Instructions to use VirtualAddressExtension/Neta-Lumina-v1.0-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use VirtualAddressExtension/Neta-Lumina-v1.0-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("VirtualAddressExtension/Neta-Lumina-v1.0-diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
| 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 | |
| <video controls autoplay loop muted playsinline style="max-width:100%; border-radius:8px;"> | |
| <source src="https://pages-r2.neta.art/Neta_Lumina_Flash_PV.webm" type="video/webm" /> | |
| Your browser does not support the video tag. | |
| </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 | |