Instructions to use varcoder/Augmented-MIT-b5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use varcoder/Augmented-MIT-b5 with Transformers:
# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("varcoder/Augmented-MIT-b5") model = SegformerForSemanticSegmentation.from_pretrained("varcoder/Augmented-MIT-b5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e7252e2bca3d436c97dd3c76e19b42ae6e84ab4cf3580125a507ec57cf29c2cc
- Size of remote file:
- 339 MB
- SHA256:
- 17e86f42cd753e0ff10014b78c6bdc3ad6bf3084df12614c8e8037b6457f2d9c
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