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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.
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.
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.
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.
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.