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
- Draw Things
- DiffusionBee
- Xet hash:
- 0bbf60138a647cc722dc38660996f7e8b560b845975e9506aa2e5bafe915f3d7
- Size of remote file:
- 3.28 MB
- SHA256:
- 3a1ff29a6a008131f10fd3ec6ff97f2a6dff0dbf961901db93513cb5e2804f8c
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