ed-bert

Emotional Detection using Bidirectional Encoder Representations from Transformers (BERT).

Features 🚀

Using ED-BERT, you can:

• Detect emotion from text.
• Report incorrect prediction and save the data on database.
• Train your own model with additional data from database.

Prerequisites 📋

• Python 3.10 or higher
• Streamlit 1.25.0 or higher
• MySQL 8.0.32 or higher
• Docker 24.0.4 or higher (optional)
• docker-compose 1.29.2 or higher (optional)

Installation 🛠

Manual Installation

• Clone the repository

git clone https://github.com/putuwaw/ed-bert.git

• Create virtual environment and activate it

python -m venv venv
source venv/bin/activate

• Install the dependencies

pip install -r requirements.txt

• Set up database using SQL dump in init.sql file.

• Run the app

streamlit run Home.py

Important

This repository contain .h5 file which is the model of ED-BERT. Please consider to read about Git Large File Storage.

Docker Installation

• Clone the repository

git clone https://github.com/putuwaw/ed-bert.git

• Run the app

docker-compose up

License 📝

This project is licensed under the MIT License. See the LICENSE file for details.