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distill-lab
/
distill-n4_00-01_combined_cls_v1b2-siglip2-large-patch16-512

Image Classification
Transformers
Safetensors
siglip
Model card Files Files and versions
xet
Community

Instructions to use distill-lab/distill-n4_00-01_combined_cls_v1b2-siglip2-large-patch16-512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use distill-lab/distill-n4_00-01_combined_cls_v1b2-siglip2-large-patch16-512 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="distill-lab/distill-n4_00-01_combined_cls_v1b2-siglip2-large-patch16-512")
    pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForImageClassification
    
    processor = AutoProcessor.from_pretrained("distill-lab/distill-n4_00-01_combined_cls_v1b2-siglip2-large-patch16-512")
    model = AutoModelForImageClassification.from_pretrained("distill-lab/distill-n4_00-01_combined_cls_v1b2-siglip2-large-patch16-512")
  • Notebooks
  • Google Colab
  • Kaggle
distill-n4_00-01_combined_cls_v1b2-siglip2-large-patch16-512
1.27 GB
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  • 1 contributor
History: 4 commits
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trojblue
Update README.md
6e8d15b verified over 1 year ago
  • .gitattributes
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  • README.md
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  • config.json
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  • model.safetensors
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  • preprocessor_config.json
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