I. Introduction
NetaYume Lumina is a text-to-image model fine-tuned from Neta Lumina, a high-quality anime-style image generation model developed by Neta.art Lab. It builds upon Lumina-Image-2.0, an open-source base model released by the Alpha-VLLM team at Shanghai AI Laboratory.
Key Features:
High-Quality Anime Generation: Generates detailed anime-style images with sharp outlines, vibrant colors, and smooth shading.
Improved Character Understanding: Better captures characters, especially those from the Danbooru dataset, resulting in more coherent and accurate character representations.
Enhanced Fine Details: Accurately generates accessories, clothing textures, hairstyles, and background elements with greater clarity.
II. Information
For version 1.0:
This model was fine-tuned from the NetaLumina model, version
neta-lumina-beta-0624-raw, using a custom dataset consisting of approximately 10 million images. Training was conducted over a period of 3 weeks on 8× NVIDIA B200 GPUs.
III. Model Components:
Text Encoder: Pretrained Gemma-2-2B
VAE: From Flux.1 dev's VAE
Image Backbone: Fine-tuned version of NetaLumina's backbone
IV. File Information
This all-in-one file includes weights for VAE, text encoder, and image backbone. Fully compatible with ComfyUI and other systems supporting custom pipelines.
V. Suggestion Settings
For more details and to achieve better results, please refer to the Neta Lumina Prompt Book.
VI. Notes & Feedback
This is an early experimental fine-tuned release, and I’m actively working on improving it in future versions.
Your feedback, suggestions, and creative prompt ideas are always welcome — every contribution helps make this model even better!
VII. Acknowledgments
Big thanks to narugo1992 for the dataset contributions.
Credit to Alpha-VLLM and Neta.art Lab for the fantastic base model architecture.
If you'd like to support my work, you can do so through Ko-fi!