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--- |
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license: mit |
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--- |
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Model trained on chess "narratives" created from PGN notation from a large set of games downloaded from The Week in Chess (https://theweekinchess.com/). A script was run to convert the PGN notation to english text, and the model was finetuned on that. The approach is described in the paper [_Navigating Human Language Models with Synthetic Agents_](https://arxiv.org/abs/2008.04162). |
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# Useful Prompts: |
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* "The game begins" |
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* "In move X" // X can be a number between 1 and approximately 100 |
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* "White/Black moves X from Y" // X is the piece (pawn, bishop, knight, rook, queen, king) and Y is the square (e.g. e2) |
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* "The game begins as white uses the X opening" // X is a known opening move such as Sicilian |
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* "White moves X from" // X is the piece (pawn, bishop, knight, rook, queen, king) |
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* "Black moves X from" // X is the piece (pawn, bishop, knight, rook, queen, king) |
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# Citation: |
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``` |
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@misc{feldman2020navigating, |
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title={Navigating Human Language Models with Synthetic Agents}, |
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author={Philip Feldman and Antonio Bucchiarone}, |
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year={2020}, |
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eprint={2008.04162}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.AI} |
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} |
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``` |
