Health AI Developer Foundations (HAI-DEF)
Groups models released for use in health AI by Google. Read more about HAI-DEF at http://goo.gle/hai-def
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Image-Text-to-Text • 29B • Updated • 16.8k • 251 -
google/medgemma-27b-text-it
Text Generation • 27B • Updated • 27k • 379 -
google/medgemma-4b-pt
Image-Text-to-Text • 4B • Updated • 1.29k • 133 -
google/medgemma-4b-it
Image-Text-to-Text • 4B • Updated • 394k • 801
google/medsiglip-448
Zero-Shot Image Classification • 0.9B • Updated • 14.2k • 93Note MedSigLIP is a SigLIP variant that is trained to encode medical images and text into a common embedding space. It was trained on a variety of de-identified medical image and text pairs, including chest X-rays, dermatology images, ophthalmology images, histopathology slides, and slices of CT and MRI volumes, along with associated descriptions or reports.
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google/txgemma-9b-predict
Text Generation • 9B • Updated • 577 • 26 -
google/txgemma-9b-chat
Text Generation • 9B • Updated • 551 • 42 -
google/txgemma-27b-chat
Text Generation • 27B • Updated • 454 • 56 -
google/txgemma-27b-predict
Text Generation • 27B • Updated • 33.7k • 36 -
google/txgemma-2b-predict
Text Generation • 3B • Updated • 1.76k • 46
google/hear-pytorch
Image Feature Extraction • Updated • 199 • 12Note Health Acoustic Representations accelerates AI development for bioacoustic data e.g., coughs or breath sounds. The model is pre-trained on 300 million 2-second audio clips to produce embeddings that capture dense features relevant for bioacoustic applications.
google/hear
Updated • 75 • 33Note Health Acoustic Representations accelerates AI development for bioacoustic data e.g., coughs or breath sounds. The model is pre-trained on 300 million 2-second audio clips to produce embeddings that capture dense features relevant for bioacoustic applications.
google/path-foundation
Image Classification • Updated • 140 • 59Note Path Foundation accelerates AI development for histopathology image analysis. The model uses self-supervised learning on large amounts of digital pathology data to produce embeddings that capture dense features relevant for histopathology applications.
google/derm-foundation
Image Classification • Updated • 179 • 75Note Derm Foundation accelerates AI development for skin image analysis. The model is pre-trained on large amounts of labeled skin images to produce embeddings that capture dense features relevant for dermatology applications.
google/cxr-foundation
Image Classification • Updated • 109 • 95Note CXR Foundation accelerates AI development for chest X-ray image analysis. The model is pre-trained on large amounts of chest X-rays paired with radiology reports. It produces language-aligned embeddings that capture dense features relevant for chest X-ray applications.
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google/medasr
Automatic Speech Recognition • Updated • 3.24k • 136