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README.md

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-# ArtGPT-4: Artistic Vision-Language Understanding with Adapter-enhanced MiniGPT-4
-[Zhengqing Yuan](https://orcid.org/0000-0002-4870-8492)*, [Huiwen Xue]()*, [Xinyi Wang]()*, [Yongming Liu](https://www.semanticscholar.org/author/Yongming-Liu/2130184867)*, [Zhuanzhe Zhao](https://www.semanticscholar.org/author/Zhuanzhe-Zhao/2727550)*, and [Kun Wang](https://www.ahpu.edu.cn/jsjyxxgc/2023/0220/c5472a187109/page.htm)*. *Equal Contribution
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-**Anhui Polytechnic University, Soochow University**
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-<a href='https://artgpt-4.github.io'><img src='https://img.shields.io/badge/Project-Page-Green'></a>  <a href='ArtGPT_4.pdf'><img src='https://img.shields.io/badge/Paper-PDF-red'></a>
- <!-- <a href='https://huggingface.co/spaces/Vision-CAIR/minigpt4'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue'></a> <a href='https://huggingface.co/Vision-CAIR/MiniGPT-4'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Model-blue'></a> [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1OK4kYsZphwt5DXchKkzMBjYF6jnkqh4R?usp=sharing) [![YouTube](https://badges.aleen42.com/src/youtube.svg)](https://www.youtube.com/watch?v=__tftoxpBAw&feature=youtu.be) -->
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-## Online Demo
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-<!-- Click the image to chat with MiniGPT-4 around your images
-[![demo](figs/online_demo.png)](https://artgpt-4.github.io) -->
-Waiting for updates...
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-## Introduction
-- ArtGPT-4 is a novel model that builds upon the architecture of MiniGPT-4 by incorporating tailored linear layers and activation functions into Vicuna, specifically designed to optimize the model's performance in vision-language tasks.
-- The modifications made to Vicuna in ArtGPT-4 enable the model to better capture intricate details and understand the meaning of artistic images, resulting in improved image understanding compared to the original MiniGPT-4 model.
-- To address this issue and improve usability, we propose a novel way to create high-quality image-text pairs by the model itself and ChatGPT together. Based on this, we then create a small (3500 pairs in total) yet high-quality dataset.
-- ArtGPT-4 was trained using about 200 GB of image-text pairs on a Tesla A100 device in just 2 hours, demonstrating impressive efficiency and effectiveness in training.
-- In addition to improved image understanding, ArtGPT-4 is capable of generating visual code, including aesthetically pleasing HTML/CSS web pages, with a more artistic flair.
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 ## Getting Started
 ### Installation