Instructions to use RobertML/edge-super-compile-0D with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use RobertML/edge-super-compile-0D with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("RobertML/edge-super-compile-0D", 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
- Xet hash:
- 085ea3eabf51f574c9c1f78dd57c18fe49c4c81e4cb612e2418b2c99ffceb216
- Size of remote file:
- 188 MB
- SHA256:
- 2f021f65e5e14250dd95db8ad25245f9bb2709c22952e31f2aa68403599b7562
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