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The Model: This demo features Google's MedGemma-27B, a Gemma 3-based model fine-tuned for comprehending medical text and images, specifically Chest X-Rays. It demonstrates MedGemma's ability to facilitate the learning process for medical students by advanced interpretation of medical images and contextual question generation while leveraging clinical guidelines. Context from clinical guidelines are generated using RAG which utilizes Google's MedSigLIP embedding model to build a vector index database.
Accessing and Using the Model: Google's MedGemma-27B is available on{' '}
HuggingFace
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and{' '}
Model Garden
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Learn more about using the model and its limitations on the{' '}
HAI-DEF developer site
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Health AI Developer Foundations (HAI-DEF): Provides a collection of open-weight models and companion resources to empower developers in building AI models for healthcare.
Enjoying the Demo? We'd love your feedback! If you found this demo helpful, please show your appreciation by clicking the ❤️ button on the HuggingFace page, linked at the top.
Explore More Demos: Discover additional demos on HuggingFace Spaces or via Colabs: