Show HN: I reimplemented TRM – trains on Sudoku 6×6 in minutes on an A10 (github.com)

A developer has reimplemented the TRM (Transformer-based Reinforcement Model) for training on Sudoku puzzles, specifically the 6x6 variant, achieving training times of just minutes on an A10 GPU. This project not only enables users to reproduce official results but also pushes the boundaries of the model's capabilities. By providing a streamlined setup process with automated installation scripts, users can quickly generate Sudoku datasets and execute training runs that reach around 87% accuracy, comparable to existing benchmarks. This development is significant for the AI/ML community as it exemplifies the growing accessibility of advanced AI training techniques while showcasing the efficiency of the TRM model. The easy-to-follow commands allow even less experienced practitioners to explore and build upon the model, potentially leading to innovations in reinforcement learning applications. Future plans to implement self-play through TRM further highlight its versatility, suggesting opportunities for enhanced model training and evaluation in various gaming and problem-solving contexts.