MiniGPT-5

Why we included this project

MiniGPT-5 is for the harder authoring case where you want a language model to produce a piece of text and the illustrations that go with it in the same pass, rather than a chatbot with an image generator bolted on. It works by inserting learned 'vokens' into the text stream to mark where a picture belongs and feed those positions through Stable Diffusion, so the images stay tied to the narrative around them. The model builds on the MiniGPT-4 architecture with a Vicuna backbone and BLIP-2 vision encoder, and its two-stage training scheme avoids needing detailed image captions, with classifier-free guidance keeping text and image aligned. Teams experimenting with multimodal dialogue, visual storytelling, or any pipeline that wants words and matching pictures out of one model will find plenty worth studying here. It is an academic codebase, though, so expect to supply pretrained weights and GPU resources; treat it as a foundation to adapt rather than something ready to ship.