VirtualAddressExtension/Neta-Lumina-v1.0-diffusers

Neta Lumina v1.0 for diffusers library

Neta Lumina Tech Report

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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. We will keep updating.

neta-lumina-v1.0

• Official Release: overall best performance

neta-lumina-beta-0624-raw (archived)

• Primary Goal: General knowledge and anime‑style optimization
• Data Set: >13 million anime‑style images
• >46,000 A100 Hours
• Higher upper limit, suitable for pro users. Check Neta Lumina Prompt Book for better results.

neta-lumina-beta-0624-aes-experimental (archived)

• 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 an older version of raw model)
• User-friendly, suitable for most people.
  

How  to  Use

Try it at Hugging Face playground

Or use it with diffusers:

import torch
from diffusers import Lumina2Pipeline

pipe = Lumina2Pipeline.from_pretrained("VirtualAddressExtension/Neta-Lumina-v1.0-diffusers", torch_dtype=torch.bfloat16)
pipe.enable_model_cpu_offload() #save some VRAM by offloading the model to CPU. Remove this if you have enough GPU power

prompt = "You are an assistant designed to generate anime images based on textual prompts. <Prompt Start> neta, @quasarcake, 1girl, solo, 1girl,solo,bangs,black hair,purple eyes,pink hair,purple hair,multicolored hair,virtual youtuber,hair bun,streaked hair,double bun, school uniform, white shirt, pleated skirt, gentle smile, looking at viewer, sitting, upper body, close-up, soft lighting, depth of field, cherry blossom background, warm lighting, best quality"
image = pipe(
    prompt,
    height=1024,
    width=1024,
    guidance_scale=4.0,
    num_inference_steps=50,
    cfg_trunc_ratio=0.25,
    cfg_normalization=True,
    generator=torch.Generator("cpu").manual_seed(0)
).images[0]
image.save("lumina_demo.png")

Prompt Book

Detailed prompt guidelines: Neta Lumina Prompt Book

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
  • 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 Apache License 2.0
  

Participants & Contributors

• Special thanks to the Alpha‑VLLM team for open‑sourcing Lumina‑Image‑2.0
• Model development: Neta.art Lab (Civitai)
  • Core Trainer: li_li Civitai ・ Hugging Face
    
• Partners
  • nebulae: Civitai ・ Hugging Face
  • 生姜: Hugging Face
  • 孙一
• 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