Instructions to use maedtb/zimage-f32-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use maedtb/zimage-f32-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("maedtb/zimage-f32-diffusers", 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
The ZImage Base model in F32 format.
This is the originally uploaded weights from the ZImage huggingface repo, before they were deleted and replaced with the down-scaled BF16 version for release--this is not the BF16 release converted to F32.
This model is in the original diffusers format.
- Downloads last month
- 2
Model tree for maedtb/zimage-f32-diffusers
Base model
Tongyi-MAI/Z-Image