Dataset descriptions:
- lichess: 7GB of 16 million games from lichess's database. No elo filtering performed.
- Lichess_gt_18k: ~4GB of games from lichess. Per OpenAI's weak to strong generalization paper, filtered to only include games where white is > 1800 ELO.
- Stockfish: 4.5GB of games generated by White playing as Stockfish ELO 3200 against a range of Stockfish ELO 1300-3200 as black.
- Lichess-stockfish mix: a 50 / 50 mix of > 1800 ELO lichess games and stockfish generated games
- Lichess results: lichess, but we include the result before every game. Hopefully, we can then prompt the model with ";1-0#1.", indicating to the model that it's supposed to win this game.
Blocks dataset include only one column and are used for training. Every cell is a batch I created that is 1024 characters long. Datasets without "blocks" in the name contain metadata like player skill, result, etc.