Instructions to use Adapter/t2iadapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Adapter/t2iadapter 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("Adapter/t2iadapter", 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
Download res_pose.png from Adapter/t2iadapter: direct link, hf CLI and curl.
- Browser
- Download file 1.45 MB
-
https://huggingface.co/Adapter/t2iadapter/resolve/main/res_pose.png
- Command line
-
hf download hf://Adapter/t2iadapter/res_pose.png
-
curl -L -o res_pose.png https://huggingface.co/Adapter/t2iadapter/resolve/main/res_pose.png
1.45 MB

- Xet hash:
- 92f1ec1586fc635cdb989e8c95b84c9b233e5a95a37b75f20f8bdc9e0cb3abc5
- Size of remote file:
- 1.45 MB
- SHA256:
- f1b58cb6c61927c4cbcd39d0771c9552381b8aa6e502be290039f30c9d6814f3
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