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
Link model to OmniRad paper and repository
#1
by nielsr HF Staff - opened
This PR improves the model card for RadioDINO-s16 by:
- Linking the model to the associated paper: OmniRad: A Radiological Foundation Model for Multi-Task Medical Image Analysis.
- Adding a link to the official OmniRad GitHub repository.
- Updating the
pipeline_tagtoimage-feature-extractionfor better discoverability and standardization.