Instructions to use pidgedough/Paint3d_UVPos_Control with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use pidgedough/Paint3d_UVPos_Control with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("pidgedough/Paint3d_UVPos_Control", 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:
- 321a7110e8e732edcfa14b605e2335268e850afaea6f304f42cf68c5aebf9930
- Size of remote file:
- 1.45 GB
- SHA256:
- ff96b80822245ac0e7c9df4a9d1c3e0d8c5a9f923920fc4f0d232f5219fb9a53
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