Instructions to use microsoft/rad-dino with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/rad-dino with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="microsoft/rad-dino")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("microsoft/rad-dino") model = AutoModel.from_pretrained("microsoft/rad-dino", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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@@ -13,7 +13,7 @@ RAD-DINO is a vision transformer model trained to encode chest X-rays using the
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RAD-DINO is described in detail in [Exploring Scalable Medical Image Encoders Beyond Text Supervision (F. Pérez-García, H. Sharma, S. Bond-Taylor, et al.,
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- **Developed by:** Microsoft Health Futures
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- **Model type:** Vision transformer
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RAD-DINO is described in detail in [Exploring Scalable Medical Image Encoders Beyond Text Supervision (F. Pérez-García, H. Sharma, S. Bond-Taylor, et al., 2025)](https://www.nature.com/articles/s42256-024-00965-w).
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- **Developed by:** Microsoft Health Futures
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- **Model type:** Vision transformer
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