Instructions to use pamixsun/swinv2_tiny_for_glaucoma_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pamixsun/swinv2_tiny_for_glaucoma_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="pamixsun/swinv2_tiny_for_glaucoma_classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("pamixsun/swinv2_tiny_for_glaucoma_classification") model = AutoModelForImageClassification.from_pretrained("pamixsun/swinv2_tiny_for_glaucoma_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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@@ -15,8 +15,8 @@ This is a Swin Transformer model fine-tuned on the REFUGE challenge dataset. It
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- **Developed by:** [Xu Sun]
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- **Shared by:** Xu Sun
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- **Model type:** Image classification
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- **License:** Apache-2.0
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- **Developed by:** [Xu Sun][https://pamixsun.github.io]
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- **Shared by:** [Xu Sun][https://pamixsun.github.io]
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- **Model type:** Image classification
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- **License:** Apache-2.0
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