Transformers
PyTorch
Safetensors
English
fundus
diabetic retinopathy
classification
Eval Results (legacy)
Instructions to use ClementP/FundusDRGrading-efficientnet_b2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ClementP/FundusDRGrading-efficientnet_b2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ClementP/FundusDRGrading-efficientnet_b2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c0b81440b2708ffc3ee038c327990d5dc5e4803d60ee6b261c661a557150381
- Size of remote file:
- 31.1 MB
- SHA256:
- 8ec13cd74c1d40ac18bd0c5c7e29946fe8ed5114a11396d9cfdad3b6db4112ad
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