Image-to-Image
Diffusers
StableDiffusionImageVariationPipeline
stable-diffusion
stable-diffusion-diffusers
Instructions to use lambda/sd-image-variations-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lambda/sd-image-variations-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lambda/sd-image-variations-diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Commit ·
d7246ca
1
Parent(s): 81640d8
Add `clip_sample=False` to scheduler to make model compatible with DDIM. (#7)
Browse files- Add `clip_sample=False` to scheduler to make model compatible with DDIM. (f0c29c067d5cf5ac9997bd75ea6cd0732383b4b5)
Co-authored-by: Patrick von Platen <patrickvonplaten@users.noreply.huggingface.co>
scheduler/scheduler_config.json
CHANGED
|
@@ -4,6 +4,7 @@
|
|
| 4 |
"beta_end": 0.012,
|
| 5 |
"beta_schedule": "scaled_linear",
|
| 6 |
"beta_start": 0.00085,
|
|
|
|
| 7 |
"num_train_timesteps": 1000,
|
| 8 |
"set_alpha_to_one": false,
|
| 9 |
"skip_prk_steps": true,
|
|
|
|
| 4 |
"beta_end": 0.012,
|
| 5 |
"beta_schedule": "scaled_linear",
|
| 6 |
"beta_start": 0.00085,
|
| 7 |
+
"clip_sample": false,
|
| 8 |
"num_train_timesteps": 1000,
|
| 9 |
"set_alpha_to_one": false,
|
| 10 |
"skip_prk_steps": true,
|