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:
- 2c8009fc0a943f1bfb65b0eb3d69fbdeec87db5ff69742eef997609fa6b0376e
- Size of remote file:
- 2.5 GB
- SHA256:
- 1df519349f3f2b6a3c6ff23127dd9b98a78e1f50628cf4037a5a9527c08b767c
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