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:
- e361a2f7ee94d5f848be6ea00695a4843c14c6f12df845a280c1fea3803c2b50
- Size of remote file:
- 1.9 MB
- SHA256:
- be76e43d026360dcb2e44288b63d3bae6e623fcd9c247d842314a02f08e767ef
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