Instructions to use ilkerzgi/Overlay-Kontext-Dev-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ilkerzgi/Overlay-Kontext-Dev-LoRA with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ilkerzgi/Overlay-Kontext-Dev-LoRA") prompt = "Place it" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
Kontext Dev LoRA - Image Overlay

- Prompt
- Place it

- Prompt
- Place it

- Prompt
- Place it
This is a LoRA (Low-Rank Adaptation) model that has been trained for image overlay tasks, allowing you to seamlessly blend and place elements into existing images.
Table of Contents
Model Details
Model Description: This model is a LoRA fine-tune of black-forest-labs/FLUX.1-Kontext-dev specifically designed for image overlay workflows, enabling natural integration of new elements into existing scenes.
- Trained by: ilkerzgi and gokaygokay
- Model Type: LoRA for Image Overlay
- Language(s): English
- License: flux1-dev-non-commercial-license
- Parent Model: black-forest-labs/FLUX.1-Kontext-dev
- Resources for more information:
- Download the weights
- Try the model directly on fal.ai
Uses
Direct Use
This model is designed for image overlay tasks, allowing you to naturally integrate new objects, elements, or modifications into existing images. The model excels at understanding context and placement, creating seamless compositions.
The model works best when using the trigger phrase: "place it".
Recommended Settings
- LoRA Scale: 1.0 or 0.9 for optimal results
- Image Format: Square format images work best
- Overlay Area: Clear definition of where elements should be placed
- Context Understanding: Works well with natural scene composition
Training
Training Procedure
Training was performed using the FLUX Kontext Trainer on fal.ai.
The base model for training was black-forest-labs/FLUX.1-Kontext-dev, with specialized focus on image overlay scenarios and contextual element placement.
Usage Tips
- Use square format images for best results
- Set LoRA scale to 1.0 or 0.9 for optimal output quality
- Use the simple prompt "place it" as the trigger phrase
- Provide clear context about what you want to overlay and where
- The model understands spatial relationships and lighting conditions for natural integration
- Works well with both object placement and scene modifications
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Model tree for ilkerzgi/Overlay-Kontext-Dev-LoRA
Base model
black-forest-labs/FLUX.1-Kontext-dev