Instructions to use levelife/ReGra-VTON with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use levelife/ReGra-VTON with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("levelife/ReGra-VTON", 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
Download ref_encoder/pytorch_model.bin from levelife/ReGra-VTON: direct link, hf CLI and curl.
- Browser
- Download file 7.15 MB
-
https://huggingface.co/levelife/ReGra-VTON/resolve/main/ref_encoder/pytorch_model.bin
- Command line
-
hf download hf://levelife/ReGra-VTON/ref_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/levelife/ReGra-VTON/resolve/main/ref_encoder/pytorch_model.bin
7.15 MB
- Xet hash:
- a59222b856c52e91cf9c0182fd052f9a61a241d6be212d511ea19eddebd5db1a
- Size of remote file:
- 7.15 MB
- SHA256:
- 96d9eab40c6b5d63612c15901c4ce855d2375c721c2de36cba692679fd63a496
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