Instructions to use mzbac/Z-Image-Turbo-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mzbac/Z-Image-Turbo-8bit with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mzbac/Z-Image-Turbo-8bit", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- b3eaa691a06817a4e123594bdaec8586d2ab1c14bbf71b0ba93643fed2b94971
- Size of remote file:
- 15.8 MB
- SHA256:
- 6f9895b3246d2547bac74bbe0be975da500eaae93f2cad4248ad3281786b1ac6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.