A 200,000-position supervised fine-tuning dataset for training language models
to play chess by predicting the next move from a PGN prefix. Derived from
strong-player Lichess games, stripped to a minimal input/output format.
Task: given a partial game in PGN notation, predict the next move in
Standard Algebraic Notation (SAN).
Source: Lichess/standard-chess-games
(all games downloadable from lichess.org; CC0).
Strength filter: both… See the full description on the dataset page:
https://huggingface.co/datasets/cetusian/chess-sft-lichess-2200.
