Instructions to use yijunwang2/krea2-outpaint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use yijunwang2/krea2-outpaint 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("krea/Krea-2-Turbo", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("yijunwang2/krea2-outpaint") 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
- Local Apps Settings
- Draw Things
Download showcase/3d_source.webp from yijunwang2/krea2-outpaint: direct link, hf CLI and curl.
- Browser
- Download file 133 kB
-
https://huggingface.co/yijunwang2/krea2-outpaint/resolve/main/showcase/3d_source.webp
- Command line
-
hf download hf://yijunwang2/krea2-outpaint/showcase/3d_source.webp
-
curl -L -o 3d_source.webp https://huggingface.co/yijunwang2/krea2-outpaint/resolve/main/showcase/3d_source.webp
133 kB

- Xet hash:
- 3922294d51f226f93fdb3dbbd413b3d8e4b8c9d21d5697decb2076ae41c1b172
- Size of remote file:
- 133 kB
- SHA256:
- a9820f33bf3b01f98d8eacd90043f93194f067065eff25bb324516342f3e48b5
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