Text-to-Image
Diffusers
Safetensors
English
ZImagePipeline
z-image
juggernaut
openvino-export-candidate
Instructions to use Aminfri/juggernaut-z-fast-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Aminfri/juggernaut-z-fast-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("Aminfri/juggernaut-z-fast-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: cc-by-nc-4.0 | |
| language: | |
| - en | |
| pipeline_tag: text-to-image | |
| library_name: diffusers | |
| base_model: Tongyi-MAI/Z-Image | |
| tags: | |
| - diffusers | |
| - safetensors | |
| - z-image | |
| - juggernaut | |
| - openvino-export-candidate | |
| # Juggernaut Z Fast Diffusers Assembly | |
| This repo is an assembled diffusers-style model intended for OpenVINO export. | |
| It combines: | |
| - Pipeline/config/text-encoder/tokenizer/VAE files copied from `RunDiffusion/Juggernaut-Z-Image` | |
| - Fast transformer weights copied from `RunDiffusion/Juggernaut-Z-Image-Fast/Juggernaut_Z_V1_Fast_FP16.safetensors` | |
| The Fast weight is placed at: | |
| ```text | |
| transformer/diffusion_pytorch_model.safetensors | |
| ``` | |
| Destination repo: `Aminfri/juggernaut-z-fast-diffusers` | |
| RunDiffusion's Fast model is CC BY-NC 4.0. Confirm licensing before commercial use. | |