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

- Xet hash:
- 1641bd6f80d02a037a9abe8c9b3c64b34852c4c49b61b03f5a89ec85615c8ae0
- Size of remote file:
- 1.59 MB
- SHA256:
- 7e2d4052861101ac24667e95998c9a1504a054eeee5723a395ab86d29a8b20f7
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