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gdurkin
/
cali_fire_risk

Image Segmentation
Transformers
Safetensors
mask2former
semantic-segmentation
remote-sensing
aerial-imagery
wildfire-risk
Eval Results (legacy)
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use gdurkin/cali_fire_risk with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-segmentation", model="gdurkin/cali_fire_risk")
    # Load model directly
    from transformers import AutoImageProcessor, Mask2FormerForUniversalSegmentation
    
    processor = AutoImageProcessor.from_pretrained("gdurkin/cali_fire_risk")
    model = Mask2FormerForUniversalSegmentation.from_pretrained("gdurkin/cali_fire_risk")
  • Notebooks
  • Google Colab
  • Kaggle
cali_fire_risk
866 MB
Ctrl+K
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  • 1 contributor
History: 5 commits
gdurkin's picture
gdurkin
Update README with YAML on main (homepage card)
2e5c93b verified 10 months ago
  • .gitattributes
    1.52 kB
    initial commit 10 months ago
  • README.md
    2.4 kB
    Update README with YAML on main (homepage card) 10 months ago
  • config.json
    75.3 kB
    Promote best snapshot to main 10 months ago
  • labels.json
    413 Bytes
    Promote best snapshot to main 10 months ago
  • model.safetensors
    866 MB
    xet
    Promote best snapshot to main 10 months ago
  • preprocessor_config.json
    457 Bytes
    Promote best snapshot to main 10 months ago