Instructions to use drbaph/Z-Image-fp8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use drbaph/Z-Image-fp8 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("drbaph/Z-Image-fp8", 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

- Xet hash:
- 6109cda98c8a402348dba974840918501566c6749f2cce7c0f184c27dae97c69
- Size of remote file:
- 4.54 MB
- SHA256:
- 09e25ae0a4c99a571666ba7975b5031ff7d6e774cc07b4ba84f698ecf9e34782
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.