Large language models (LLMs) are artificial intelligence (AI) systems that use machine learning (ML) algorithms to process vast amounts of natural language text data. They have become increasingly popular due to their impressive natural language processing (NLP) capabilities.
Large pretrained language models are capable of extracting generalizations from vast amounts of text data, which can be utilized for a myriad of downstream applications such as text classification, text summarization, text generation, named entity recognition (NER), text sentiment analysis, and question-answering (Q&A). Additionally, many large language models are multilingual, making them even more versatile in utilizing text datasets across many different languages.
This whitepaper will discuss one approach to developing and deploying LLMs on a single Dell PowerEdge server and the impressive results delivered over a traditional HPC architecture approach.