Instructions to use ukeeba/cv1-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ukeeba/cv1-2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ukeeba/cv1-2", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 5a53b7af82c6495709a8022e7884025102a060517cdde335ecb403827608e0a6
- Size of remote file:
- 246 MB
- SHA256:
- 6d258e8445285177f017329ebaeb101c7f98a9b4030356f20fa52c2c53ff0457
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