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:
- 1e7feaed003d67138aec402a141862548a99ede27f08c3bae52ac23933433a3b
- Size of remote file:
- 137 MB
- SHA256:
- 71f45047e27ebc7a005d8d26d412fd7547ddaad1b632fdb637d733bf3a88155e
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