Specialized vision-language models for clinical ophthalmology (specifically AMD in retinal OCT)

See paper [https://arxiv.org/abs/2407.08410](https://arxiv.org/abs/2407.08410)

These versions of the model are not applicable for clinical use, as they were developed for research purposes

These models use the 8 bit versions of meta-llama/Meta-Llama-3-8B-Instruct

They were designed to accept a fovea-centered retinal OCT image of size 192x192, with physical pixel dimensions of 7.0×23.4 μm2, from the Topcon scanner

These models also accept an associated textual instruction and outputs a textual response

The results in paper relate to these specifications, and performance cannot be guaranteed for other image types, sizes or anatomical locations in the retina

To use RetinaVLM, first clone: [https://github.com/RobbieHolland/SpecialistVLMs](https://github.com/RobbieHolland/SpecialistVLMs)

And run: `models/retinavlm_wrapper.py model=minigpt4 dataset/task=all pretrained_models=specialist_v5_192px`