Instructions to use CiaraRowles/IP-Adapter-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CiaraRowles/IP-Adapter-Instruct 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("CiaraRowles/IP-Adapter-Instruct", 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:
- 0a8840b427101fb9a214fc1583356c8522fb1280fef38b839a6ca946829b3287
- Size of remote file:
- 352 MB
- SHA256:
- 8a4e97a38f3f9cdea790af3ec3093219ac3735d78cee319d6fbba261515c2847
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.