Instructions to use CodyOnce/cococoloa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CodyOnce/cococoloa with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CodyOnce/cococoloa", 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:
- b3383e5a37a709fc54e706d9e38475565f55d0ba762a28627431ca16492a5dbf
- Size of remote file:
- 74.2 MB
- SHA256:
- 17f5f8ff8f490f03a4463fe9ea133586420fa970557d44d7fc62432b7ffe1074
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