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:
- 1f77c9e1d39196e99054a1c3059dbb1098cb6d1e4cdecadb4f2abdf9805c1003
- Size of remote file:
- 189 MB
- SHA256:
- 1a1a4154b5a6d6abf4333a12c3903cc84a16d57da7c6d9eaffec3748c3e552e3
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