--- base_model: stabilityai/stable-diffusion-xl-base-1.0 library_name: diffusers pipeline_tag: text-to-image license: openrail++ tags: - diffusers - stable-diffusion-xl - sdxl - lora - text-to-image - king2 - arabic - art - image-generation - fal-ai inference: parameters: guidance_scale: 7.5 negative_prompt: blurry, low quality, distorted, ugly, bad anatomy, watermark, text, signature widget: - text: a futuristic royal palace at sunset, highly detailed, 8k, golden hour, epic composition output: url: https://huggingface.co/RASHID778/king2-image/resolve/main/examples/example_01.png - text: majestic arabian knight on horseback, desert landscape, cinematic lighting, photorealistic, 4k output: url: https://huggingface.co/RASHID778/king2-image/resolve/main/examples/example_02.png - text: ancient library with floating books, mystical atmosphere, volumetric lighting, detailed illustration output: url: https://huggingface.co/RASHID778/king2-image/resolve/main/examples/example_03.png - text: cosmic king on a throne of stars, nebula background, majestic, epic fantasy, concept art output: url: https://huggingface.co/RASHID778/king2-image/resolve/main/examples/example_04.png datasets: - jackyhate/text-to-image-2M language: - en - ar thumbnail: https://huggingface.co/RASHID778/king2-image/resolve/main/examples/example_01.png ---

KING2 Image Banner

πŸ‘‘ KING2-IMAGE β€” SDXL LoRA

A Stable Diffusion XL LoRA (rank 16) fine-tuned for majestic, high-quality text-to-image generation with a distinctive aesthetic.

Hugging Face Spaces License KING2 Series

--- ## πŸ“‹ Overview **KING2-IMAGE** is a **Stable Diffusion XL LoRA adapter** (rank 16) trained on a 3,000-image subset of the [jackyhate/text-to-image-2M](https://huggingface.co/datasets/jackyhate/text-to-image-2M) dataset. It is designed to produce visually striking, detailed, and aesthetically refined images β€” from majestic royal scenes and cinematic landscapes to fantasy art and photorealistic portraits. Built as part of the **KING2 AI ecosystem**, this model inherits the "royal" essence of the KING2 brand, excelling at generating images with grandeur, rich color palettes, and epic compositions. | Property | Value | |----------|-------| | **Base Model** | [`stabilityai/stable-diffusion-xl-base-1.0`](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0) | | **VAE (training)** | [`madebyollin/sdxl-vae-fp16-fix`](https://huggingface.co/madebyollin/sdxl-vae-fp16-fix) | | **LoRA Rank** | 16 | | **Resolution** | 768Γ—768 | | **Training Steps** | 1,500 | | **Precision** | fp16 | | **Library** | [🧨 Diffusers](https://github.com/huggingface/diffusers) | | **License** | [OpenRAIL++](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/LICENSE.md) | --- ## ✨ Features - **🎨 Refined Aesthetic** β€” Fine-tuned on high-quality synthetic image-text pairs emphasizing composition and visual appeal. - **πŸ‘‘ Royal & Majestic Style** β€” Excels at grand, epic, and regal image generation β€” palaces, knights, kings, fantasy worlds. - **🌍 Bilingual Prompt Support** β€” Works with both English and Arabic prompts (Arabic prompts may require transliteration or English for best results). - **⚑ Lightweight Adapter** β€” Only ~93 MB LoRA weights; combines with the base SDXL model for a total footprint manageable on consumer GPUs. - **πŸ•΄οΈ Stickman Adapter Included** β€” A second LoRA in [`stickman/`](https://huggingface.co/RASHID778/king2-image/tree/main/stickman) for stick-figure pose illustrations (see below). - **πŸ”„ Diffusers Native** β€” Drop-in compatible with the Hugging Face Diffusers ecosystem; easy to integrate into existing pipelines. --- ## πŸ‹οΈ Training Details ### Dataset | Property | Detail | |----------|--------| | **Source** | [`jackyhate/text-to-image-2M`](https://huggingface.co/datasets/jackyhate/text-to-image-2M) | | **Subset Size** | 3,000 images (sampled from the dataset stream) | | **Resolution** | 768Γ—768 (center-cropped) | | **Format** | Image-Text pairs | The training used a 3,000 image-text pair sample from the text-to-image-2M dataset β€” a large collection of high-quality synthetic images with descriptive captions covering diverse scenes (nature, architecture, fantasy, portraits, landscapes). ### Hyperparameters | Parameter | Value | |-----------|-------| | **Base Model** | `stabilityai/stable-diffusion-xl-base-1.0` | | **VAE** | `madebyollin/sdxl-vae-fp16-fix` | | **LoRA Rank (r)** | 16 | | **LoRA Alpha** | 16 | | **Resolution** | 768 Γ— 768 | | **Optimizer** | AdamW (8-bit) | | **Learning Rate** | 1e-4 | | **LR Scheduler** | Cosine | | **Training Steps** | 1,500 | | **Batch Size** | 1 (per device) | | **Gradient Accumulation** | 4 | | **Mixed Precision** | fp16 | | **Checkpoints Saved** | Every 500 steps (checkpoint-500, checkpoint-1000, checkpoint-1500) | ### Checkpoints | Checkpoint | Steps | Description | |------------|-------|-------------| | `checkpoint-500` | 500 | Early snapshot β€” good for broad compositional styles | | `checkpoint-1000` | 1,000 | Mid-training β€” balanced detail and coherence | | `checkpoint-1500` | **1,500 (final)** | Fully trained β€” recommended for best results | --- ## πŸ“¦ Installation ### Requirements - Python β‰₯ 3.10 - PyTorch β‰₯ 2.0.0 - CUDA-compatible GPU with β‰₯ 8 GB VRAM (recommended) - Hugging Face Diffusers, Transformers, Accelerate ### Setup ```bash # Create a virtual environment (recommended) python -m venv venv source venv/bin/activate # Linux/macOS # .\venv\Scripts\activate # Windows # Install dependencies pip install -U diffusers transformers accelerate torch safetensors ``` --- ## πŸš€ Usage ### Basic Inference ```python import torch from diffusers import DiffusionPipeline, AutoencoderKL # Optional but recommended: the fp16-safe VAE used during training vae = AutoencoderKL.from_pretrained( "madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16, ) # Load the base SDXL pipeline pipe = DiffusionPipeline.from_pretrained( "stabilityai/stable-diffusion-xl-base-1.0", vae=vae, torch_dtype=torch.float16, variant="fp16", use_safetensors=True, ) pipe.to("cuda") # Load the KING2-IMAGE LoRA adapter pipe.load_lora_weights("RASHID778/king2-image") # Generate prompt = "a futuristic royal palace at sunset, highly detailed, 8k, golden hour" image = pipe( prompt, num_inference_steps=30, guidance_scale=7.5, height=768, width=768, negative_prompt="blurry, low quality, distorted, ugly, bad anatomy, watermark, text", ).images[0] image.save("king2_output.png") ``` ### LoRA Weight Configuration You can adjust the LoRA influence scale for finer control: ```python pipe.load_lora_weights("RASHID778/king2-image", adapter_name="king2") pipe.set_adapters(["king2"], adapter_weights=[0.85]) # scale from 0.0 to 1.0 ``` --- ## πŸ•΄οΈ Stickman Adapter The repo also ships a **second LoRA adapter** at [`stickman/pytorch_lora_weights.safetensors`](https://huggingface.co/RASHID778/king2-image/tree/main/stickman) β€” a style/pose adapter that makes SDXL draw **stick-figure illustrations** across a wide range of human poses and actions (run, jump, kick, sit, climb, dance…). Trained on 10,000 curated 1024Γ—1024 stick-figure frames derived from HumanML3D motion sequences (quality-scored, de-duplicated, captioned from the official HumanML3D texts). ```python pipe.load_lora_weights( "RASHID778/king2-image", weight_name="stickman/pytorch_lora_weights.safetensors", adapter_name="stickman", ) image = pipe( "a stickman doing a backflip, simple black and white stick figure line drawing", num_inference_steps=30, guidance_scale=7.0, ).images[0] ``` **Prompting tips:** - Keep the trigger phrasing seen in training: `…, simple black and white stick figure line drawing`. - Best at **single-figure** body poses/actions; multi-figure scenes are out of distribution. - LoRA scale **0.8–1.0** (lower toward 0.6 if the pose collapses), guidance 6–8, 25–35 steps. - Style is fixed: thick-stroke skeleton on white background β€” no head circle, colors, props, or backgrounds. > ⚠️ The stickman adapter's training data derives from HumanML3D (AMASS/HumanAct12). Treat it as **research use**; review upstream licensing before commercial deployment. --- ### Inference Providers (Zero Setup) You can run the LoRA without any local GPU via **fal.ai**: ```python # pip install fal-client (and set FAL_KEY) import fal_client result = fal_client.subscribe( "fal-ai/lora", arguments={ "model_name": "stabilityai/stable-diffusion-xl-base-1.0", "loras": [{ "path": "https://huggingface.co/RASHID778/king2-image/resolve/main/pytorch_lora_weights.safetensors", "scale": 0.85, }], "prompt": "cosmic king on a throne of stars, nebula background, majestic, epic fantasy", "negative_prompt": "blurry, low quality", "image_size": "square", "guidance_scale": 7.5, "num_inference_steps": 30, }, ) print(result["images"][0]["url"]) ``` You can also use the **Inference Providers** widget on this model page (powered by fal-ai) with zero setup. --- ## 🎯 Example Prompts Here are some prompts that work exceptionally well with KING2-IMAGE: ### Royal & Majestic | Prompt | Style | |--------|-------| | `a futuristic royal palace at sunset, highly detailed, 8k, golden hour, epic composition` | Cinematic / Epic | | `majestic arabian knight on horseback, desert landscape, cinematic lighting, photorealistic, 4k` | Photorealistic | | `cosmic king on a throne of stars, nebula background, majestic, epic fantasy, concept art` | Fantasy Art | | `ancient king with golden crown, ornate throne room, dramatic lighting, oil painting style` | Classical Art | ### Fantasy & Mystical | Prompt | Style | |--------|-------| | `ancient library with floating books, mystical atmosphere, volumetric lighting, detailed illustration` | Illustrative | | `enchanted forest with glowing crystals, magical blue and purple hues, fantasy landscape, detailed` | Fantasy | | `dragon coiled around a crystal tower, stormy sky, epic scale, cinematic, 8k` | Epic Fantasy | ### Architecture & Scenery | Prompt | Style | |--------|-------| | `grand mosque at night, illuminated, reflective pool, stars, ultra detailed, architectural photography` | Architectural | | `oriental garden with water fountain, blooming flowers, warm sunlight, peaceful, highly detailed` | Scenic | | `massive marble palace with golden domes, symmetrical composition, bright blue sky, majestic` | Symmetrical | ### Arabic / Middle Eastern Themes | Prompt | Style | |--------|-------| | `arabian fortress at dawn, sandstorm clearing, golden light, cinematic wide shot` | Cinematic | | `traditional arabian market alley, lanterns, warm colors, detailed architecture, bustling` | Detailed | --- ## πŸ–ΌοΈ Example Images

Example 1 β€” Futuristic royal palace at sunset Example 2 β€” Majestic arabian knight on horseback

Example 3 β€” Ancient library with floating books Example 4 β€” Cosmic king on a throne of stars

Images generated with KING2-IMAGE using prompts from the example tables above.

--- ## ⚠️ Limitations - **Resolution Constraint** β€” Trained at 768Γ—768. Higher resolutions (>1024) may produce artifacts or quality degradation. - **Synthetic Training Data** β€” The training subset consists of AI-generated images, so the adapter inherits the visual style (and any artifacts) of the generator used to build the source dataset. - **Domain Specificity** β€” Fine-tuned primarily for majestic, royal, and fantasy aesthetics. May not perform optimally on unrelated domains (e.g., modern tech, medical imagery, abstract minimalism). - **Bias & Representation** β€” As with all generative models trained on web-scale data, the model may reflect biases present in the training dataset. Use responsibly and critically evaluate outputs. - **Arabic Prompts** β€” The model was trained primarily on English captions. Arabic prompts may produce less reliable results; transliteration to English is recommended. - **Not a Checkpoint** β€” This is a LoRA adapter only. The base SDXL model must be loaded separately (requires ~12 GB VRAM for full pipeline). - **Safety** β€” The model has not been fine-tuned for safety filtering. Always use appropriate NSFW/content filters in production deployments. --- ## πŸ”¬ Technical Notes - The adapter was trained using the Diffusers `train_text_to_image_lora_sdxl.py` script. - All checkpoints use `.safetensors` format for secure and fast loading. - Xet storage is used on Hugging Face for efficient large-file hosting. - Available for live inference via the fal-ai Inference Provider on Hugging Face. --- ## πŸ“œ License This model is released under the **OpenRAIL++** license (inherited from [`stabilityai/stable-diffusion-xl-base-1.0`](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/LICENSE.md)), which permits: - βœ… **Use** β€” Free to use for both research and commercial purposes - βœ… **Modification** β€” You may fine-tune, adapt, or modify the weights - βœ… **Distribution** β€” You may share the weights and derivatives **Conditions:** - ❗ You must not use the model to generate illegal or harmful content - ❗ You must include the same license when redistributing - ❗ You must not use the model to violate any applicable laws > Note: the **stickman adapter** has additional upstream data considerations β€” see the Stickman Adapter section above. --- ## πŸ›οΈ KING2 Ecosystem KING2-IMAGE is part of the **KING2 AI Series**: | Model | Type | Description | |-------|------|-------------| | [`king2-qwen2.5-3b`](https://huggingface.co/RASHID778/king2-qwen2.5-3b) | LLM (LoRA) | Arabic conversational AI assistant with royal persona | | [`king2-image`](https://huggingface.co/RASHID778/king2-image) | SDXL LoRA | Text-to-image generation with majestic aesthetic | | [`king2-image` β†’ `stickman/`](https://huggingface.co/RASHID778/king2-image/tree/main/stickman) | SDXL LoRA | Stick-figure pose illustration adapter | | [KING2 Space](https://huggingface.co/spaces/RASHID778/king2-qwen2.5-3b) | Demo | Try the KING2 experience live | --- ## πŸ™ Acknowledgements - [Stability AI](https://stability.ai/) for the SDXL base model - [@jackyhate](https://huggingface.co/jackyhate) for the text-to-image-2M dataset - [@madebyollin](https://huggingface.co/madebyollin) for the fp16 VAE fix - [Hugging Face](https://huggingface.co) for the Diffusers library and model hosting - [fal-ai](https://fal.ai) for the inference provider integration --- ## πŸ“¬ Contact & Community - **Author:** [RASHID778](https://huggingface.co/RASHID778) - **GitHub:** [MOT1209](https://github.com/MOT1209) - **Report Issues:** [Community Tab](https://huggingface.co/RASHID778/king2-image/discussions) ---

Made with πŸ‘‘ by RASHID778
Part of the KING2 AI Series β€” Royal Intelligence