This article provides a tutorial on integrating locally hosted open-source large language models such as Mistral, Gemma, and Llama 3 for language tasks like text classification. It demonstrates how to achieve this for free using Ollama and the Scikit-LLM Python library.
The content examines how generative AI models, specifically LLMs, have increasingly replaced traditional machine learning methods for tasks like text classification. It discusses the scenarios in which an LLM should be preferred.
This tutorial demonstrates practical Natural Language Processing tasks like text classification and question answering directly in the browser using the Transformers.js library's pipeline() API.
Zero-shot text classification allows you to label text without first training a classifier on your own task-specific dataset. It offers an efficient approach to categorizing textual information.
This project tackles the limitation of traditional AI models with unseen data, proposing a solution for college ERP systems. It uses Zero-Shot Learning to classify dynamic and unpredictable text, while also incorporating memory of past interactions to improve performance.