Instructions to use SearchingMan/Z-Image-Turbo-student-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SearchingMan/Z-Image-Turbo-student-adapter with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SearchingMan/Z-Image-Turbo-student-adapter", 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:
- 60341199c5731d1b7b0382c2564086ed235875f30b09c814f39c270f7977f01c
- Size of remote file:
- 1.31 MB
- SHA256:
- 90b3bc7238d07b1a528ece3936c922d95480252d061578009e50e4b736e905c8
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