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--- |
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dataset_info: |
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features: |
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- name: id |
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dtype: string |
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- name: ctx |
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dtype: string |
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- name: target |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 748604106 |
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num_examples: 1479018 |
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download_size: 407484559 |
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dataset_size: 748604106 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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--- |
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This is a collection of ~1.5M chess puzzles from the [Lichess database](https://database.lichess.org/#puzzles) of ~3.9M puzzles (as of 2024-05-09). |
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The set of puzzles from ["Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks"](https://github.com/aks2203/easy-to-hard-data/tree/main) is included, with the exception of 26,079 puzzles that are no longer in the Lichess database (on the assumption that they might have been removed for a good reason). |
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For each puzzle, `ctx` is a SAN transcript (with every half-move numbered) of an actual Lichess game, up to the puzzle position. Note that this includes the first move of the `Moves` column in the Lichess and Easy-to-Hard datasets. |
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`target` is the **best** next move, in SAN, with a leading space. This move (second move in `Moves` column) generally differs from the actual Lichess game, which may contain blunders. |
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Additional moves of the puzzle solution are not included. |
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This format matches that used in ["Weak-to-strong generalization"](https://openai.com/index/weak-to-strong-generalization/) and the set of puzzles is also intended to be as similar as possible (except for the 26k that Lichess removed). |
