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EducativeCS2023
/
whisper-en-tiny-trained

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
Model card Files Files and versions
xet
Metrics Training metrics Community
1

Instructions to use EducativeCS2023/whisper-en-tiny-trained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use EducativeCS2023/whisper-en-tiny-trained with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="EducativeCS2023/whisper-en-tiny-trained")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("EducativeCS2023/whisper-en-tiny-trained")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("EducativeCS2023/whisper-en-tiny-trained")
  • Notebooks
  • Google Colab
  • Kaggle
whisper-en-tiny-trained / runs
24.7 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 6 commits
EducativeCS2023's picture
EducativeCS2023
End of training
0a15280 almost 3 years ago
  • Jun15_11-47-38_educative
    End of training almost 3 years ago
  • Jun15_15-07-50_educative
    End of training almost 3 years ago