Update README.md

README.md

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 Part of the [**Maia3**](https://huggingface.co/collections/UofTCSSLab/maia3) family of transformer models for human chess move prediction. This is the **5M-parameter variant**.
 
-For the full model card — architecture details, training recipe, full evaluation, and ablations — see the paper [*Chessformer: A Unified Architecture for Chess Modeling*](https://openreview.net/forum?id=2ltBRzEHyd) (ICLR 2026) and the [Maia3 collection](https://huggingface.co/collections/UofTCSSLab/maia3).
+For full details — architecture details, training recipe, full evaluation, and ablations — see our paper [*Chessformer: A Unified Architecture for Chess Modeling*](https://openreview.net/forum?id=2ltBRzEHyd) (ICLR 2026).
 
 ## Model summary
 
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 The Maia3 family reaches **57.1% move-matching accuracy** on human moves, significantly surpassing the previous state of the art with fewer than a quarter of the parameters. Per-size accuracy curves, scaling analysis, and skill-conditioned breakdowns are reported in the paper.
 
-## Limitations
-
-- Trained on Lichess games only; play styles on other platforms or over-the-board may differ.
-- Predicts moves conditioned on rating; does not produce engine-strength play. For maximum strength, use Chessformer integrated into Leela Chess Zero (see the paper).
-- Predictions reflect patterns in human play at each rating level, including systematic blunders and stylistic biases.
-
 ## Citation
 
 ```bibtex