Instructions to use CompVis/stable-diffusion-v1-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CompVis/stable-diffusion-v1-1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-1", 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
KeyError: 'sample'
😎 1
#11 opened about 1 year ago
by
ProgramerSalar
create dataset with latents
#10 opened over 2 years ago
by
csegalin
test iteration
#9 opened almost 3 years ago
by
ksericpro
Add `scale_factor` to vae config.
#6 opened over 3 years ago
by
valhalla
Add `clip_sample=False` to scheduler to make model compatible with DDIM.
#5 opened over 3 years ago
by
patrickvonplaten
Use new pipeline output
#2 opened over 3 years ago
by
pcuenq