Image Feature Extraction
timm
PyTorch
Safetensors
vit
radiomics
medical-imaging
vision-transformer
dino
dinov2
feature-extraction
foundation-model
Eval Results (legacy)
Instructions to use Snarcy/RadioDino-s16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use Snarcy/RadioDino-s16 with timm:
import timm model = timm.create_model("hf_hub:Snarcy/RadioDino-s16", pretrained=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b776b9e1a899d253e2a4c406dca672a6237ea59799ada74177753276b04e9864
- Size of remote file:
- 86.7 MB
- SHA256:
- e77a4fd67147536b3a569b9d2dd5937b84223d9dbd1542c04b845e481c1ea59c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.