Natural Language Analytics with GLLMs by Francisco S. Marcondes(.PDF)+
File Size: 18.0 MB
Natural Language Analytics with Generative Large-Language Models: A Practical Approach with Ollama and Open-Source LLMs by Francisco S. Marcondes, Adelino Gala, Renata Magalhães, Fernando Perez de Britto, Dalila Durães, Paulo Novais
Requirements: .ePUB, .PDF reader, 18.0 MB
Overview: This book explores the application of generative Large Language Models (LLMs) for extracting and analyzing data from natural language artefacts. Unlike traditional uses of LLMs, such as translation and summarization, this book focuses on utilizing these models to convert unstructured text into data that can be processed through the Data Science pipeline to generate actionable insights. The content is designed for professionals in diverse fields including cognitive science, linguistics, management, and information systems. It combines insights from both industry and academia to provide a comprehensive understanding of how LLMs can be effectively used for natural language analytics (NLA). The book details practical methodologies for implementing LLMs locally using open-source tools, ensuring data privacy and feasibility without the need for expensive infrastructure. Ollama is a tool designed to facilitate the deployment and operation of Large Language Models (LLMs) for various language analytics tasks. This chapter provides a quick-start guide for Ollama, detailing the steps to download and start using the tool on a local machine. This includes the navigation of Ollama’s model library and selection of models, the use of Ollama in a command shell environment, the setup of models through a modelfile, and its integration with Python (enabling developers to incorporate LLM functionality into Python-based projects). Ollama is presented as a solution that not only enhances the use of LLMs but also makes them more adaptable and easier to use in various contexts.
Genre: Non-Fiction > Tech & Devices
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