Instructions to use MnLgt/lucia_wing_chair_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MnLgt/lucia_wing_chair_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("runwayml/stable-diffusion-inpainting", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("MnLgt/lucia_wing_chair_lora") prompt = "sks chair" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things

- Xet hash:
- d3b58cc1e5b37c8688a5968bd581adba8b6c7350fba4b29cfc22c85882acdaa3
- Size of remote file:
- 324 kB
- SHA256:
- fe5a95439e2766949a596afd87f02b0332a2045041cb681d2fc9e003d49044df
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.