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: this https URL

利用 Hugging Face LLMs 的系统性命名法，通过使用 n-grams 和词频 - 逆文档频率进行层次聚类，我们成功地识别出一个个 LLMs 家族，并将其准确地聚类成有意义的子群。我们还提供了一个公共网络应用程序，用于浏览和探索我们的 LLMs 地图 Constellation。Constellation 可以快速生成各种可视化，包括树状图、图表、词云和散点图。Constellation 可在以下链接中访问：this https URL。