Text Summarizer This project includes extractive and abstractive text summarization models. The extractive model uses the CN/Daily Mail dataset, while the abstractive model uses the SAMSum dataset. It features a user-friendly interface and is fully deployed for easy access.

DarkGPT Chat Explorer is an interactive web application that allows users to engage in conversations with various GPT (Generative Pre-trained Transformer) models in real-time. This repository contains the source code for the application.

A collection of encoder-decoder transformers model fine tuned for abstractive text summarization using Liputan 6 news article dataset.

This repository houses a script that can download PDFs from a specified URL, convert them to text, and perform text analysis. This analysis includes identifying the language, eliminating stopwords, and counting word and phrase frequency. It's worth noting that the script is capable of analyzing texts in multiple languages.

1 line for thousands of State of The Art NLP models in hundreds of languages The fastest and most accurate way to solve text problems.

This project provides a web interface for uploading PDFs or entering text to generate a summarized output using the BiDirectional Auto Regressive Transformer (BART) model. The project is built using Flask for the backend and HTML, CSS, and JavaScript for the frontend

A Chatbot - to answer user queries based on the data stored in collaboration tools such as Confluence, Jira, BitBucket

We unified some latent block models by proposing a flexible ELBM that is extended to SELBM to address the sparse problem by revealing a diagonal structure from sparse datasets. This leads to obtain more homogeneous co-clusters and therefore produce useful, ready-to-use and easy-to-interpret results.

Experience the power of Clarifai’s AI platform with the python SDK. 🌟 Star to support our work!

Legal document analysis using BERT

IntelliLearn is a FastAPI-based application designed to process and transcribe audio and video files into text using the Whisper model. The application also supports processing PDF files to extract and summarize their content.

Artificial Intelligence Laboratory (6th semester) course's project.

NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, image generation, code generation, and much more...

This project demonstrates text summarization using the BART (Bidirectional and Auto-Regressive Transformers) model. BART is a transformer model trained as a denoising autoencoder and is effective for text generation tasks such as summarization.

NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, image generation, code generation, and much more...

If you want to learn these topics, i refer you to go through this notebook.

Welcome to InterviewX, your ultimate interview companion powered by AI. With features like scam detection, resume optimization, real-time posture analysis, time-saving text summarization, and ice breaker insights, InterviewX equips you with everything you need to ace your next interview with confidence and ease.

A web app that summarizes text or PDF content, detects sentiment, and creates word clouds from frequently used words.

Apply various Text Summarization techniques to simplify long and complex Terms of Service Agreements so you understand what you are agreeing to 😉