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 for license plate object detection.

Model Details

Model Description

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.

• Developed by: Aritra Roy Gosthipaty and Sergio Paniego
• Finetuned from model: gemma-3-4b-pt

Model Sources

• Repository:
• HF Space:
• Collection:
• Dataset:

Uses

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.

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}}
}