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:
- a1cb6d992860b50fe31f0d7efa421145ffc1088eace39efcc26a791486e77260
- Size of remote file:
- 2.73 MB
- SHA256:
- 8e4f76a58c293e5cc26a24c8425e0104116a6d8b1cff86e02f8f6610f360a82d
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