Instructions to use perilli/OCS_Models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use perilli/OCS_Models with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("perilli/OCS_Models", 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:
- 8e25aec64f694b2b16eea9470c2cd258a33b1d22901e13fbaf91f647219f2241
- Size of remote file:
- 106 MB
- SHA256:
- 8b63ab268e9020b0fb7fc9f46e742644d4c9ea6e5d9caf56045f0afb6475db09
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