2024.1.22 HelloWorld 4.0 Version Update

HelloWorld 4.0 is an incremental transition version from blip+clip to GPT4V tagging. It integrates the latest HelloWorld model trained with GPT4V tagging with the original HelloWorld 3.2, and in the final round of integration, incorporates a 0.05 ratio of Juggernaut XL to adjust skin tone. The new version shows improvements in prompt word coherence and conceptual coverage compared to version 3.2.

The new GPT4V tagging training set doubles the size of the HelloWorld3 series from 4000 to 8000 images, covering not only portraits but also animals, buildings, nature, food, illustrations, and more. However, the pure GPT4V version encountered overfitting issues, likely due to doubling the training image quantity. The next iterative optimization direction will focus on adding more non-portrait concepts while ensuring sufficient portrait training. Currently, a hybrid tuning of the new and old versions is used to ensure a smooth transition between versions, hence the expanded concept set and advantages brought by GPT4V tagging may not be very prominent. These advantages will become more apparent in the subsequent 5th and 6th generation models.

Special Thanks:

Special thanks to the development team of the GPT4V Image Tagging and Processing Toolbox (Jiaye, SleeepyZhou, Fok, 十字鱼). GPT4V tagging will be one of the technical foundations for future upgrades of this model. We have also developed a web-based plugin version for everyone to explore and use.

Thanks to Yuzi for developing the Unsplash Collection Downloader Greasemonkey Script, Unsplash is the world's largest royalty-free image sharing community.

Thanks to Maoruoyu, SleeepyZhou, Fok, and Cayden for sharing my collection of images. The Human Completion Plan has a long way to go, and I will continue to work hard (doge).

Thanks to the author of Juggernaut and other contributors in the community for their open-source content.

Thanks to friends who have always supported and helped Tusan, as well as the first-party dads who have provided financial support through commercial collaborations, allowing Tusan to expand computing power and continue to share open-source.