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-b16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use Snarcy/RadioDino-b16 with timm:
import timm model = timm.create_model("hf_hub:Snarcy/RadioDino-b16", pretrained=True) - Notebooks
- Google Colab
- Kaggle
Update model card with OmniRad paper and code links
#1
by nielsr HF Staff - opened
Hi! I'm Niels from the community science team at Hugging Face.
This PR improves the model card for RadioDINO-b16 by:
- Updating the
pipeline_tagtoimage-feature-extractionfor better discoverability. - Adding a link to the research paper: OmniRad: A Radiological Foundation Model for Multi-Task Medical Image Analysis.
- Adding a link to the official GitHub repository.
- Adding the OmniRad citation.
Snarcy changed pull request status to merged