Transformers
PyTorch
Safetensors
English
fundus
diabetic retinopathy
classification
Eval Results (legacy)
Instructions to use ClementP/FundusDRGrading-convnext_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ClementP/FundusDRGrading-convnext_base with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ClementP/FundusDRGrading-convnext_base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e5f8a6a5dc1198489238bfa06f3352b18206669d5241ccfb992fd4dcafdac7c9
- Size of remote file:
- 350 MB
- SHA256:
- f6754d0ee67dbb8caea198abbd89079186ee9b16f342057f770f95d63222a58a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.