Text-to-Image
Diffusers
ONNX
English
StableDiffusionPipeline
stable-diffusion
sd-1.5
hyper-sd
4-step
photorealistic
Instructions to use Heliosoph/realistic-vision-hyper-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Heliosoph/realistic-vision-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/realistic-vision-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:
- 44c8377c63c937301499b5f2dcfc0dd7752b27c60e071a79027b5bdd14bd19fb
- Size of remote file:
- 3.44 GB
- SHA256:
- fdaa9ed3eb0b6b889118c74260def9192b02b82c482e69cb737b1aece3404709
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