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
File size: 295 Bytes
d575972 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | {
"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"
}
}
}
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