Transformers
PyTorch
Safetensors
English
fundus
diabetic retinopathy
classification
Eval Results (legacy)
Instructions to use ClementP/FundusDRGrading-tf_efficientnet_b5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ClementP/FundusDRGrading-tf_efficientnet_b5 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ClementP/FundusDRGrading-tf_efficientnet_b5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d4e9dd874dc59de902564f7b6fa4f07384104d5ab476cb03718da1094009b4f
- Size of remote file:
- 114 MB
- SHA256:
- 849ddfe7e88fa2e733a1a953dddbdfa22a9f1bb4ad3d45e319c63e21e0233445
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