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
| { | |
| "model_type": "stable-diffusion-onnx", | |
| "components": { | |
| "text_encoder": { | |
| "path": "text_encoder/text_encoder.onnx" | |
| }, | |
| "unet": { | |
| "path": "unet/unet.onnx" | |
| }, | |
| "vae_decoder": { | |
| "path": "vae_decoder/vae_decoder.onnx" | |
| } | |
| } | |
| } | |