Instructions to use varcoder/Augmented-MIT-b5-new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use varcoder/Augmented-MIT-b5-new with Transformers:
# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("varcoder/Augmented-MIT-b5-new") model = SegformerForSemanticSegmentation.from_pretrained("varcoder/Augmented-MIT-b5-new", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1f994044a7d59b33dbd4b40025b4b5def258323aa78433eb0a867e4fa311f9d7
- Size of remote file:
- 3.96 kB
- SHA256:
- b9000d84cf3be23852eb4891a902faccc613e9548f1c00ed9aaccf191d32f703
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