Instructions to use imagepipeline/InteriorDesign-Checkpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use imagepipeline/InteriorDesign-Checkpoint with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("imagepipeline/InteriorDesign-Checkpoint", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- cd79c949b6cc47ef1887a9a840547d76f2156edc4ead1237f00f0d627d854b05
- Size of remote file:
- 246 MB
- SHA256:
- 822b8a1b74c8683e557a8586ba53d071937eabeecc7f021175c2ea9b38728c0b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.