Milan Maksimovic developed comprehensive Vision Transformer testing coverage for the tenstorrent/tt-xla repository, focusing on JAX-based machine learning workflows. He designed and implemented a dedicated tester class in Python to validate Vision Transformer configurations across various patch sizes and resolutions, emphasizing inference-mode reliability. His approach established a robust automated testing foundation, reducing the risk of regressions and enabling safer, faster iteration toward future training support. By integrating test harness design and commit-based traceability, Milan’s work improved the reliability of ViT model implementations within tt-xla. This contribution demonstrated depth in JAX, automated testing, and transformer architectures over the course of the month.