I. Introduction

AnimaYume is a text-to-image model fine-tuned from Anima, a high-quality anime-style image generation model developed by CircleStone Labs. It builds upon Cosmos 2, a model developed by NVIDIA’s research team.

II. Information

For version 0.1:

• This model is a preview version fine-tuned from the Anima base model using a custom dataset. Training was conducted across multiple resolutions ranging from 768 to 1280 pixels, with a primary focus around 1024. The goal of this release is to improve stability and minimize unwanted artifacts when producing high-resolution images.
• Notes: All the example images at this version were generated at the resolution 1024x1536 or 1536x1024

For version 0.2:

• This model is a continuation of AnimeYume v0.1. In this version, I improved the quality of my dataset and used several techniques to prevent oversaturation and low-quality outputs. Based on my testing phase, I observed that the prompt coherence is better than v0.1, and the model remains very stable when generating images at a resolution of 1536.
• Note: I am still waiting for the final version of Anima and testing some methods to make my training process faster. I know the license might make the model less popular, but I only care about whether the model is good or not. I’m aware that many others use better licenses, but I’m too lazy to spend a bunch of money training a model from scratch.

III. File Information

• This file contains only the diffusion model and does not include a VAE or text encoder. To use it properly, you will need to download those components from the link here

IV. Notes & Feedback

This is an experimental fine-tuned release, and I am waiting for the final version release to tune it :D
Your feedback, suggestions, and creative prompt ideas are always welcome, every contribution helps make this model even better!

V. Acknowledgments

• Big thanks to narugo1992 for the dataset contributions.
• Credit to Circlestone Labs and Nvidia for the fantastic base model architecture.

If you'd like to support my work, you can do so through Ko-fi!