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
Commit History
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Improve model card: refine pipeline tag and add GitHub link
Verified signatureThis PR refines the `pipeline_tag` from `feature-extraction` to `image-feature-extraction` for greater specificity, ensuring the model is more accurately categorized on the Hugging Face Hub (e.g., at https://huggingface.co/models?pipeline_tag=image-feature-extraction). It also adds a direct link to the GitHub repository for easier access to the model's codebase and further resources, improving the discoverability of the official implementation.f328434
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Update README.md
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Update README.md
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RedDino_config
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initial commit
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