Instructions to use NO8D/LightControl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use NO8D/LightControl 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.2-klein-9B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("NO8D/LightControl") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Slider-toolkit-Klein9B

- Prompt
- -
Model description
This is a collection of Slider - LORA, which focuses on control the lighting. If you're looking for an efficient and controllable way to generate images from text, then this collection is definitely worth a try.
Back & Front
Dark & Bright
Soft-light & Hard-light
Left-side light & Right-side light
Bottom light & Top light
Light shadows & Dark shadows
Continuously updating
I'm an independent model and workflow developer. If you like my work and want to support independent development, please consider buying me a cup of coffee to keep this motivation going! Thank you very much.
support 🫡 May the AI-power be with you, see you soon !🫡
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Model tree for NO8D/LightControl
Base model
black-forest-labs/FLUX.2-klein-9B




