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:
- a6564a97078ea89d90037b29d862f7a29108d9e9c2019a2b4246cd272ad7429c
- Size of remote file:
- 1.19 GB
- SHA256:
- 9df48c5ae3205845e5cb4ceac15bb15d31b9e4160aaf70b93f272a51409af249
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