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:
- 4000503f4544d37cf78aea56a681d43ac77465ea805f0dd584fa755a65984358
- Size of remote file:
- 2.07 MB
- SHA256:
- 4c573dae93a526febeaee94c0fe08a330b1ceac90b35833829def60c1c0d6a86
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