Learning universal representations (embeddings) of single cell RNA-sequencing data is critical for drawing scientific conclusions from diverse omics datasets. Here we propose a foundation model that produces universal cell embeddings (UCE), which capture true biological variation despite experimental noise. This repository contains files needed to run the UCE model.