Text-to-Image
Diffusers
Safetensors
English
ZImageAnyFlow2Pipeline
z-image
anyflow2
distillation
custom-pipeline
Instructions to use kimi000/ZImage-4Step-3000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kimi000/ZImage-4Step-3000 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-4Step-3000", 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
Download example.png from kimi000/ZImage-4Step-3000: direct link, hf CLI and curl.
- Browser
- Download file 1.42 MB
-
https://huggingface.co/kimi000/ZImage-4Step-3000/resolve/main/example.png
- Command line
-
hf download hf://kimi000/ZImage-4Step-3000/example.png
-
curl -L -o example.png https://huggingface.co/kimi000/ZImage-4Step-3000/resolve/main/example.png
1.42 MB

- Xet hash:
- ec5fb6f2480005e988099321c1f4b4bc9e04238b242505cd067aab9b5b1c3b1c
- Size of remote file:
- 1.42 MB
- SHA256:
- e0b4a92bb515bd872a8094cec0b173c68b6fda3350f2e3d6d48d03aa539563a6
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