Vedika-image-edit_gguf

The Lightweight Champion of Image Editing

Powered by Aura Gen 2.0 Creative

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📖 Overview

Vedika-image-edit_gguf is a highly efficient, lightweight, and performant image editing model derived from the robust FLUX.2-klein-4B architecture. This model has been specifically quantized for CPU inference, making it the perfect choice for running high-quality image generation and editing workflows on resource-constrained environments like Hugging Face Spaces (Free Tier).

This model is a proud creation of Vedika AI, designed to deliver professional-grade results without the massive hardware requirements typically associated with generative AI.

🚀 Why Choose Vedika-image-edit_gguf?

Unlike standard large-scale models, this version is precision-tuned to maintain visual fidelity while drastically reducing memory consumption.

• Extreme Efficiency: Optimized using Q4_K_M quantization, ensuring it fits comfortably within the 16GB RAM limit of free-tier environments.
• Flow Matching Excellence: Built on the latest Flow Matching technology to ensure realistic, artifact-free image transformations.
• Production Ready: Ideal for rapid prototyping, personal projects, and automated content creation.
• Aura Gen 2.0 Powered: Built upon the latest creative standards, ensuring high-quality aesthetics for every generation.

🛠 Technical Specifications

Attribute	Detail
Model Base	FLUX.2-klein-4B
Quantization	Q4_K_M (GGUF)
Framework	PyTorch / Diffusers
Inference Requirement	~4-6 GB RAM (optimized)
Precision	4-bit
Category	Image-to-Image / Inpainting

📦 Installation & Quick Start

To get started with Vedika-image-edit_gguf, ensure you have the necessary libraries installed.

1. Requirements

pip install torch diffusers transformers accelerate bitsandbytes