MS spam detection app, powered by Hugging Face's BERT model and deployed on Streamlit, offers users a simple yet powerful solution to identify spam messages in their SMS inbox. Through an intuitive user interface, users can input text messages for analysis. The app preprocesses the text, applies the BERT model trained on a SMS spam collection dataset, and classifies the message as spam or non-spam with high accuracy. Leveraging the deep understanding of natural language provided by BERT, the app ensures reliable detection of spam messages, helping users protect themselves from unwanted communication.
- Clone the repository
git clone https://github.com/surajkarki66/sms-spam-detection-BERT.git
- Create a Python virtual environment and activate the environment based on your machine(Linux, MacOS, and Windows)
- Install the requirements
pip install -r requirements.txt
- Run the following command
streamlit run app.py
You can now view your Streamlit app in your browser.
Happy Coding!