- Follow for more updates at http://discord.com/invite/TTTGccjbEa

- Try Model: Huggingface Playground

- Access to more ongoing training versions

- 中文模型说明

- QQ group: 1039442542

Introduction

Neta Lumina is a high‑quality anime‑style image‑generation model developed by Neta.art Lab.

Building on the open‑source Lumina‑Image‑2.0 released by the Alpha‑VLLM team at Shanghai AI Laboratory, we fine‑tuned the model with a vast corpus of high‑quality anime images and multilingual tag data. The preliminary result is a compelling model with powerful comprehension and interpretation abilities (thanks to Gemma text encoder), ideal for illustration, posters, storyboards, character design, and more.

Key Features

• Optimized for diverse creative scenarios such as Furry, Guofeng (traditional‑Chinese aesthetics), pets, etc.

• Wide coverage of characters and styles, from popular to niche concepts. (Still support danbooru tags!)

• Accurate natural‑language understanding with excellent adherence to complex prompts.

• Native multilingual support, with Chinese, English, and Japanese recommended first.

Model Versions

For models in alpha tests, requst access at https://huggingface.co/neta-art/NetaLumina_Alpha if you are interested.

Neta-lumina-v1.0

Request access at https://huggingface.co/neta-art/Neta-Lumina if you are interested.

• Official Release: overall best performance

Neta-lumina-beta-0624

• Primary Goal: General knowledge and anime‑style optimization

• Data Set: >13 million anime‑style images

• >46,000 A100 Hours

How  to  Use                                                                     

Neta Lumina is built on the Lumina2 Diffusion Transformer (DiT) framework, please follow these steps precisely.

ComfyUI

Environment Requirements

Currently Neta Lumina runs only on ComfyUI:

• Latest ComfyUI installation

• ≥ 8 GB VRAM

Downloads & Installation

The model provided by Civitai is a three-in-one (te, dit, vae) packaged version, which can be run using the comfyui basic workflow without the need to download Text Encoder and VAE separately.

Original (component) release

1. Neta Lumina-V1.0

   1. Hugging Face: https://huggingface.co/neta-art/Neta-Lumina/blob/main/Unet/neta-lumina-v1.0.safetensors

   2. Save path: ComfyUI/models/unet/

2. Text Encoder (Gemma-2B)

   1. Download link: https://huggingface.co/neta-art/Neta-Lumina/blob/main/Text%20Encoder/gemma_2_2b_fp16.safetensors

   2. Save path: ComfyUI/models/text_encoders/

3. VAE Model (16-Channel FLUX VAE)

   1. Download link: https://huggingface.co/neta-art/Neta-Lumina/blob/main/VAE/ae.safetensors

   2. Save path: ComfyUI/models/vae/

Workflow: load lumina_workflow.json in ComfyUI.

• UNETLoader – loads the .pth

• VAELoader – loads ae.safetensors

• CLIPLoader – loads gemma_2_2b_fp16.safetensors

• Text Encoder – connects positive /negative prompts to the sampler

Simple merged release

Download neta-lumina-v1.0-all-in-one.safetensors,

md5sum = dca54fef3c64e942c1a62a741c4f9d8a,

you may use ComfyUI’s simple checkpoint loader workflow.

Recommended Settings

• Sampler: res_multistep

• Scheduler: linear_quadratic

• Steps: 30

• CFG (guidance): 4 – 5.5

• EmptySD3LatentImage resolution: 1024 × 1024, 768 × 1532, 968 × 1322, or >= 1024
  

Prompt Book 

Detailed prompt guidelines: https://civitai.com/articles/16274/neta-lumina-drawing-model-prompt-guide

Community                                   

Discord: https://discord.com/invite/TTTGccjbEa

QQ group: 1039442542

Roadmap 

Model

• Continous base‑model training to raise reasoning capability.

• Aesthetic‑dataset iteration to improve anatomy, background richness, and overall appealness.

• Smarter, more versatile tagging tools to lower the creative barrier.

Ecosystem

LoRA training tutorials and components

• Development of advanced control / style‑consistency features (e.g., Omini Control). Call for Collaboration!

License & Disclaimer

• Neta Lumina is released under the Fair AI Public License 1.0‑SD

• Any modifications, merges, or derivative models must themselves be open‑sourced.

Participants & Contributors

• Special thanks to the Alpha‑VLLM team for open‑sourcing Lumina‑Image‑2.0

• Model development: Neta.art Lab (Civitai), especially li_li

• Partners

  • nebulae: Civitai ・ Hugging Face

• narugo1992 & deepghs: open datasets, processing tools, and models

• Naifu trainer at Mikubill

Community Contributors

Evaluators & developers: 二小姐, spawner, Rnglg2

Other contributors: 沉迷摸鱼, poi, AshenWitch, 十分无奈, GHOSTLX, wenaka, iiiiii, 年糕特工队, 恩匹希, 奶冻, mumu, yizyin, smile, Yang, 古神, 灵之药, LyloGummy, 雪时

Appendix & Resources

• TeaCache: https://github.com/spawner1145/CUI-Lumina2-TeaCache

• Advanced samplers & TeaCache guide (by spawner): https://docs.qq.com/doc/DZEFKb1ZrZVZiUmxw?nlc=1

• Neta Lumina ComfyUI Manual (in Chinese): https://docs.qq.com/doc/DZEVQZFdtaERPdXVh

license: other

license_name: fair-ai-public-license-1.0-sd

license_link: https://freedevproject.org/faipl-1.0-sd/