Instructions to use Hanbin42/stable-diffusion-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Hanbin42/stable-diffusion-onnx with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Hanbin42/stable-diffusion-onnx", 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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 38c39a9bfb8a82a8fdf888fd7c4d1c820c87c7f7dd0c5804c09853b90d93bc04
- Size of remote file:
- 198 MB
- SHA256:
- 99421e324c5d3db914a682a789df0dc073a740b7c98c267fe3343672e2ef6e96
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