This page details the topic namers available in Turftopic, allowing automated assignment of human-readable names to topics. It covers Large Language Models (local and OpenAI), N-gram patterns, and provides API references for the `TopicNamer`, `LLMTopicNamer`, `OpenAITopicNamer`, and `NgramTopicNamer` classes.
Python tutorial for reproducible labeling of cutting-edge topic models with GPT4-o-mini. The article details training a FASTopic model and labeling its results using GPT-4.0 mini, emphasizing reproducibility and control over the labeling process.
we embed all of our documents and convert them to numerical representations. Second, we find out which documents are most similar to one another. We assume that documents that are highly similar will have the same keywords, so there would be no need to extract keywords for all documents. Third, we only extract keywords from 1 document in each cluster and assign the keywords to all documents in the same cluster.
Comprehensive guide to ChatGPT API for newbies