Image Classification
PyTorch
Safetensors
timm
medical-imaging
retinal-imaging
fundus
ophthalmology
multi-label-classification
ensemble
Eval Results (legacy)
Instructions to use Mjolnirslams/retinal-disease-ensemble with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use Mjolnirslams/retinal-disease-ensemble with timm:
import timm model = timm.create_model("hf_hub:Mjolnirslams/retinal-disease-ensemble", pretrained=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e2502d90620d954790716db5d84781494df8a05928ef3321f63c49f096e8cc1
- Size of remote file:
- 289 MB
- SHA256:
- 472e64d1f70505dcdadf645c7a2f85ce7a2ba62986f46521f49deb0464aeba3b
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