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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Base model
black-forest-labs/FLUX.1-Kontext-dev