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Wseop
/
AST

Audio Classification
Transformers
PyTorch
audio-spectrogram-transformer
Model card Files Files and versions
xet
Community
1

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

  • Libraries
  • Transformers

    How to use Wseop/AST with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("audio-classification", model="Wseop/AST")
    # Load model directly
    from transformers import AutoFeatureExtractor, AutoModelForAudioClassification
    
    extractor = AutoFeatureExtractor.from_pretrained("Wseop/AST")
    model = AutoModelForAudioClassification.from_pretrained("Wseop/AST")
  • Notebooks
  • Google Colab
  • Kaggle
AST
717 MB
Ctrl+K
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  • 1 contributor
History: 5 commits
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model
3e9d600 verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    21 Bytes
    initial commit about 2 years ago
  • config.json
    955 Bytes
    upload about 2 years ago
  • model.safetensors
    358 MB
    xet
    Adding `safetensors` variant of this model over 1 year ago
  • pytorch_model.bin

    Detected Pickle imports (3)

    • "collections.OrderedDict",
    • "torch.FloatStorage",
    • "torch._utils._rebuild_tensor_v2"

    What is a pickle import?

    358 MB
    xet
    Upload pytorch_model.bin about 2 years ago