Gemma 3 4b Pt Object Detection

🚀 Gemma 3 4B Fine-Tuned for Object Detection

This model is a fine - tuned version of Gemma 3 4B, specifically designed for license plate object detection, offering a practical solution for related tasks.

🚀 Quick Start

This model is a fine-tuned version of Gemma 3 4B for license plate object detection.

Detected License Plates (Sample 1)	Detected License Plates (Sample 2)

📚 Documentation

✨ Features

This model aims to prove that VLMs NOT previously trained for object detection and without previous knowledge of location tokens (<locXXXX>) can still be fine tuned for object detection out of the box. This is an experimental model.

📦 Installation

Follow these steps to configure, train, and run predictions (using the code repository):

1. Configuration (config.py): All major parameters are centralized here. Before running any script, review and adjust these settings as needed.
2. Training (train.py): This script handles the fine-tuning process.
3. Running inference (infer.py): Run this to visualize object detection.

🔧 Technical Details

• Developed by: Aritra Roy Gosthipaty and Sergio Paniego
• Finetuned from model: gemma-3-4b-pt
• Model Sources
  • Repository:
  • HF Space:
  • Collection:
  • Dataset:

📄 License

This model is released under the apache-2.0 license.

📚 Citation

If you use our work, please cite us:

@misc{gosthipaty_gemma3_object_detection_2025,
  author = {Aritra Roy Gosthipaty and Sergio Paniego},
  title = {Fine-tuning Gemma 3 for Object Detection},
  year = {2025},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/ariG23498/gemma3-object-detection.git}}
}