---
license: mit
---
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).

# Useful Prompts:
* "The game begins"
* "In move X" // X can be a number between 1 and approximately 100
* "White/Black moves X from Y" // X is the piece (pawn, bishop, knight, rook, queen, king) and Y is the square (e.g. e2)
* "The game begins as white uses the X opening" // X is a known opening move such as Sicilian
* "White moves X from" // X is the piece (pawn, bishop, knight, rook, queen, king)
* "Black moves X from" // X is the piece (pawn, bishop, knight, rook, queen, king)

# Citation:
```
@misc{feldman2020navigating,
      title={Navigating Human Language Models with Synthetic Agents}, 
      author={Philip Feldman and Antonio Bucchiarone},
      year={2020},
      eprint={2008.04162},
      archivePrefix={arXiv},
      primaryClass={cs.AI}
}
```