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:
- 85e2dbcbfd3bbdc2567405a37a3d002fa7cefe10c97c0d2b7bf07451b2d3166f
- Size of remote file:
- 1.32 MB
- SHA256:
- e38068594d37127a274b2530046b479ad3a64dcbed68672bae2abc6407e225cd
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