Instructions to use Joypop/GDPO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Joypop/GDPO with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Joypop/GDPO", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Upload DAPE.pth
Browse files- ckp/DAPE.pth +3 -0
ckp/DAPE.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:a7028be2edcbe9ab0bd1c4ab6f2a2a86f4b44d32261a4faa50ae10fdd9b2feba
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size 7194489
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