Topic Modelling With Quantized LLaMA 3 & BERTopic
Today we’re diving into topic modeling using a powerful algorithm called BERTopic , and Llama-3, the next generation of Llama, is now available for broad use. It features pre-trained and instruction-fine-tuned language models with 8B and 70B parameters, supporting various use cases. We will be using topic modeling for topic extraction using BERTopic and the quantized gguf version of Llama-3 –8b-instruct from the dataset, and visualizing it for further understanding. What is Topic Modeling? Businesses need help with vast amounts of unstructured text daily, ranging from customer emails to online reviews. This abundance of textual data necessitates efficient organization and understanding, leading us to rely on topic modeling. Topic modeling is a statistical technique using unsupervised machine learning to uncover and showcase thematic structures within textual data. It’s crucial in various domains like information retrieval, text mining, modern search systems, and data visualization
