PSSA: A non-transformer language model written from scratch in Rust

PSSA is a newly released language model implementation developed entirely from scratch using the Rust programming language. Unlike the vast majority of modern large language models that rely on the transformer architecture, PSSA explores alternative structural approaches to natural language processing. By leveraging Rust's memory safety and performance capabilities, the project aims to provide a high-performance, low-level implementation that avoids the heavy dependencies often associated with Python-based AI frameworks. The source code, now available on GitHub, serves as a technical demonstration for developers interested in the mechanics of language modeling outside the standard transformer paradigm. This project highlights a growing trend in the developer community to rebuild core AI components in systems languages to achieve better efficiency and control over computational resources. It offers a unique perspective for researchers and engineers looking to experiment with custom model architectures and low-level systems programming.