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:
- 5211ac69743c0891b111ccb7217af8f18d388f979d6ac582d9e0c97d200e1108
- Size of remote file:
- 557 Bytes
- SHA256:
- 9465a7da2e0970f4d884d83d8387cc4e08a9346456948a6f16fbe2b22367af3c
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