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bn22
/
naflexvit_base_patch16

Image Feature Extraction
Transformers
Safetensors
timm
timm_wrapper
Model card Files Files and versions
xet
Community

Instructions to use bn22/naflexvit_base_patch16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use bn22/naflexvit_base_patch16 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-feature-extraction", model="bn22/naflexvit_base_patch16")
    # Load model directly
    from transformers import AutoImageProcessor, AutoModel
    
    processor = AutoImageProcessor.from_pretrained("bn22/naflexvit_base_patch16")
    model = AutoModel.from_pretrained("bn22/naflexvit_base_patch16")
  • timm

    How to use bn22/naflexvit_base_patch16 with timm:

    import timm
    
    model = timm.create_model("hf_hub:bn22/naflexvit_base_patch16", pretrained=True)
  • Notebooks
  • Google Colab
  • Kaggle
naflexvit_base_patch16
372 MB
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  • 1 contributor
History: 2 commits
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bn22
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a50d72e verified 19 days ago
  • .gitattributes
    1.52 kB
    initial commit 19 days ago
  • README.md
    5.18 kB
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  • config.json
    812 Bytes
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  • model.safetensors
    372 MB
    xet
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