Instructions to use superdiff/superdiff-sd-v1-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use superdiff/superdiff-sd-v1-4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("superdiff/superdiff-sd-v1-4", 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
Update README.md
Browse files
README.md
CHANGED
|
@@ -25,7 +25,9 @@ This pipeline shows how to superimpose different text prompts from [Stable Diffu
|
|
| 25 |
from PIL import Image
|
| 26 |
from diffusers import DiffusionPipeline
|
| 27 |
|
|
|
|
| 28 |
image = pipeline("a flamingo", "a candy cane", seed=1, num_inference_steps=1000, batch_size=1)
|
|
|
|
| 29 |
image = Image.fromarray(image.cpu().numpy())
|
| 30 |
image.save("superdiff_output.png")
|
| 31 |
```
|
|
|
|
| 25 |
from PIL import Image
|
| 26 |
from diffusers import DiffusionPipeline
|
| 27 |
|
| 28 |
+
pipeline = DiffusionPipeline.from_pretrained("superdiff/pipeline", custom_pipeline='pipeline', trust_remote_code=True, force_download=True)
|
| 29 |
image = pipeline("a flamingo", "a candy cane", seed=1, num_inference_steps=1000, batch_size=1)
|
| 30 |
+
|
| 31 |
image = Image.fromarray(image.cpu().numpy())
|
| 32 |
image.save("superdiff_output.png")
|
| 33 |
```
|