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midoiv
/
results

Audio Classification
Transformers
PyTorch
TensorBoard
wav2vec2
Model card Files Files and versions
xet
Metrics Training metrics Community
1

Instructions to use midoiv/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use midoiv/results with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("audio-classification", model="midoiv/results")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForAudioClassification
    
    processor = AutoProcessor.from_pretrained("midoiv/results")
    model = AutoModelForAudioClassification.from_pretrained("midoiv/results")
  • Notebooks
  • Google Colab
  • Kaggle
results / runs
270 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 49 commits
midoiv's picture
midoiv
Training in progress, epoch 15
b2b5179 about 2 years ago
  • Apr01_14-45-14_90bce822a50f
    Training in progress, epoch 1 about 2 years ago
  • Apr01_15-00-38_90bce822a50f
    Training in progress, epoch 25 about 2 years ago
  • Apr02_15-07-46_68f8a344ca6d
    Training in progress, epoch 4 about 2 years ago
  • Apr02_16-46-39_84f7122d9cb5
    Training in progress, epoch 1 about 2 years ago
  • Apr02_17-41-16_84f7122d9cb5
    Training in progress, epoch 15 about 2 years ago