Original:https://civitai.com/models/1612109/neta-lumina

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

Model Versions

Base Model

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

Primary Goal: General knowledge and anime‑style optimization
Data Set: >13 million anime‑style images
>46,000 A100 Hours

Neta-lumina-beta-0624

First beta release candidate
Primary Goal: Enhanced aesthetics, pose accuracy, and scene detail
Data Set: Hundreds of thousands of handpicked high‑quality anime images (fine‑tuned on the Base)

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

Neta Lumina-Beta
1. Hugging Face: https://huggingface.co/neta-art/Neta-Lumina/blob/main/neta-lumina-beta-0624.pth
2. Save path: ComfyUI/models/unet/
Text Encoder (Gemma-2B)
1. Download link: https://huggingface.co/neta-art/Neta-Lumina/resolve/main/gemma_2_2b_fp16.safetensors
2. Save path: ComfyUI/models/text_encoders/
VAE Model (16-Channel FLUX VAE)
1. Download link: https://huggingface.co/neta-art/Neta-Lumina/resolve/main/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-beta-0624.safetensors], md5sum = dca54fef3c64e942c1a62a741c4f9d8a, you may use ComfyUI’s simple checkpoint loader workflow (default workflow see beblow).

Recommended Settings

Sampler: res_multistep
Scheduler: linear_quadratic
Steps: 30
CFG (guidance): 4 – 5.5
EmptySD3LatentImage resolution: 1024 × 1024, 768 × 1532, or 968 × 1322

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: 785779037

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
- Experienced users may already fine‑tune via Lumina‑Image‑2.0’s open code.
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氵, ashan, 十分无奈, GHOSTLXH, wenaka, iiiiii, 年糕特工队, 恩匹希, 奶冻, mumu, yizyin, smile

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/

Neta Lumina - Beta-0624 aes-exp