README.md

---
library_name: diffusers
license: apache-2.0
base_model:
- neta-art/Neta-Lumina
tags:
- diffusers,
- text-to-image
---

# Neta Lumina v1.0 for diffusers library

[**Neta Lumina Tech Report**](https://neta.art/blog/neta_lumina/)

## 📽️ Flash Preview

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</video>

# 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**](https://nieta-art.feishu.cn/wiki/RY3GwpT59icIQlkWXEfcCqIMnQd) 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. 
<br>

# How  to  Use

[Try it at Hugging Face playground](https://huggingface.co/spaces/neta-art/NetaLumina_T2I_Playground)

## Or use it with diffusers:
```python
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**](https://neta.art/blog/neta_lumina_prompt_book/)
<br>

# Community

- Discord: https://discord.com/invite/TTTGccjbEa  
- QQ group: 1039442542
<br>

# 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](https://arxiv.org/pdf/2411.15098)). [**Call for Collaboration!**](https://discord.com/invite/TTTGccjbEa)
<br>

# License & Disclaimer

- Neta Lumina is released under [**Apache License 2.0**](https://www.apache.org/licenses/LICENSE-2.0)
<br>

# 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](https://civitai.com/user/li_li) ・ [Hugging Face](https://huggingface.co/heziiiii)
<br>
- **Partners**  
  - **nebulae**: [Civitai](https://civitai.com/user/kitarz) ・ [Hugging Face](https://huggingface.co/NebulaeWis)
  - **生姜**: [Hugging Face](https://huggingface.co/ssj0021)
  - **孙一**
- [**narugo1992**](https://github.com/narugo1992) & [**deepghs**](https://huggingface.co/deepghs): open datasets, processing tools, and models
- [**Naifu**](https://github.com/Mikubill/naifu) trainer at [Mikubill](https://github.com/Mikubill)
<br>

# Community Contributors

- **Evaluators & developers**: [二小姐](https://huggingface.co/Second222), [spawner](https://github.com/spawner1145), [Rnglg2](https://civitai.com/user/Rnglg2)  
- **Other contributors**: [沉迷摸鱼](https://www.pixiv.net/users/22433944), [poi](https://x.com/poi______1), AshenWitch, [十分无奈](https://www.pixiv.net/users/15750592), [GHOSTLX](https://civitai.com/user/ghostlxh), [wenaka](https://civitai.com/user/Wenaka_), [iiiiii](https://civitai.com/user/Blueberries_i), [年糕特工队](https://x.com/gaonian2331), [恩匹希](https://civitai.com/user/NPCde), 奶冻, [mumu](https://civitai.com/user/mumu520), [yizyin](https://civitai.com/user/yizyin), smile, Yang, 古神, 灵之药, [LyloGummy](https://civitai.com/user/LyloGummy), 雪时
<br>

# 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