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@ -24,15 +24,13 @@ More examples can be found in the [project page](https://minigpt-4.github.io).
## Introduction ## Introduction
- MiniGPT-4 aligns a frozen visual encoder from BLIP-2 with a frozen LLM, Vicuna, using just one projection layer. - MiniGPT-4 aligns a frozen visual encoder from BLIP-2 with a frozen LLM, Vicuna, using just one projection layer.
- The training of MiniGPT-4 consists of a first pretrain stage using roughly 5 million aligned image-text pairs for 10 hours on 4 A100s and a second finetuning stage using additional 3,500 carefully curated high-quality pairs for 7 minutes on 1 A100. - We train MiniGPT-4 with two stages. The first pretraining stage is trained using roughly 5 million aligned image-text pairs with around 40 A100 hours. The second finetuning stage is trained using additional 3,500 carefully curated high-quality pairs with around 7 A100 minutes.
- MiniGPT-4 processes many emerging vision-language capabilities similar to those exhibited by GPT-4. - MiniGPT-4 yields many emerging vision-language capabilities similar to those demonstrated in GPT-4.
![overview](figs/overview.png) ![overview](figs/overview.png)
## Getting Started ## Getting Started
### Installation ### Installation