Textual Compression Using Lamini-LM

Abstract

In the age of digital overload, the ability to efficiently summarize large amount of text has become a critical capability. This project focuses on the development of a document summarization system that uses the power of the LaMini-LM model, a member of the Langchain family of large language models (LLMs). By using the natural language processing (NLP) techniques through the Langchain LLM technology it creates a robust and practical solution for automatically generating concise and informative summaries of text documents. The methodological approach of this project combines the strengths of NLP techniques, including the transformer architecture, the T5 model, and specialized components such as the T5 tokenizer and the Pipeline API. This strategic integration of technologies allows to create a comprehensive and efficient document summarization system that can effectively process and summarize a diverse range of text documents. The successful development and implementation of the document summarization system using the LaMini-LM model represents a significant advancement in the field of natural language processing.