Instructions to use srcphag/Z-Image-Turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use srcphag/Z-Image-Turbo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("srcphag/Z-Image-Turbo", torch_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:
- 8f5e9f0bfd166f6b0ac1742bc4b9cb3a4f9b5f7f18feb390470ca56e524f5c72
- Size of remote file:
- 9.97 GB
- SHA256:
- a4bbe43ee184a1fb5af4b412d27555f532893bdc3165b1149e304ed82b5d7015
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