How to use from the
Use from the
Diffusers library
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/metallic-objects-kontext-dev-lora")

prompt = "Make it metallic with a black background and a 3D perspective"
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]

Metallic Objects Kontext Dev LoRA

This is a LoRA (Low-Rank Adaptation) model that has been trained to transform input images into a metallic style, featuring a black background and a 3D perspective.

Table of Contents

Model Details

Model Description: This model is a LoRA fine-tune of black-forest-labs/FLUX.1-Kontext-dev. It's designed to be used in an image-to-image pipeline to apply a specific artistic style. When prompted with "Make it metallic with a black background and a 3D perspective", it converts regular images into 3D-looking metallic objects on a dark background.

Uses

Direct Use

This model is intended to be used for artistic image generation. You can use it to apply a "metallic object" style to your own images. The model works best when using the trigger phrase: "Make it metallic with a black background and a 3D perspective".

Training

Training Data

I trained the model on a custom dataset of 20 paired (before and after) images of various objects to learn the "metallic" style transformation.

Training Procedure

I performed the training using the FLUX Kontext Trainer on fal.ai. The base model for training was black-forest-labs/FLUX.1-Kontext-dev.

Hyperparameters:

  • Learning Rate: 0.0001
  • Steps: 1300
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