Identifying invariants is an important program analysis task with applications towards program understanding, vulnerability analysis, and formal verification. Existing tools for identifying invariants rely on dynamic analysis, requiring traces collected from multiple executions in order to produce reliable invariants. We study the application of large language models to invariant prediction, finding that models trained on source code and fine-tuned on invariants can perform invariant prediction…