| ### **LoRA Model Card**: `svjack/Qwen_Image_4_Grid_Display_Lora` | |
| #### **Unified Multi-Grid Concept Synthesis** | |
| **Base Model**: `Qwen-Image` (Multi-modal Vision-Language Architecture) | |
| **Core Function**: Generates **4 cohesive image grids** with unified style, composition, and thematic continuity for rapid design exploration. | |
| **Key Strengths**: | |
| - **Layout Consistency**: Seamless alignment of color palettes, perspective, and visual motifs across all grid cells. | |
| - **Style Hybridization**: Integrates diverse LoRA adapters for specialized effects (e.g., anime landscapes, cyberpunk textures). | |
| - **Concept Packaging**: Transforms abstract ideas into 4-variant visual prototypes for design workflows. | |
| - **Efficiency Optimization**: Parallel generation of 4 images with shared latent space constraints. | |
| **MayBe an Inverse Problem**: | |
| - **Scalable Group Inference**: Treat outputs as a set; formulate group inference as a Quadratic Integer Programming (QIP) problem; scale efficiently with progressive pruning. | |
| - **Link**: https://github.com/GaParmar/group-inference | |
| --- | |
| ### **Adapter Configuration Guide** | |
| | Adapter Name | Role | Recommended Weight | | |
| |-------------------------------------|----------------------------------|-------------------| | |
| | `Four_qwen_image_lora-step00002920.safetensors` | **Grid Orchestration** | 1.0 (Mandatory) | | |
| | `qwen-image-japanese-text-lora-step00017000.safetensors` | Traditional Japanese Aesthetics | 1.0 | | |
| | `qwen_image_anime_landscape_lora_v1_000002000.safetensors (weight = 1.5)` | Anime-Scene Enhancement | 1.0-1.5 | | |
| | `qwen_image_infinite_future_lora_v1_000002750.safetensors` | Cyberpunk/Mecha Elements | 1.0-1.5 | | |
| | `qwen_image_black_white_naoki_urasawa_v1.safetensors` | Manga Monochrome Stylization | 1.0-1.5 | | |
| --- | |
| ### **Optimized Example Prompts** | |
| #### **Example 1: Japanese Doll Collection** | |
| **Adapters**: | |
| - `Four_qwen_image_lora` (1.0) | |
| - `qwen-image-japanese-text-lora` (1.0) | |
| **Prompt**: | |
| ``` | |
| "In the style of GPT-4o-Design-Images, Generate 4 image samples for the current design concept and piece them into 4 square blocks." | |
| 1、神社外盛开地樱花下，神社鸟居前，展示传统日式娃娃：穿十二单衣的皇室风格女娃娃，服饰绣有平安时代传统纹样，娃娃手持桧扇。 | |
| 2、神社外盛开地樱花下，神社鸟居前，展示传统日式娃娃：宫廷女官人偶，分别持酒器、乐器和文书，服饰为渐变樱色袿袴。 | |
| 3、神社外盛开地樱花下，神社鸟居前，展示传统日式娃娃：女乐师人偶，持筝、琵琶、笛等雅乐乐器，着萌黄色狩衣。 | |
| 4、神社外盛开地樱花下，神社鸟居前，展示传统日式娃娃：宫女人偶，迷你厨具和牛车模型，两侧立着金屏风与纸灯笼。 | |
| ``` | |
| **Key Features**: | |
| - Unified backdrop: Torii gate + cherry blossom saturation | |
| - Consistent doll proportions and fabric texture | |
| - Symmetric composition with radial focal points | |
|  | |
| --- | |
| #### **Example 2: Cybernetic Vehicle Breakout** | |
| **Adapters**: | |
| - `Four_qwen_image_lora` (1.0) | |
| - `qwen_image_infinite_future_lora` (1.2) | |
| **Prompt**: | |
| ``` | |
| "In the style of GPT-4o-Design-Images, Generate 4 image samples for the current design concept and piece them into 4 square blocks." | |
| 1、金属质感的IPad屏幕内部，一个立体四驱车正在从点亮的屏幕中跃出： 金属边框iPad屏幕亮起，黑色奥迪R8车体搭配橙黄条纹冲破屏幕：车头尖锐如匕首，尾部45°上翘露出碳纤维扩散器，轮胎带立体尖刺纹理；屏幕背景为蓝色电路板光效，裂痕处散发金色粒子； | |
| 2、金属质感的IPad屏幕内部，一个立体四驱车正在从点亮的屏幕中跃出： 金属边框iPad屏幕内红黄撞色宝马M4高速跃出：方正硬朗的车身棱角分明，车顶流线贴纸呈动态模糊，轮毂泛起银色金属反光；背景为霓虹赛道投影，屏幕裂纹泛紫光； | |
| 3、金属质感的IPad屏幕内部，一个立体四驱车正在从点亮的屏幕中跃出： iPad屏幕被白色保时捷911撞裂：流线型车身覆盖蓝色闪电浮雕纹路，可拆卸尾翼悬浮展开，大尺寸轮胎碾压处迸发冰晶特效；背景是深空粒子漩涡； | |
| 4、金属质感的IPad屏幕内部，一个立体四驱车正在从点亮的屏幕中跃出： 半透明红蓝车壳奔驰AMG GT撕裂屏幕跃出：内部V8引擎结构透出机械红光，火焰轮毂旋转残留轨迹，分体车灯射出激光；背景为全息齿轮hologram，边框裂缝溢出蓝电火花。 | |
| ``` | |
| **Key Features**: | |
| - Shared "shattered glass" fracture pattern | |
| - Dynamic vehicle angles at 45° trajectory | |
| - Synced particle effects (gold/blue sparks) | |
|  | |
| --- | |
| #### **Example 3: Snow Globe LEGO Series** | |
| **Adapters**: | |
| - `Four_qwen_image_lora` (1.0) | |
| **Prompt**: | |
| ``` | |
| "In the style of GPT-4o-Design-Images, Generate 4 image samples for the current design concept and piece them into 4 square blocks." | |
| 1、下雪的水晶球，内部为乐高玩具：包含大象、长颈鹿等15种动物模型和可拼砌的游览车。通过大颗粒积木模拟喂食、清洁等互动场景。 | |
| 2、下雪的水晶球，内部为乐高玩具：海盗船、幽灵岛或骷髅要塞。船体设计含可升降帆布、隐藏宝藏舱和可拆卸桅杆。 | |
| 3、下雪的水晶球，内部为乐高玩具：伦敦地标建筑泰晤士河上的塔桥。套装包含4285块积木，细节高度还原，如可开合的桥面、哥特式塔楼及微型车辆。 | |
| 4、下雪的水晶球，内部为乐高玩具：龙与地下城，包含6个人仔及大量奇幻场景元素，如红龙巢穴、宝箱与陷阱机关。 | |
| ``` | |
| **Key Features**: | |
| - Identical snow density and crystal ball refraction | |
| - Minifigure scale consistency (1:87 ratio) | |
| - Thematic color coding per globe (blue/green/red/gold) | |
|  | |
| --- | |
| #### **Example 4: Anime Waterdrop Landscapes** | |
| **Adapters**: | |
| - `Four_qwen_image_lora` (1.0) | |
| - `qwen_image_anime_landscape_lora` (1.5) | |
| **Prompt**: | |
| ``` | |
| "In the style of GPT-4o-Design-Images, Generate 4 image samples for the current design concept and piece them into 4 square blocks." | |
| 1、一个占据整个画面的巨大圆形水滴，水滴下是一个3D立体动漫画面，由水滴的弧度凸显出立体性：anime style, 晨光穿透薄雾洒落樱花山谷，粉白花瓣覆盖蜿蜒溪流，朱红拱桥横跨两岸，远处青山层叠如黛；卷轴边缘泛黄，金色云纹浮动 | |
| 2、一个占据整个画面的巨大圆形水滴，水滴下是一个3D立体动漫画面，由水滴的弧度凸显出立体性：anime style, 暮色中的樱花湖畔，橙红晚霞浸染水面，青石小径延伸至红木舟停泊处，花瓣飘落涟漪；卷轴两侧题有银色诗句残影 | |
| 3、一个占据整个画面的巨大圆形水滴，水滴下是一个3D立体动漫画面，由水滴的弧度凸显出立体性：anime style, 月下荧光樱花林，深蓝夜幕中花瓣如星闪烁，石灯笼沿苔藓小径排列，微光映照飘雪般的落英；卷轴裱布呈暗红织锦纹理 | |
| 4、一个占据整个画面的巨大圆形水滴，水滴下是一个3D立体动漫画面，由水滴的弧度凸显出立体性：anime style, 晨雾缭绕的樱花台地，乳白雾气缠绕青松，悬崖观景台俯瞰云海，风卷起花瓣如粉色浪涛；卷轴轴头为青玉雕花，边缘水墨晕染 | |
| ``` | |
| **Key Features**: | |
| - Curvature lens effect across all droplets | |
| - Shared scroll border design with variations | |
| - Time-of-day progression (dawn → dusk → night → dawn) | |
|  | |
| --- | |
| #### **Example 5: Monochrome Robot Narrative** | |
| **Adapters**: | |
| - `Four_qwen_image_lora` (1.0) | |
| - `qwen_image_black_white_naoki` (0.9) | |
| **Prompt**: | |
| ``` | |
| "In the style of GPT-4o-Design-Images, Generate 4 image samples for the current design concept and piece them into 4 square blocks." | |
| 1、日式黑白漫画：一个机器人在月下躺在沙漠里。周围是仙人掌和月色。 | |
| 2、日式黑白漫画：一个戴眼镜的男孩接近沙漠中躺着的机器人，在机器人身上进行修理。 | |
| 3、日式黑白漫画：机器人醒来，头边有一个白色气泡，里面有文字“谢谢!” | |
| 4、日式黑白漫画：男孩和机器人手拉手走向远处的绿洲。 | |
| ``` | |
| **Key Features**: | |
| - Consistent Urasawa-style screentone patterns | |
| - Progressive panel sequencing (isolated → interaction → resolution) | |
| - Shadow density gradient matching time progression | |
|  | |
| --- | |
| ### **Technical Parameters** | |
| | Setting | Value | Notes | | |
| |------------------|-------------------|----------------------------------------| | |
| | **Resolution** | 1024x1024 | Optimal grid detail retention | | |
| | **CFG Scale** | 7.5 | Balances creativity vs. prompt fidelity| | |
| | **Sampler** | DPM++ 2M Karras | Preserves fine linework | | |
| | **Steps** | 25 | Critical for texture coherence | | |
| | **LoRA Rank (r)**| 32 | High complexity demands (see ) | | |
| | **LoRA Alpha** | 64 | α=2r for multi-adapter fusion (see ) | | |
| --- | |
| ### **Performance Profile** | |
| - **VRAM Usage**: ~18GB at 1024x1024 (RTX 4090) | |
| - **Generation Speed**: 12-18 sec/grid (4 images) | |
| - **Troubleshooting**: | |
| - **Grid Misalignment**: Add `4x4 uniform matrix, isometric perspective` to prompt | |
| - **Style Bleed**: Reduce non-core LoRA weights by 0.3 | |
| - **Color Inconsistency**: Enable `--color_sync_node` in inference pipeline | |
| ### **License** | |
| Apache 2.0 (Commercial use permitted) | |
| **Community Hub**: https://huggingface.co/svjack/Qwen_Image_4_Grid_Display_Lora | |
| --- |