vision-cair/minigpt-4

MiniGPT-4 and its successor MiniGPT-v2 are open-source AI research projects that let you have a conversation with an AI about images. You can show the AI a picture and ask it questions, request a story based on the image, or have it describe what it sees, all in natural language. This is called vision-language understanding, meaning the AI can "see" and "talk" at the same time. The system works by combining a large language model (the part that understands and generates text, specifically Llama 2 or Vicuna) with a visual component that processes images. MiniGPT-4 bridges these two components so the language model can reason about visual content. MiniGPT-v2 extends this further, framing multiple vision-language tasks, like image captioning, visual question answering, and grounding (identifying specific regions in an image), through a single unified interface. You would use this if you are a researcher or developer experimenting with multimodal AI, AI that handles both images and text. Running it requires downloading pretrained model weights from Hugging Face, setting up a Python environment with Conda, and having access to a GPU. A live demo is also available on Hugging Face Spaces. Built with Python, it relies on Llama 2 and Vicuna language models as its backbone.