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:
- 3adfd0ccfc0e0da53478b66c17d1cf99ad30e36547c6a140961f425b50ad15b0
- Size of remote file:
- 7.7 GB
- SHA256:
- f07cad74c4adce52ca14ca1bdf74cf3c14cbafb0823b95eca4459467fa369f40
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