/Table-Question-Answering-using-HuggingFace

Primary LanguagePython

Table Question Answering with Streamlit

A Streamlit application that uses the Hugging Face Transformers library to perform table-based question answering. Users can upload a CSV file, ask questions about the data in the table, and get answers using the TAPAS model.

Features

  • Upload a CSV file.
  • Ask questions about the table data.
  • Get answers using the TAPAS model.

Usage

  1. Start the Streamlit app.

  2. Upload a CSV file: Click the "Upload a CSV file" button and select a CSV file from your local machine. The app will read and load the data from the CSV file into a DataFrame.

  3. View the uploaded data: The uploaded CSV data is displayed in a table format, allowing you to review its contents.

  4. Enter your question: In the "Enter your question" text input field, type a question related to the data in the uploaded table.

  5. Ask the question: Click the "Ask" button to submit your question.

  6. Get the answer: The TAPAS model will process the table and your question to provide an answer. The answer is displayed under the "Answer" subheader.

Installation

To run the app locally, follow these steps:

  1. Clone the repository:

    git clone https://github.com/abdullawagih1/Table-Question-Answering-using-HuggingFace.git