Text-to-Image
Diffusers
Safetensors
English
ZImageAnyFlow2Pipeline
z-image
anyflow2
distillation
custom-pipeline
Instructions to use kimi000/ZImage-AnyFlow2-4Step-1000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kimi000/ZImage-AnyFlow2-4Step-1000 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kimi000/ZImage-AnyFlow2-4Step-1000", 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
Commit History
Today
-
Publish ZImage AnyFlow2 step-1000 EMA as merged Diffusers pipeline with four-step demo
Verified signature91627db