Update README.md

README.md

@@ -20,7 +20,7 @@ A Colab notebook is available in our [GitHub repository](https://github.com/MLI-
 ## Training Details
 
 - Models are pretrained on synthetic data generated by sampling ground-truth sequences of length L uniformly at random over the quaternary alphabet, and independently introducing insertions, deletions, and substitutions at each position.
-- Error probabilities for insertions, deletions, and substitutions are drawn uniformly from the interval [0.01, 0.1], and cluster sizes are sampled uniformly from \([2, 10]\).
+- Error probabilities for insertions, deletions, and substitutions are drawn uniformly from the interval [0.01, 0.1], and cluster sizes are sampled uniformly from [2, 10].
 - Models are fine-tuned on real-world sequencing data (Noisy-DNA and Microsoft datasets).
 
 For full experimental details, see [our paper](https://arxiv.org/abs/XXXX.XXXXX).