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
File size: 792 Bytes
505f047 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | ---
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.
|