Instructions to use yunhe1/pose with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use yunhe1/pose with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("yunhe1/pose", 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:
- b52a25ae0950f03dfc11abe9a181b0bb8072fd3b43cb671bd298fe8d71707374
- Size of remote file:
- 20.4 MB
- SHA256:
- cdb731a4203dc91c4dfa28d3a19fb560910f8eca128914144c215b768b6c559a
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