Instructions to use CedarC/Z-Image_360 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CedarC/Z-Image_360 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("CedarC/Z-Image_360") prompt = "test" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Z-Image_360

- Prompt
- test
Model description
Generate 360 images with Z-image-Turbo. Use trigger word: 360panorama
Trigger words
You should use 360panorama to trigger the image generation.
Download model
Download them in the Files & versions tab.
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Model tree for CedarC/Z-Image_360
Base model
Tongyi-MAI/Z-Image-Turbo