TALLM: A framework for Text Analysis using Large Language Models

Artificial intelligence systems known as Large Language Models have proven to process and interpret human language. With these models attaining state-of-the-art outcomes in various tasks, such as language translation, text summarization, sentiment analysis, and text production, it is important to understand how the models get their judgments to maintain confidence and dependability. This paper presents the design and the development of TALLM i.e., a framework for text analysis using large language models. TALLM seamlessly allows the integration of pre-trained models sourced from repositories and the use of an appropriate set of curated datasets. This workflow permits achieving the targeted level of model performance and guarantees its reliability and traceability, thereby setting applicable precedents for future development.