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:
- 81a1ce5504b6fd170ac3e223377b4a5d35f79eeac037870869ebfec6c93c1aa9
- Size of remote file:
- 2.76 MB
- SHA256:
- 912f8d1609dff8c12030bdaf14f387e0340f9f432bd4cf405f699711cbe8825c
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