FLUX Kontext Object Placement LoRA

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

Usage

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".

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