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

- Prompt
- -
Model description
Recommended Strength: 0.60 - 0.70 (This version is potent; start lower and adjust up if needed). Trigger Words: While not strictly required, using these tags will force the model to activate specific textures and lighting styles: For the "Camera Roll" Look: amateur digital snapshot, candid, smartphone capture, high ISO noise, direct on-camera flash. For High-Fidelity Details: visible pores, visible vellus hair, subsurface scattering, detailed skin texture. For Optical Realism: wide-angle lens, barrel distortion, chromatic aberration, depth of field.
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Model tree for Yuuuna/RealisticSnapshotZImageTurbo
Base model
Tongyi-MAI/Z-Image-Turbo