On the Origin of LLMs: An Evolutionary Tree and Graph for 15,821 Large
  Language Models
Sarah Gao Andrew Kean Gao
Since late 2022, Large Language Models (LLMs) have become very prominent with
LLMs like ChatGPT and Bard receiving millions of users. Hundreds of new LLMs
are announced each week, many of which are deposited to Hugging Face, a
repository of machine learning models and datasets. To date, nearly 16,000 Text
Generation models have been uploaded to the site. Given the huge influx of
LLMs, it is of interest to know which LLM backbones, settings, training
methods, and families are popular or trending. However, there is no
comprehensive index of LLMs available. We take advantage of the relatively
systematic nomenclature of Hugging Face LLMs to perform hierarchical clustering
and identify communities amongst LLMs using n-grams and term frequency-inverse
document frequency. Our methods successfully identify families of LLMs and
accurately cluster LLMs into meaningful subgroups. We present a public web
application to navigate and explore Constellation, our atlas of 15,821 LLMs.
Constellation rapidly generates a variety of visualizations, namely
dendrograms, graphs, word clouds, and scatter plots. Constellation is available
at the following link: https://constellation.sites.stanford.edu/.