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:
- 4bb176d2cd9448b5d76a2d730f684b7dc326bab6f79c7fc50a93f810129fb1e3
- Size of remote file:
- 703 MB
- SHA256:
- ba1002529e783604c5f326d49f0122025392d1d20ac8d573b3eeb3e6dea4ebb6
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