An AI-powered system for extracting and summarizing key legal information from complex legal documents using advanced Natural Language Processing (NLP) techniques. This project utilizes SpaCy for preprocessing and entity extraction, and Sumy for text summarization, to generate concise summaries of lengthy legal texts.

This project is a text summarization system that leverages word sense disambiguation and pre-trained T5 models. It identifies and summarizes repeating words with different meanings, using spaCy for NLP and an n-gram model for candidate word selection. It compares summaries using Rouge scores and outputs the best one. Written in Python with Flask.

A beginner‑friendly project demonstrating text summarization using the spaCy NLP library.

NLP-Text-Summarizer-Spacy is a Streamlit app that uses SpaCy for text summarization. It enables users to input text, adjust the summary length, and generate concise summaries by identifying the most important sentences based on word frequency.

we implement nlp tasks like Text summarization , named entity Recognition and other tasks using spaCy

This model/app aims to summarizes huge text article and documnets. It utilizes spacy and nltk. It is built using Flask, NLP, and HTML/CSS. liabraries for that.

An intelligent text summarization tool that supports both extractive and abstractive approaches. It combines traditional NLP (TF-IDF, Logistic Regression, spaCy) with modern deep learning (Hugging Face Transformers) to generate concise and meaningful summaries from long documents.

"Text Summarization Using NLP" is a Python repo employing spaCy for concise text summaries. Explore extractive techniques, follow a simple setup, and dive into effective NLP-based summarization.

Comprehensive NLP toolkit with text classification, named entity recognition, sentiment analysis, and text summarization. Built with transformers, spaCy, and custom models.

Developed a web application using Streamlit and integrated NLP models (T5 Transformer and spaCy) for text summarization and enabling users to summarize online articles with improved readability and comprehension.

A NLP app built with streamlit framework using SpaCy for Named Entity Extraction(NER) and tokenization, TextBlob for sentiment analysis and Gensim and Sumy for text summarization

An intelligent text summarization tool that supports both extractive and abstractive approaches. It combines traditional NLP (TF-IDF, Logistic Regression, spaCy) with modern deep learning (Hugging Face Transformers) to generate concise and meaningful summaries from long documents.

The Python code in this notebook can be used to implement a baseline Chatbot aimed at reproducing philosophical conversation. It consists of various NLP components: a topic extractor (SpaCy, nltk) via NMF algorithm followed by a summarization pipeline (Transformer). Then a GPT2 model for text generation fine-tuned on questions extracted from texts by F. Nietzsche.

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NLP-Text-Summarizer-Spacy is a Streamlit app that uses SpaCy for text summarization. It enables users to input text, adjust the summary length, and generate concise summaries by identifying the most important sentences based on word frequency.

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A text summarizer using NLP & spaCy library

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Text summarization using SpaCy NLP pipeline.

Text Summarizer (NLP) using pretrained model named Spacy

This repository contains a text summarizer using Spacy library of NLP.

NLP slovak statistical models in spacy framework mainly for text summarization

Using "Spacy the free open source library for NLP creating text summarization

web-based Text Summarization tool built using Flask and Spacy NLP library

Automatic text summarization from PDFs and YouTube videos using spaCy and advanced NLP techniques.

"Text Summarizer" is a Flask-based web app using Spacy for NLP. It condenses lengthy text into concise summaries. Spacy's NLP capabilities extract key info, presenting users with summarized content, making information consumption efficient and accessible.

This simple portuguese text summarizer was built using Spacy in order to enhance my skills regarding this NLP application.

simple and effective text summarization script using NLP libraries such as NLTK,SpaCY,or transformers

Using Spacy in NLP to develop a tool to summarize text from a given passage

News articles text processing & NER using traditional NLP (nltk, spacy) & abstractive summarization using LLM (Azure OpenAI)