Instructions to use udg/rpppgic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use udg/rpppgic with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("udg/rpppgic", 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:
- 973b25599d78944105689d6ed0dd42cf5af47efed536f4b3a79cbb81fde8fdda
- Size of remote file:
- 492 MB
- SHA256:
- 002f4cdd9b96c6d23d89ef868303afb9083e86353dd331a7f5f01963fc95ea13
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