DeepMet is a chemical language model of the human metabolome. By representing chemical structures as short strings of text, DeepMet applies the same neural network architectures that are used to model the words in an English sentence to the atoms and bonds in a chemical structure. This paradigm allows DeepMet to learn the biosynthetic logic that is embedded within the structures of known human metabolites, and leverage this understanding to predict the existence of as-of-yet undiscovered metabolites.