Instructions to use hosnasn/interio_design_office with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hosnasn/interio_design_office with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hosnasn/interio_design_office", 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
Download text_encoder/pytorch_model.bin from hosnasn/interio_design_office: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/hosnasn/interio_design_office/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://hosnasn/interio_design_office/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hosnasn/interio_design_office/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 9a6ca4d97ac02a15363a2a4e817a831204dda9c4a08f9d6aa29ffcb6ef742991
- Size of remote file:
- 246 MB
- SHA256:
- ccf84ce0c4c5f7860bedd9e3ae9f87db809e68a283626d6c1a18106c4af1a7fe
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.