Image Feature Extraction
timm
PyTorch
Safetensors
red-blood-cells
hematology
medical-imaging
vision-transformer
dino
dinov2
feature-extraction
foundation-model
Eval Results (legacy)
Instructions to use Snarcy/RedDino-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use Snarcy/RedDino-base with timm:
import timm model = timm.create_model("hf_hub:Snarcy/RedDino-base", pretrained=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- db4a91af6f98fd1fbfee422a1c7d803611aa61427dd5345c2e08a32f412f4f76
- Size of remote file:
- 343 MB
- SHA256:
- 52d7ceb6e91f90ff1e8c2c80a69a7c55137c480c0fa430ffe1ed5400c0ab7515
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