Flux Product Ad Backdrop

🚀 Flux-Product-Ad-Backdrop

This model is designed for generating product advertisement backdrops. It can create various vivid and realistic product - related images.

🚀 Quick Start

Prerequisites

Make sure you have the necessary libraries installed. You can set up the environment as follows:

import torch
from pipelines import DiffusionPipeline

base_model = "black-forest-labs/FLUX.1-dev"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)

lora_repo = "prithivMLmods/Flux-Product-Ad-Backdrop"
trigger_word = "Product Ad"  
pipe.load_lora_weights(lora_repo)

device = torch.device("cuda")
pipe.to(device)

Trigger Words

You should use Product Ad to trigger the image generation.

Download Model

Weights for this model are available in Safetensors format. Download them in the Files & versions tab.

✨ Features

• Text - to - Image Generation: Generate high - quality product advertisement images based on text descriptions.
• Multiple Product Support: Can generate images for different types of products, such as fried chicken wings, electric razors, and vegan snacks.

📦 Installation

The installation mainly involves setting up the Python environment and loading the model. The code for setting up is as follows:

import torch
from pipelines import DiffusionPipeline

base_model = "black-forest-labs/FLUX.1-dev"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)

lora_repo = "prithivMLmods/Flux-Product-Ad-Backdrop"
trigger_word = "Product Ad"  
pipe.load_lora_weights(lora_repo)

device = torch.device("cuda")
pipe.to(device)

💻 Usage Examples

Basic Usage

You can use the following steps to generate product advertisement images:

import torch
from pipelines import DiffusionPipeline

base_model = "black-forest-labs/FLUX.1-dev"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)

lora_repo = "prithivMLmods/Flux-Product-Ad-Backdrop"
trigger_word = "Product Ad"  
pipe.load_lora_weights(lora_repo)

device = torch.device("cuda")
pipe.to(device)

# Assume you have a text prompt
text_prompt = "Product Ad, Captured at eye - level, a close - up shot captures a pile of fried chicken wings in a white paper cup..."
image = pipe(text_prompt).images[0]
image.show()

📚 Documentation

Model Description

prithivMLmods/Flux-Product-Ad-Backdrop

Image Processing Parameters

Labeling: florence2 - en(natural language & English) Total Images Used for Training: 19

Best Dimensions

• 768 x 1024 (Best)
• 1024 x 1024 (Default)

📄 License

This model is licensed under the creativeml - openrail - m license.

⚠️ Important Note

The model is still in the training phase. This is not the final version and may contain artifacts and perform poorly in some cases.