Instructions to use ostris/Z-Image-De-Turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ostris/Z-Image-De-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("ostris/Z-Image-De-Turbo", 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
- Draw Things
- DiffusionBee
The problem of training the Z-Image-De-Turbo model has been solved
#7
by Liyan01 - opened
I will replace the transformer in the original Z-Image-Turbo file with the new transformer from Z-Image-De-Turbo, and you can start training!
Please confirm if this is correct?
but need little bit adjustment of parameters ,