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@@ -10,4 +10,9 @@ They were designed to accept a fovea-centered retinal OCT image of size 192x192,
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  These models also accept an associated textual instruction and outputs a textual response
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- The results in paper relate to these specifications, and performance cannot be guaranteed for other image types, sizes or anatomical locations in the retina
 
 
 
 
 
 
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  These models also accept an associated textual instruction and outputs a textual response
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+ The results in paper relate to these specifications, and performance cannot be guaranteed for other image types, sizes or anatomical locations in the retina
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+ To use RetinaVLM, first clone: [https://github.com/RobbieHolland/SpecialistVLMs](https://github.com/RobbieHolland/SpecialistVLMs)
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+ And run: `models/retinavlm_wrapper.py model=minigpt4 dataset/task=all pretrained_models=specialist_v5_192px`
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