Instructions to use bdsager/CatVTON with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bdsager/CatVTON with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("bdsager/CatVTON", 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
Upload CatVTON.zip
Browse files
- CatVTON.zip +3 -0
CatVTON.zip
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version https://git-lfs.github.com/spec/v1
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oid sha256:467aff99cc30eeecb4000287f4cea7020de9991bcbdd4cbe2beefc825c4150cd
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size 3186507975
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