Create README.md

README.md

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+---
+base_model:
+- Alpha-VLLM/Lumina-Image-2.0
+license: other
+license_name: fair-ai-public-license-1.0-sd
+license_link: https://freedevproject.org/faipl-1.0-sd/
+---
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/655319e00166ff6bd2351948/yp3wklEAT2JJ000dqqr1r.png)
+
+# 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
+
+### Base Model
+
+Request access at https://huggingface.co/neta-art/NetaLumina_Alpha if you are inteseted.
+
+- **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
+
+### HuggingFace Playground
+[Try it here](https://huggingface.co/spaces/neta-art/NetaLumina_T2I_Playground)
+
+### ComfyUI
+Neta Lumina is built on the **Lumina2 Diffusion Transformer (DiT)** framework, please follow these steps precisely.
+
+#### Environment Requirements
+
+Currently Neta Lumina runs only on ComfyUI:
+- Latest ComfyUI installation
+- ≥ 8 GB VRAM
+
+#### Downloads & Installation
+
+**Original (component) release**
+
+1. **Neta Lumina-Beta**
+   - Download link: https://huggingface.co/neta-art/Neta-Lumina/blob/main/neta-lumina-beta-0624.pth  
+   - Save path: `ComfyUI/models/unet/`
+2. **Text Encoder (Gemma-2B)**
+   - Download link:https://huggingface.co/neta-art/Neta-Lumina/resolve/main/gemma_2_2b_fp16.safetensors  
+   - Save path: `ComfyUI/models/text_encoders/`
+3. **VAE Model (16-Channel FLUX VAE)**
+   - Download link: https://huggingface.co/neta-art/Neta-Lumina/resolve/main/ae.safetensors  
+   - Save path: `ComfyUI/models/vae/`
+
+**Workflow**: load [`lumina_workflow.json`](https://huggingface.co/neta-art/NetaLumina_Alpha/blob/main/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 K Sampler
+
+**Simple merged release**  
+Download [`neta-lumina-beta-0624.safetensors`](https://huggingface.co/neta-art/Neta-Lumina/tree/main),  
+`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, or 968 × 1322
+
+## Prompt Book
+
+Detailed prompt guidelines: [**Neta Lumina Prompt Book**](https://nieta-art.feishu.cn/wiki/RVBgwvzBqiCvQ7kOMm1cM6NdnNc)
+
+## 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](https://arxiv.org/pdf/2411.15098)). [**Call for Collaboration!**](https://discord.com/invite/TTTGccjbEa)
+
+## License & Disclaimer
+
+- Neta Lumina is released under the [**Fair AI Public License 1.0‑SD**](https://freedevproject.org/faipl-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)**
+  - Core Trainer **li_li** [Civitai](https://civitai.com/user/li_li) ・ [Hugging Face](https://huggingface.co/heziiiii)
+  - 
+- **Partners**  
+  - **nebulae**: [Civitai](https://civitai.com/user/kitarz) ・ [Hugging Face](https://huggingface.co/NebulaeWis)
+- [**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)
+
+### 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, 奶冻美宣集, mumu, yizyin, smile
+
+## Appendix & Resources
+
+- **TeaCache**: https://github.com/spawner1145/sd-samplers.git  
+- **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