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:
- 9fe6c6597fcfe2f1b216c50d4e9c9a3c7257328813cfed589eac440541552da5
- Size of remote file:
- 3.29 MB
- SHA256:
- effc0ac612bdc603f422cf23df8457520344d4b08c859b64af5df5e5e6e0a385
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