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:
- aa71dfbbf530e73f73fcc75899832a15e2ad2536fbd11be47e2d6f2f716d5e20
- Size of remote file:
- 4.03 kB
- SHA256:
- 6ebe9160d436a6ed9df1ffd87c416c7909fdcd4548651e8704e47c9fff3a5537
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