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Pawel Sarkowicz
2026-06-10 10:38:55 -04:00
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README.md
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**ClimbingBoardGPT uses AI to generate new climbing routes and predict their difficulty — for Tension Board 2 and Kilter Board.**
The route generator follows the small causal-transformer recipe from Andrej Karpathy's [nanoGPT](https://github.com/karpathy/nanoGPT): train a model to predict the next token, then sample from it autoregressively. The twist here is that the "language" is made of board, angle, grade, and hold-role tokens instead of text.
You give it a board, a wall angle, and a target grade. It gives you a route. You can also paste in a route you already know, and it will guess the grade.
**[Try it live →](https://cbgpt.pawelsarkowicz.xyz)**
**[Try it live](https://cbgpt.pawelsarkowicz.xyz)**
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- [Tension-Board-2-Analysis](https://github.com/psark007/Tension-Board-2-Analysis)
- [Kilter-Board-Analysis](https://github.com/psark007/Kilter-Board-Analysis)
The route generator architecture is inspired by Andrej Karpathy's [nanoGPT](https://github.com/karpathy/nanoGPT).
Acknowledgement: the route generator draws on ideas from Andrej Karpathy's [nanoGPT](https://github.com/karpathy/nanoGPT).
Board layouts, hold metadata, and route data are from the [Tension Board 2](https://tensionclimbing.com/products/tension-board-2) and [Kilter Board](https://settercloset.com/collections/kilter-board) apps, loaded via [`BoardLib`](https://github.com/lemeryfertitta/BoardLib). This project is unaffiliated with Tension Climbing or Kilter.