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| title: README | |
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| *Which model would you rather have: the weaker student who crammed for the test, or the stronger student who walked in underprepared? Existing leaderboards mostly reward the former.* | |
| **LM-Harmony** is a multi-task leaderboard for **model potential**. Instead of judging deployment-ready performance out of the box, we use a **train-before-test** paradigm: every model is fine-tuned on the same benchmark-specific training set before evaluation. | |
| Across diverse tasks, LM-Harmony yields far more stable and consistent rankings than standard direct-evaluation leaderboards. If you care about which model will perform better after you fine-tune it on your own data, the ranking you see here is much more likely to generalize to your workload. | |