文件列表:

BERTModel.ipynb (53738, 2023-11-12)
app.py (2087, 2023-11-12)
fakeNewsDetector.ipynb (109451, 2023-11-12)
model.py (885, 2023-11-12)
requirements.txt (5276, 2023-11-12)
static/ (0, 2023-11-12)
static/css/ (0, 2023-11-12)
static/css/style.css (2501, 2023-11-12)
static/js/ (0, 2023-11-12)
static/js/script.js (505, 2023-11-12)
templates/ (0, 2023-11-12)
templates/index.html (1941, 2023-11-12)

# VerifAI: Text Classification with BERT Flask Application This Flask application allows you to perform text classification using a pre-trained BERT model. It can classify text as either "Fake" or "True" based on the content. ## Table of Contents - [Overview](https://github.com/poojappatel/FakeNewsDetector/blob/master/#overview) - [Purpose](https://github.com/poojappatel/FakeNewsDetector/blob/master/#purpose) - [Inspiration](https://github.com/poojappatel/FakeNewsDetector/blob/master/#inspiration) - [Prerequisites](https://github.com/poojappatel/FakeNewsDetector/blob/master/#prerequisites) - [Usage](https://github.com/poojappatel/FakeNewsDetector/blob/master/#usage) - [Acknowledgments](https://github.com/poojappatel/FakeNewsDetector/blob/master/#acknowledgments) - [Author](https://github.com/poojappatel/FakeNewsDetector/blob/master/#author) ## Overview This Flask application enables text classification using a pre-trained BERT model. It classifies text as either "Fake" or "True" based on its content. ## Inspiration In light of recent events, there is a high concentration of media and social media being used to spread information to people across the globe and to the people who are directly affected by the conflicts happening. Making sure that people have the right information at the right times, including where a hospital may be located or where a road might be broken to redirect them to the right place, is extremely critical. With the advent of new technology and people promoting false information, creating a tool to benefit and aid these people in distress is something that we all felt was truly something we could dedicate ourselves and this hackathon towards. ## Purpose The purpose of this project is to provide a user-friendly and accessible tool for text classification, particularly for distinguishing between fake and true news articles or texts. Text classification is a valuable task in various domains, including journalism, content moderation, and social media analysis. By using a pre-trained BERT model, this application aims to: - Assist users in quickly assessing the authenticity of textual content. - Serve as a practical example of deploying machine learning models for real-world applications. - Facilitate further research and development in natural language processing and text classification tasks. ## Prerequisites Before running this application, make sure you have the following dependencies installed: - Python 3.10.12 - Numpy - Pandas - Flask - PyTorch - Transformers (Hugging Face) - Pycaret - Other necessary libraries (refer to `requirements.txt`) You can install the required libraries using pip: pip install -r requirements.txt ## Acknowledgments: - This project uses the Hugging Face Transformers library for working with pre-trained BERT models. ## Authors: Emma Azzi, Ananya Shekhawat, Pooja Patel, Aymaan Shaikh

近期下载者：

相关文件：

评论：[我要评论] [举报此文件]

收藏者：