Instructions to use GD-ML/Omni-Effects with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use GD-ML/Omni-Effects with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("GD-ML/Omni-Effects", 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
Download teaser.jpg from GD-ML/Omni-Effects: direct link, hf CLI and curl.
- Browser
- Download file 3.4 MB
-
https://huggingface.co/GD-ML/Omni-Effects/resolve/main/teaser.jpg
- Command line
-
hf download hf://GD-ML/Omni-Effects/teaser.jpg
-
curl -L -o teaser.jpg https://huggingface.co/GD-ML/Omni-Effects/resolve/main/teaser.jpg
3.4 MB

- Xet hash:
- faaff84d164effb7d270538bf1bedeb9637fa965881602bb91d99d5627dc7200
- Size of remote file:
- 3.4 MB
- SHA256:
- e6a5dfad52c0741e625da58fab87d48719985daed4329cf0c5df58c146a42db5
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