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BiliSakura
/
DECUR-transformers

Feature Extraction
Transformers
English
remote-sensing
earth-observation
self-supervised-learning
multispectral
sar
rgb
depth
decur
resnet
vit
segformer
Model card Files Files and versions
xet
Community

Instructions to use BiliSakura/DECUR-transformers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use BiliSakura/DECUR-transformers with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="BiliSakura/DECUR-transformers")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("BiliSakura/DECUR-transformers", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
DECUR-transformers / decur-vit-small-patch16-s2c
45.7 kB
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  • 1 contributor
History: 1 commit
BiliSakura's picture
BiliSakura
Sync updated code and configs (no weight re-upload)
ba1e0da verified 5 days ago
  • config.json
    747 Bytes
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  • dat_blocks.py
    26.7 kB
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  • image_processing_decur.py
    6.24 kB
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  • modeling_decur.py
    9.66 kB
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  • pipeline_decur.py
    2.06 kB
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  • preprocessor_config.json
    334 Bytes
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