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:
- 55481d6d06b90939a03dc3120f41cc637b3c8e807b5d949e10a6a3683b2d031e
- Size of remote file:
- 492 MB
- SHA256:
- d886ca33addac5b03aa1cb9ee164884d57951ace7e27f0eebb7e7710c2c07ab5
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