Instructions to use monkseal555/CIRAcentered with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use monkseal555/CIRAcentered with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("monkseal555/CIRAcentered", 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:
- 2837e5acdd6526750e6b94f8d49c0bab95fccc01365606f7a3d77051d8cfc340
- Size of remote file:
- 2.04 MB
- SHA256:
- 6b295e8a0cda2a9bd1c129f0e950fc2dd85711c2fad3b6d28d89f9ea7d9fa246
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