A NLP based summarizer which can summarize news article.
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Updated
Feb 19, 2024 - Jupyter Notebook
A NLP based summarizer which can summarize news article.
A django application that allows you to summarize the content of a press article found by a user. It uses the T5 model for summarization, the LDA algorithm for topic modeling and Selenium to scrape the content of the linked article.
Multilingual Text Summarizer is a web application that summarizes text, PDFs, and images in multiple languages using a T5 transformer model. The application is built with Streamlit, EasyOCR, and Hugging Face Transformers.
An agent-based, peer-to-peer, chat/social messaging application, intended for users that speak differing native languages. Built atop Fetch.ai's uAgents framework and t5-base integration.
This repository consists of the implementation of the paper "Automatic Ellipsis Reconstruction in Coordinated German Sentences based on Text-To-Text Transfer Transformers" which is accepted at 27th International Conference on Text, Speech and Dialogue.
This repository contains the code and outputs for the CS505: Natual Language Processing course project. The objective of this work is to explore the performance of different machine learning models in generating commit messages from changes in code.
Thesis scope: Train and Develop a Table-to-Text Transformer-based model for contextual summarization of tabular data. To achieve this T5-small , T5-base, Bart-base and Llama2 7B chat were finetuned on ToTTo and QTSumm. Regarding ToTTo, the models outperformed the benchmark.
A news headline generator finetuned on T5-base.
A resume matching tool. Finds the top 5 best matching resumes for each job description provided.
Finetuned FLAN-T5 to translate English to Hawaiian Pidgin
An agent-based reader view plugin for summarizing an article or web page, using Fetch.ai's uAgents framework and the t5-base integration.
Fine-tuning the T5-base model using parts of the CNN/DailyMail dataset using PyTorch Lightning.
T5-base model is finetunned for abstract2title
German-to-English fine-tuned T5 base model with dependency-parsing enhancement.
finetuning t5-base model for detoxifying texts.
Fine-Tuning LLM for summarization in Portuguese (T5)
This project summarizes large text from any article to a smaller version without any loss in context. It uses the T5 Base transformer model.
Repository containing the project for the course on Business and Project Management at the University of Pisa (A.Y. 2022/2023) realized by Fabiano Pilia, Emanuele Tinghi and Matteo Dal Zotto.
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