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
Download text_encoder/pytorch_model.bin from hafsa000/interior-design: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/hafsa000/interior-design/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://hafsa000/interior-design/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hafsa000/interior-design/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 6881377151157cb4572b680f14917778f3a1896916a911adc62641290e3583ec
- Size of remote file:
- 492 MB
- SHA256:
- 8241f415f8928554e4ab48fe49f8f7076e524a92bfd8be9b860978ece38adfec
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