Instructions to use facadelighting/facadelightingservices with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use facadelighting/facadelightingservices with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("facadelighting/facadelightingservices") prompt = "\"A modern villa facade at night with elegant architectural lighting, warm white wall washes, LED uplights on columns, soft garden lights, reflections on glass windows, realistic shadows, cinematic style, high-resolution, professional exterior lighting design\"" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
facadelightingservicesai

- Prompt
- "A modern villa facade at night with elegant architectural lighting, warm white wall washes, LED uplights on columns, soft garden lights, reflections on glass windows, realistic shadows, cinematic style, high-resolution, professional exterior lighting design"
- Negative Prompt
- "blurry, low resolution, distorted, overexposed, dark spots, extra objects, people, cars, random colors, messy composition"
Download model
Download them in the Files & versions tab.
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Model tree for facadelighting/facadelightingservices
Base model
black-forest-labs/FLUX.1-dev