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 t_lineart.PNG from Adapter/t2iadapter: direct link, hf CLI and curl.
- Browser
- Download file 3.05 MB
-
https://huggingface.co/Adapter/t2iadapter/resolve/main/t_lineart.PNG
- Command line
-
hf download hf://Adapter/t2iadapter/t_lineart.PNG
-
curl -L -o t_lineart.PNG https://huggingface.co/Adapter/t2iadapter/resolve/main/t_lineart.PNG
3.05 MB
- Xet hash:
- 4056dafd80685700f6dbc4320917182abe48d151aa9421203821324309ec619b
- Size of remote file:
- 3.05 MB
- SHA256:
- a5616aa3b6b96df5c9794ebe72943cd669c97a165f83a59ce35f3b93ab3fd991
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