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", torch_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
| license: apache-2.0 | |
| base_model: | |
| - CompVis/stable-diffusion-v1-4 | |
| pipeline_tag: text-to-image | |
| library_name: diffusers | |
| Convert U-Net, text encoder, and VAE decoder to ONNX. |