Just released! An open source model for generating anime-style images with one click

#Introducing to you the latest AIGC open source project-Animagine XL 3.1. This project is the latest iteration of the anime-themed text-to-image model, aiming to provide users with a more optimized and powerful anime image generation experience.

In Animagine XL 3.1, the development team focused on optimizing several key aspects to ensure that the model reaches new heights in performance and functionality. First, they expanded the training data to include not only game character data from previous versions, but also data from many other well-known anime series into the training set. This move enriches the model's knowledge base, allowing it to more fully understand various anime styles and characters.

Animagine XL 3.1 introduces a new set of special tags and aesthetic tags for better guidance The model generates images with specific visual appeal and quality. The addition of these tags not only improves the quality of generated images, but also enables users to more precisely control the direction and results of image generation.

The development team has fine-tuned some issues that appeared in the previous version, such as uneven distribution of exposure and quality labels. By updating the training script and optimizing the model configuration, they successfully improved the accuracy of the model and the quality of the generated images, providing users with a more accurate and reliable experience.

Finally, it is worth mentioning that users can obtain Animagine XL 3.1 through platforms such as SeaArt and Huggingface Early version. The release of this open source project not only represents the development team's commitment to continuous improvement and innovation, but will also bring more surprises and experiences to users. Let us look forward to the arrival of the official version of Animagine XL 3.1, which will inject more vitality and innovation into the field of animation image generation!

Model download address:

//m.sbmmt.com/link/0365aaecae1f149351d36fb06a31828f

Online experience address:

//m.sbmmt.com/link/ca0226c1b273bb50a210ba4a8db4ce8c