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
metadata
license: creativeml-openrail-m
base_model: runwayml/stable-diffusion-inpainting
instance_prompt: sks chair
tags:
- if
- if-diffusers
- inpaint
- diffusers
- lora
inference: true
LoRA DreamBooth - jordandavis/lucia_wing_chair_lora
These are LoRA adaption weights for runwayml/stable-diffusion-inpainting. The weights were trained on sks chair using DreamBooth. You can find some example images in the following.
LoRA for the text encoder was enabled: True.



