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Register MedGemma, MedSigLIP Presets to kerashub #2450

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Merged
merged 3 commits into from
Oct 28, 2025
Merged

Register MedGemma, MedSigLIP Presets to kerashub #2450

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09d691f
Register MedGemma, MedSigLIP Presets to kerashub
laxmareddyp Oct 27, 2025
eaa9d4d
Address gemini comments
laxmareddyp Oct 27, 2025
74f524f
Add siglip preset mapping
laxmareddyp Oct 28, 2025
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39 changes: 39 additions & 0 deletions keras_hub/src/models/gemma3/gemma3_presets.py
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Expand Up @@ -181,4 +181,43 @@
},
"kaggle_handle": "kaggle://keras/gemma3/keras/gemma3_instruct_270m/4",
},
"medgemma_instruct_4b": {
"metadata": {
"description": (
"A 4 billion parameter model based on Gemma 3. "
"This model is trained for performance on medical text"
"and image comprehension and is optimized for medical"
"applications that involve a text generation component."
),
"params": 4300079472,
"path": "gemma3",
},
"kaggle_handle": "kaggle://keras/medgemma/keras/medgemma_instruct_4b/1",
},
"medgemma_instruct_27b": {
"metadata": {
"description": (
"A 27 billion parameter model based on Gemma 3. "
"This model trained for performance on medical text "
"and image comprehension and is optimized for medical "
"applications that involve a text generation component."
),
"params": 27432406640,
"path": "gemma3",
},
"kaggle_handle": "kaggle://keras/medgemma/keras/medgemma_instruct_27b/1",
},
"medgemma_instruct_27b_text": {
"metadata": {
"description": (
"A 27 billion parameter text-only model based on Gemma 3. "
"This model is trained for performance on medical text "
"comprehension and is optimized for medical applications "
"that involve a text generation component."
),
"params": 27009002240,
"path": "gemma3",
},
"kaggle_handle": "kaggle://keras/medgemma/keras/medgemma_instruct_27b_text/1",
},
}
15 changes: 15 additions & 0 deletions keras_hub/src/models/siglip/siglip_presets.py
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Expand Up @@ -321,4 +321,19 @@
},
"kaggle_handle": "kaggle://keras/siglip/keras/siglip2_so400m_patch16_512/1",
},
"medsiglip_900m_448": {
"metadata": {
"description": (
"A 900 million parameter variant of SigLIP trained to encode "
"medical images and text into a common embedding space. "
"MedSigLIP contains a vision encoder and a text encoder, and "
"supports 448x448 image resolution with up to 64 text tokens."
),
"params": 878301426,
"official_name": "SigLIP2",
"path": "siglip",
"model_card": "https://huggingface.co/google/medsiglip-448#medsiglip-model-card",
},
"kaggle_handle": "kaggle://keras/medsiglip/keras/medsiglip_900m_448/1",
},
}
1 change: 1 addition & 0 deletions tools/checkpoint_conversion/convert_siglip_checkpoints.py
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Expand Up @@ -110,6 +110,7 @@
"siglip2_so400m_patch16_256": "google/siglip2-so400m-patch16-256",
"siglip2_so400m_patch16_384": "google/siglip2-so400m-patch16-384",
"siglip2_so400m_patch16_512": "google/siglip2-so400m-patch16-512",
"medsiglip_900m_448": "google/medsiglip-448",
}

flags.DEFINE_string(
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