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
Upload Juggernaut_Z_V1_by_RunDiffusion_q4_k_m-002.gguf
Browse files
.gitattributes
CHANGED
|
@@ -34,3 +34,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
Juggernaut_Z_V1_by_RunDiffusion_q4_k_s-001.gguf filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
Juggernaut_Z_V1_by_RunDiffusion_q4_k_s-001.gguf filter=lfs diff=lfs merge=lfs -text
|
| 37 |
+
Juggernaut_Z_V1_by_RunDiffusion_q4_k_m-002.gguf filter=lfs diff=lfs merge=lfs -text
|
Juggernaut_Z_V1_by_RunDiffusion_q4_k_m-002.gguf
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c781e7be88ef7ed956094cc7ea29859585b631ae7349d71c07a285245d5a9d26
|
| 3 |
+
size 5151107136
|