Instructions to use egeozsoy/EndoViT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use egeozsoy/EndoViT with timm:
import timm model = timm.create_model("hf_hub:egeozsoy/EndoViT", pretrained=True) - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -80,7 +80,7 @@ def load_model_from_huggingface(repo_id, model_filename):
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return model, loading
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image_paths = sorted(Path('demo_images').glob('*.png')) # TODO replace with image
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images = torch.stack([process_single_image(image_path) for image_path in image_paths])
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device = "cuda"
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return model, loading
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image_paths = sorted(Path('demo_images').glob('*.png')) # TODO replace with image path
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images = torch.stack([process_single_image(image_path) for image_path in image_paths])
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device = "cuda"
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