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:
- 2f298a34c23018771b7586f3f3b1fe5f86689fee63bff0cb211c5a970efe1dcd
- Size of remote file:
- 563 Bytes
- SHA256:
- 8d3cea0647e5f3650234fe625907def537b68106a04ee5bd24cb840403e516ee
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