Detoxigram

Detoxigram is a tool designed to analyze and reduce toxicity in different contexts, combining the strengths of BERT classifiers and generative Language Models (LLMs) to promote healthier online interactions.

Table of Contents

• Overview
• Project Structure
• Installation
• Usage
• Contributing
• License

Overview

Inspired by literature (Zhixue et al., 2021; Ousidhoum et al., 2021; Fortuna et al., 2021), Detoxigram identifies and classifies toxic content using a five-level toxicity scale. It leverages BERT models for initial classification and generative LLMs for detailed analysis and detoxification suggestions.

Project Structure

• dataset: Contains datasets for training and evaluation.
• detoxigram_bot: The implementation of the bot for toxicity analysis.
• model_evaluation_scripts: Scripts for evaluating machine learning models.
• script-download-channels: Scripts to download data from various channels.
• requirements.txt: Python dependencies for the project.

Installation

1. Clone the repository:

   git clone https://github.com/LIA-DiTella/Detoxigram.git
   cd Detoxigram

2. Create a virtual environment and activate it:

   python3 -m venv venv
   source venv/bin/activate

3. Install dependencies:

   pip install -r requirements.txt

Contributing

1. Fork the repository.
2. Create a new branch (git checkout -b feature/YourFeature).
3. Commit your changes (git commit -am 'Add a new feature').
4. Push to the branch (git push origin feature/YourFeature).
5. Create a new Pull Request.