Instructions to use InstantX/SD3-Controlnet-Canny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use InstantX/SD3-Controlnet-Canny with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("InstantX/SD3-Controlnet-Canny", 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
Update README.md
Browse files
README.md
CHANGED
|
@@ -21,7 +21,7 @@ pip install -e .
|
|
| 21 |
# Demo
|
| 22 |
```python
|
| 23 |
import torch
|
| 24 |
-
from diffusers.utils
|
| 25 |
import sys, os
|
| 26 |
sys.path.append('/path/diffusers/examples/community')
|
| 27 |
from pipeline_stable_diffusion_3_controlnet import StableDiffusion3CommonPipeline
|
|
|
|
| 21 |
# Demo
|
| 22 |
```python
|
| 23 |
import torch
|
| 24 |
+
from diffusers.utils import load_image
|
| 25 |
import sys, os
|
| 26 |
sys.path.append('/path/diffusers/examples/community')
|
| 27 |
from pipeline_stable_diffusion_3_controlnet import StableDiffusion3CommonPipeline
|