README.md

---
license: other
library_name: diffusers
tags:
- lora
- flux
- kontext
- object-placement
base_model: black-forest-labs/FLUX.1-Kontext-dev
---

# FLUX Kontext Object Placement LoRA

This is a LoRA (Low-Rank Adaptation) model trained on FLUX.1-Kontext for object placement tasks.

## Usage

```python
from diffusers import FluxPipeline
import torch

# Load the base model
pipe = FluxPipeline.from_pretrained(
    "black-forest-labs/FLUX.1-Kontext-dev",
    torch_dtype=torch.bfloat16
)

# Load the LoRA
pipe.load_lora_weights("fediry/flux-kontext-object-placement-lora")

# Generate images with object placement
prompt = "place it --ctrl_img path/to/your/control/image.jpg"
image = pipe(prompt).images[0]
```

## Training Details

- **Base Model**: black-forest-labs/FLUX.1-Kontext-dev
- **Training Steps**: 3000
- **Batch Size**: 1
- **Learning Rate**: 1e-4
- **Architecture**: LoRA with rank 128
- **Trigger Word**: "place"

## Model Description

This LoRA was trained to help with object placement tasks using the FLUX Kontext architecture. It can be used to place objects in images by providing a control image and using the trigger word "place".