Instructions to use StonyBrook-CVLab/PixCell-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use StonyBrook-CVLab/PixCell-256 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("StonyBrook-CVLab/PixCell-256", 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
Upload pixcell_256_banner.png
Browse files- .gitattributes +1 -0
- pixcell_256_banner.png +3 -0
.gitattributes
CHANGED
|
@@ -35,3 +35,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
test_image.jpg filter=lfs diff=lfs merge=lfs -text
|
| 37 |
test_image.png filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
test_image.jpg filter=lfs diff=lfs merge=lfs -text
|
| 37 |
test_image.png filter=lfs diff=lfs merge=lfs -text
|
| 38 |
+
pixcell_256_banner.png filter=lfs diff=lfs merge=lfs -text
|
pixcell_256_banner.png
ADDED
|
Git LFS Details
|