Instructions to use hafsa000/interior-design with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hafsa000/interior-design 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("hafsa000/interior-design", 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:
- 4e080611eb0725ade024bffc6b096bd8c474d9b65c1ff42fb52832350cc454ec
- Size of remote file:
- 335 MB
- SHA256:
- 34aaf62f17470cbb0d50f865239e69b76ac4817c0ad33f3b9e1a5813c5e3d0ce
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.