Pawitt/zero-evaluator

Zero Evaluator High-Variance Chess Positions This dataset collects 3,809,201 chess positions from three distinct styles of play — engine tournament games, neural-network self-play, and strong human online games. Positions are stored as normalized six-field FEN records for immediate board reconstruction without replaying a game, and every collection balances opening, middlegame, and endgame coverage. Two of the collections additionally carry static, depth-zero win/draw/loss… See the full description on the dataset page: https://huggingface.co/datasets/Pawitt/zero-evaluator.