak3ra/wav2vec2-base-ach")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForCTC
    
    processor = AutoProcessor.from_pretrained("ak3ra/wav2vec2-base-ach")
    model = AutoModelForCTC.from_pretrained("ak3ra/wav2vec2-base-ach")
  • Notebooks
  • Google Colab
  • Kaggle
wav2vec2-base-ach
378 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 25 commits
ak3ra's picture
ak3ra
Training in progress, step 48000
03e0266 almost 3 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 3 years ago
  • .gitignore
    13 Bytes
    Training in progress, step 2000 almost 3 years ago
  • config.json
    2.35 kB
    Training in progress, step 2000 almost 3 years ago
  • preprocessor_config.json
    256 Bytes
    Training in progress, step 2000 almost 3 years ago
  • pytorch_model.bin
    378 MB
    xet
    Training in progress, step 48000 almost 3 years ago
  • special_tokens_map.json
    96 Bytes
    Training in progress, step 2000 almost 3 years ago
  • tokenizer_config.json
    333 Bytes
    Training in progress, step 2000 almost 3 years ago
  • training_args.bin
    3.58 kB
    xet
    Training in progress, step 2000 almost 3 years ago
  • vocab.json
    342 Bytes
    Training in progress, step 2000 almost 3 years ago