Text-to-Image
Diffusers
ONNX
English
StableDiffusionPipeline
stable-diffusion
sd-1.5
hyper-sd
4-step
Instructions to use Heliosoph/dreamshaper-hyper-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Heliosoph/dreamshaper-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/dreamshaper-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:
- 2f04201f943756c92dceacc685dc2b2cafdf9d0cbf64c8842e4a51c892b8be69
- Size of remote file:
- 3.44 GB
- SHA256:
- b7b0caf5f84d493a3aa8650548253a9c2632ea2670db991c3bf70bc29baf92ca
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