Instructions to use udg/rpppg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use udg/rpppg 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/rpppg", 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:
- 85a35fb542628f72b07f58ce6bb8f471852b9c16055fd57ab90e2413c41b2b15
- Size of remote file:
- 335 MB
- SHA256:
- 9111e806ec1b9803c749a5ec921f67a21d939c6978871cc66289250a902c0a4d
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