README.md · xjlulu/question

metadata

title: Question Answering
emoji: ❓
colorFrom: green
colorTo: blue
sdk: gradio
sdk_version: 3.50.2
app_file: app.py
pinned: false
license: apache-2.0

Introduction

Welcome to the Question Answering project powered by Hugging Face Transformers and Gradio. This project provides a user-friendly interface for performing question-answering tasks, allowing users to input a question and a context paragraph, and the model will generate an answer.

Getting Started

Prerequisites

Before you run the application, ensure that you have the following prerequisites installed:

Python 3.6+: Make sure you have Python 3.6 or higher installed on your system.
Hugging Face Transformers: Install the Hugging Face Transformers library, which is used for powerful natural language processing tasks.
```
pip install transformers
```
Gradio: Install Gradio, a user-friendly Python library for creating web-based UIs for machine learning models.
```
pip install gradio
```
Datasets: Depending on your specific dataset requirements, make sure to install any additional datasets you might need for training or evaluation.
```
pip install datasets
```

Configuration Reference

For detailed configuration options and fine-tuning, please refer to the Hugging Face Spaces Config Reference.

Usage

Follow these steps to get started with the Question Answering project:

Clone this repository to your local machine.

# Make sure you have git-lfs installed (https://git-lfs.com)
git lfs install
git clone https://huggingface.co./spaces/xjlulu/question_answering
cd question_answering

# if you want to clone without large files – just their pointers
# prepend your git clone with the following env var:
GIT_LFS_SKIP_SMUDGE=1

Install the necessary dependencies as mentioned in the "Prerequisites" section.
Prepare your data if you're using a custom dataset. Ensure that your dataset is in the right format for your model.
Run the application:
```
python app.py
```
You can customize app.py to modify the appearance and behavior of the application as needed.
Open your web browser and navigate to http://localhost:7860 to access the Question Answering interface.

Acknowledgments

This project leverages the power of Hugging Face Transformers for state-of-the-art natural language understanding and Gradio for building an intuitive user interface.

License

This project is open-source and available under the Apache License 2.0.

Contact

For any questions, feedback, or support, please feel free to reach out at [email protected].