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
File size: 994 Bytes
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tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/b5c581707be7f7e9aed6537cebc55ce6.jpg
text: '-'
base_model: Tongyi-MAI/Z-Image-Turbo
instance_prompt: null
license: apache-2.0
---
# Realistic Snapshot (Z-Image-Turbo)
<Gallery />
## 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.
## Download model
[Download](/Yuuuna/RealisticSnapshotZImageTurbo/tree/main) them in the Files & versions tab.
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