Instructions to use jarod2212/HumanUltraReal_XL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jarod2212/HumanUltraReal_XL with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("sdxl", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("jarod2212/HumanUltraReal_XL") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
HumanUltraReal_XL

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Model description
Trigger word: hureal
HumanUltraReal_XL is a modular SDXL LoRA trained on approximately 120 professionally curated images, designed to deliver high‑fidelity realism across a wide range of photographic scenarios. The model focuses on portrait performance, half‑body accuracy, multi‑ethnic consistency, and robust lighting/scene adaptability, while maintaining a neutral, non‑stylized output.
The LoRA was built using a balanced, multi‑concept dataset (faces, lighting, environments, outfits, poses), allowing it to generalize cleanly without imposing a fixed aesthetic. It preserves the structure of the base model while enhancing realism, skin texture, lighting behavior, and subject coherence.
Core Capabilities Portraits (close‑up) High facial fidelity
Clean skin texture
Stable eyes and facial structure
Excellent performance across ethnicities
Strong response to makeup, lighting, and expression prompts
Half‑body Accurate anatomy and proportions
Natural posture and clothing behavior
Strong consistency across indoor/outdoor environments
Excellent light integration (soft, hard, rim, warm, ambient)
Lighting Soft diffused light
Hard directional light
Rim light
Warm/cinematic tones
Studio and natural daylight
Stable shadows and color balance
Environments Studio backgrounds
Indoor ambient light
Outdoor daylight
Urban and natural settings
Clean subject–environment integration
Training Overview Images: ~120
Dataset type: professional, curated, multi‑concept
Architecture: SDXL LoRA (modular training)
Focus: realism, neutrality, flexibility
Goal: enhance realism without imposing style or identity
Recommended Settings Trigger word: hureal
LoRA weight: 0.8 – 1.2
0.8 → more neutral, base‑model‑friendly
1.0 → balanced realism
1.2 → maximum fidelity and detail
Base models: realistic SDXL checkpoints (photo‑oriented)
CFG: 5–7
Resolution: 1024×1024 or higher
Prompting: photographic, minimal, clean
Ideal Use Cases High‑quality portraits
Editorial half‑body shots
Lookbook and fashion concepts
Lighting tests
Multi‑ethnic character creation
Realistic photography workflows
Trigger words
You should use hureal to trigger the image generation.
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