Advanced Extractive Text Summarization #101
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
|
👋 @one-Alive 👋 We're delighted to have your pull request! Please take a moment to check our contributing guidelines and ensure you've filled out the PR template for a smooth process. We will review it soon. |
king04aman
approved these changes
Nov 21, 2024
|
👋 @king04aman 👋 🎉 You've just merged your pull request! We're excited to have you in our community. Keep up the fantastic contributions to the project! |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Welcome to the Advanced Extractive Text Summarization Model! This project uses Natural Language Processing (NLP) techniques to automatically distill essential points from lengthy content, making it an invaluable tool for handling reports, research papers, news articles, and more.
🚀 Project Overview
This model leverages NLP to:
Why It Matters
In today’s information-dense world, quickly understanding critical points from long documents is essential. This model saves time and boosts productivity by providing concise summaries while preserving core insights.