Instructions to use varcoder/CrackSeg-MIT-b0-aug with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use varcoder/CrackSeg-MIT-b0-aug with Transformers:
# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("varcoder/CrackSeg-MIT-b0-aug") model = SegformerForSemanticSegmentation.from_pretrained("varcoder/CrackSeg-MIT-b0-aug", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9dfc80e4072e658af958f1a83bb707e089d4347dee10abe42726f724c1ba3be0
- Size of remote file:
- 110 MB
- SHA256:
- 7b59ea85e43b3861c6901e957eca4b6a2768678bddcb803a578461078f8aa3d1
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