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:
- a8e49e4bc20583a6d7fa458a3582dfd631368db0334ba2daedb0673f3fbd74a5
- Size of remote file:
- 1.44 MB
- SHA256:
- d3a80e0830bccdd3827499fd61db2fac4eca233bbeaa364c0224cfb82715ccd0
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