Instructions to use pamixsun/segformer_for_optic_disc_cup_segmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pamixsun/segformer_for_optic_disc_cup_segmentation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="pamixsun/segformer_for_optic_disc_cup_segmentation")# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("pamixsun/segformer_for_optic_disc_cup_segmentation") model = SegformerForSemanticSegmentation.from_pretrained("pamixsun/segformer_for_optic_disc_cup_segmentation") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d465220f34e9d4e7d58287883b4fe297ff45db39f79fca4f487f68803d672ff1
- Size of remote file:
- 189 MB
- SHA256:
- 22e45131b64eb07a5d29a2e5388a7709d10696b13f48d2d0cdcf56cafa1f9ea5
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