Instructions to use vyshnav112233/retina-dr-deit-without-distillation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use vyshnav112233/retina-dr-deit-without-distillation with timm:
import timm model = timm.create_model("hf_hub:vyshnav112233/retina-dr-deit-without-distillation", pretrained=True) - Notebooks
- Google Colab
- Kaggle
DeiT WITHOUT Distillation
This model classifies retinal images into:
- No DR
- Mild
- Moderate
- Severe
- Proliferative DR
Model architecture: deit_small_patch16_224
Distilled model: False
Primary metric: Tuned Quadratic Weighted Kappa
Primary inference output: Threshold-tuned QWK prediction
Tuned thresholds:
[ 1.0235428891379215, 1.7234984095439454, 2.025988978797374, 2.6660228022901524 ]
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