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Vkt
/
model-dataaugmentationpipe

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
wav2vec2
Model card Files Files and versions
xet
Metrics Training metrics Community
1

Instructions to use Vkt/model-dataaugmentationpipe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Vkt/model-dataaugmentationpipe with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="Vkt/model-dataaugmentationpipe")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForCTC
    
    processor = AutoProcessor.from_pretrained("Vkt/model-dataaugmentationpipe")
    model = AutoModelForCTC.from_pretrained("Vkt/model-dataaugmentationpipe")
  • Notebooks
  • Google Colab
  • Kaggle
model-dataaugmentationpipe / runs
74.7 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 74 commits
Vkt's picture
Vkt
Training in progress, step 12000
e05e78d almost 4 years ago
  • Jul01_19-06-29_dsbrwavvec2-0
    Training in progress, step 1500 almost 4 years ago
  • Jul04_14-48-31_dsbrwavvec2-0
    Training in progress, step 300 almost 4 years ago
  • Jul04_20-17-45_dsbrwavvec2-0
    add tokenizer almost 4 years ago
  • Jul05_11-58-32_dsbrwavvec2-0
    Training in progress, step 12000 almost 4 years ago