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_encoder/model.onnx from Heliosoph/mo-di-hyper-onnx: direct link, hf CLI and curl.
- Browser
- Download file 137 MB
-
https://huggingface.co/Heliosoph/mo-di-hyper-onnx/resolve/main/vae_encoder/model.onnx
- Command line
-
hf download hf://Heliosoph/mo-di-hyper-onnx/vae_encoder/model.onnx
-
curl -L -o model.onnx https://huggingface.co/Heliosoph/mo-di-hyper-onnx/resolve/main/vae_encoder/model.onnx
137 MB
- Xet hash:
- 16a44ec5f62d09703e6905f7ea7032a62b0902ad1d7bb8459b78fadd1690da8e
- Size of remote file:
- 137 MB
- SHA256:
- ed837d5e537f8396e8308828f71f75b5a41daf6a63118d8e34e3ba4051e3c6e1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.