Image Feature Extraction
timm
PyTorch
Safetensors
radiology
medical-imaging
xray
ct
mri
ultrasound
foundation-model
vision-transformer
self-supervised
dino
dinov2
Eval Results (legacy)
Instructions to use Snarcy/OmniRad-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use Snarcy/OmniRad-small with timm:
import timm model = timm.create_model("hf_hub:Snarcy/OmniRad-small", pretrained=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 68752d3013a152e05c7f25a09e947fde82cfa43c23a818adbac1bd778c23a63e
- Size of remote file:
- 86.6 MB
- SHA256:
- ba5c6ce6edcdfbe3a1ebc8047707d2d2cd811d5ac033d738dc74d38588e7cc6b
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