Text-to-Image
Diffusers
ONNX
English
StableDiffusionPipeline
stable-diffusion
sd-1.5
hyper-sd
4-step
Instructions to use Heliosoph/absolute-reality-hyper-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Heliosoph/absolute-reality-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/absolute-reality-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
- Draw Things
- DiffusionBee
- Xet hash:
- 70407e3d30489457f943482889fcdf37e220cd424061b358412a21a858f13f19
- Size of remote file:
- 137 MB
- SHA256:
- 37ab771f37fce2ac2a3e0cc60b7396e7154dc6399b1e4902e6e2e06161f7e17d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.