Instructions to use maria26/Floor_Plan_LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use maria26/Floor_Plan_LoRA with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("sd-legacy/stable-diffusion-v1-5", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("maria26/Floor_Plan_LoRA") prompt = "Floor plan of a small apartment, few rooms, one bathroom, big kitchen, many windows." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 235107581df8946d5ccd6557910e8d6740180d8375c1d1ad62ad17b61fc15895
- Size of remote file:
- 13 MB
- SHA256:
- 02b66ed131febba516f76d51ffa49e486f0d4d74287a2e6e19baa5c1c214d3a7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.