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
| license: apache-2.0 | |
| base_model: | |
| - Tongyi-MAI/Z-Image | |
| 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. |