Chess Transformer — 35M Parameters, Trained from Scratch
Transformer model trained to play chess using reinforcement learning self-play,
built entirely from first principles in PyTorch.
Architecture: Custom transformer with chess-specific position encoding
Parameters: 35M
Training: RL self-play with custom reward shaping
Fine-tune: Separate LoRA/PEFT fine-tune of Qwen-0.5B also available
Built as a personal project to learn transformer architecture and RL from the ground up —
not a wrapper, not a fine-tune of an existing chess model.
