Instructions to use lsqingggg/stable-diffusion-2-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lsqingggg/stable-diffusion-2-1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lsqingggg/stable-diffusion-2-1", 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
- Xet hash:
- 124172ca3093056ad6560820b9a188ab9c1152ffcfb0b99e17ed908358034239
- Size of remote file:
- 681 MB
- SHA256:
- 7bb11b1da63986aaaaefb5ef2100d34109c024ac640cacd9ed697150c1c57f01
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