Automated Text Summarizer

A tool for condensing extensive amounts of text.

Bart Large CNN Model

BART, a transformer model, combines a bidirectional encoder (similar to BERT) and an autoregressive decoder (similar to GPT). It's pre-trained by corrupting text using a noise function and learning to reconstruct it. BART excels in tasks like text generation (e.g., summarization, translation) and performs effectively in comprehension tasks (e.g., text classification, question answering). This specific version has been fine-tuned on the CNN Daily Mail dataset, optimizing it for generating summaries from text.

Demo

Environment Variables

To run this project, you will need to add the following environment variables to your .env file

• Hugging Face API_KEY

Run Locally

Clone the project

git clone https://github.com/lohithgsk/automated-text-summarizer.git

Go to the project directory

cd my-project

Install dependencies

  npm install

Start the server

  node index.js

Feedback

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