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openmmlab
/
upernet-swin-tiny

Image Segmentation
Transformers
PyTorch
English
upernet
vision
Model card Files Files and versions
xet
Community
1

Instructions to use openmmlab/upernet-swin-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use openmmlab/upernet-swin-tiny with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-segmentation", model="openmmlab/upernet-swin-tiny")
    # Load model directly
    from transformers import AutoImageProcessor, UperNetForSemanticSegmentation
    
    processor = AutoImageProcessor.from_pretrained("openmmlab/upernet-swin-tiny")
    model = UperNetForSemanticSegmentation.from_pretrained("openmmlab/upernet-swin-tiny")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
upernet-swin-tiny
240 MB
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  • 1 contributor
History: 4 commits
nielsr's picture
nielsr HF Staff
Upload README.md with huggingface_hub
dc8e8c9 over 3 years ago
  • .gitattributes
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    initial commit over 3 years ago
  • README.md
    1.63 kB
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  • config.json
    8.98 kB
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  • preprocessor_config.json
    372 Bytes
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  • pytorch_model.bin
    240 MB
    xet
    Upload UperNetForSemanticSegmentation over 3 years ago