Text-to-Image
Diffusers
ONNX
English
StableDiffusionPipeline
stable-diffusion
sd-1.5
hyper-sd
4-step
disney-style
Instructions to use Heliosoph/mo-di-hyper-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Heliosoph/mo-di-hyper-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("Heliosoph/mo-di-hyper-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
Download vae_decoder/model.onnx from Heliosoph/mo-di-hyper-onnx: direct link, hf CLI and curl.
- Browser
- Download file 198 MB
-
https://huggingface.co/Heliosoph/mo-di-hyper-onnx/resolve/main/vae_decoder/model.onnx
- Command line
-
hf download hf://Heliosoph/mo-di-hyper-onnx/vae_decoder/model.onnx
-
curl -L -o model.onnx https://huggingface.co/Heliosoph/mo-di-hyper-onnx/resolve/main/vae_decoder/model.onnx
198 MB
- Xet hash:
- 8bb29824952f2989765b86fbf261e0cb28b93f25bbc52cd4279afcdb96c06e26
- Size of remote file:
- 198 MB
- SHA256:
- 6bb596496b0e61b55ea3d723b4d161e6f5cc7bc99dee73e4950a998a3167e7cf
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