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lrauch
/
BAT-vit-b16-pretrainedAS2M

Feature Extraction
Transformers
Safetensors
bat
audio
self-supervised-learning
masked-modeling
audioset
BAT
custom_code
Model card Files Files and versions
xet
Community

Instructions to use lrauch/BAT-vit-b16-pretrainedAS2M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use lrauch/BAT-vit-b16-pretrainedAS2M with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="lrauch/BAT-vit-b16-pretrainedAS2M", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("lrauch/BAT-vit-b16-pretrainedAS2M", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
BAT-vit-b16-pretrainedAS2M
371 MB
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  • 1 contributor
History: 3 commits
lrauch's picture
lrauch
Update README.md
1751093 verified 27 days ago
  • .gitattributes
    177 Bytes
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  • LICENSE
    1.07 kB
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  • README.md
    4.46 kB
    Update README.md 27 days ago
  • config.json
    998 Bytes
    Upload BAT ViT-B/16 AudioSet-2M pretrained encoder about 1 month ago
  • configuration_bat.py
    2.07 kB
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  • load_model.py
    941 Bytes
    Upload BAT ViT-B/16 AudioSet-2M pretrained encoder about 1 month ago
  • model.safetensors
    371 MB
    xet
    Upload BAT ViT-B/16 AudioSet-2M pretrained encoder about 1 month ago
  • modeling_bat.py
    17 kB
    Upload BAT ViT-B/16 AudioSet-2M pretrained encoder about 1 month ago
  • processing_bat.py
    3.39 kB
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  • requirements.txt
    59 Bytes
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