Instructions to use arsity/UDAPose-model-weights with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use arsity/UDAPose-model-weights with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("arsity/UDAPose-model-weights", 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:
- c7e31a7a471104522271f84226a8252d765952faa2c1699c70ac6e41e1a5c65c
- Size of remote file:
- 659 MB
- SHA256:
- 21f23a2f17fd455993f9b123d965fba541d4b062625a8724e8e1bda016bda93d
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