Instructions to use RunDiffusion/Juggernaut-Z-Image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use RunDiffusion/Juggernaut-Z-Image with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("RunDiffusion/Juggernaut-Z-Image", 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
- Draw Things
- DiffusionBee
Clarify comparison labels in model card
Browse files
README.md
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@@ -42,6 +42,8 @@ Juggernaut Z is tuned for a more presentation-ready look out of the box. Relativ
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The images below are pulled from the RunDiffusion announcement page for Juggernaut Z.
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The images below are pulled from the RunDiffusion announcement page for Juggernaut Z.
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**Comparison label:** Left = **Juggernaut Z** | Right = **Z-Image Base**
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