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RecCode
/
Project-Whisper_Fine_tuning

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use RecCode/Project-Whisper_Fine_tuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use RecCode/Project-Whisper_Fine_tuning with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="RecCode/Project-Whisper_Fine_tuning")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("RecCode/Project-Whisper_Fine_tuning")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("RecCode/Project-Whisper_Fine_tuning", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
Project-Whisper_Fine_tuning / runs
Ctrl+K
Ctrl+K
  • 1 contributor
History: 15 commits
RecCode's picture
RecCode
Training in progress, step 120
9b92206 verified over 2 years ago
  • Jan26_01-39-54_d9c0f3b99ac0
    Training in progress, step 20 over 2 years ago
  • Jan26_01-41-33_d9c0f3b99ac0
    Training in progress, step 20 over 2 years ago
  • Jan26_01-42-00_d9c0f3b99ac0
    Training in progress, step 10 over 2 years ago
  • Jan26_01-50-19_d9c0f3b99ac0
    Training in progress, step 120 over 2 years ago