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:
- 201b9cf8e2358e29caa1ca01cb9ddb4ab66612f3ccf0b3b962e5fc4d694230fd
- Size of remote file:
- 857 MB
- SHA256:
- 1fee501deabac72f0ed17610307d7131e3e9d1e838d0363aa3c2b97a6e03fb33
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