di37/multiclass-news-classification-using-llms
This repository contains a project that focuses on evaluating the performance of different Language Models (LLMs) for multi-class news classification. The project aims to assess how well LLMs can classify news articles into five distinct categories: business, politics, sports, technology, and entertainment.
This project helps anyone who needs to automatically sort large volumes of news articles. By taking raw news article text, it categorizes them into topics like business, politics, sports, technology, and entertainment. This is most useful for media analysts, content curators, or market researchers.
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Use this if you need to quickly and accurately sort news articles into predefined categories, especially when comparing the performance and resource usage of different large language models for this task.
Not ideal if your categorization needs are highly specialized beyond general news topics, or if you need to classify extremely short snippets of text where context is minimal.
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May 25, 2024
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