Question Answering System using Gradio's Lower-Level API

Overview

This project implements a question answering system using Gradio's lower-level API. The system features two input fields: one for the context and another for the user's question. The system then outputs the model's response.

Dataset

The project uses the deepset/roberta-base-squad2 model for question answering.

Methodology

The methodology for implementing the question answering system includes:

• Installing the required libraries: Gradio and transformers.
• Loading the question-answering pipeline using the deepset/roberta-base-squad2 model.
• Defining the interface components: Textbox for context, Textbox for question, and Label for displaying the model's response.
• Creating the Gradio interface with the defined components and launching it.

Setup

To run the question answering system locally, follow these steps:

1. Install the required libraries:

   pip install gradio transformers
   

2. Import the necessary libraries and load the question-answering pipeline.

Conclusion

The question answering system using Gradio's lower-level API provides a simple and user-friendly interface for interacting with the deepset/roberta-base-squad2 model. This system can be further enhanced with additional features and improvements.

Gradio Website Screenshot

This screenshot demonstrates the functionality of the question answering system on the Gradio website, showcasing how the system processes questions and provides answers.