Update README.md

README.md

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 ## Overview
 
-This repository contains a **Grapheme-Aware Tokenizer (GAT)** specifically trained for **Kannada**, designed to handle the unique orthographic and phonological structure of the language. Unlike traditional subword tokenizers such as BPE or WordPiece, this tokenizer operates at the **grapheme level**, improving representation fidelity and reducing tokenization imbalance across languages.
+This repository contains a **Grapheme-Aware Tokenizer (GAT)** specifically trained for **Kannada**, designed to handle the unique orthographic and phonological structure of the language. Unlike traditional subword tokenizers such as BPE or WordPiece, this tokenizer operates at the **grapheme level**, improving representation fidelity and reducing tokenization imbalance in token count.
 
 For tokenizer training, we utilize a **composite corpus** consisting of:
 
 1. **[Samanantar dataset](https://github.com/AI4Bharat/indic-parallel-corpus)** by AI4Bharat  
 2. **[Kannada-Instruct dataset](https://huggingface.co/datasets/Cognitive-Lab/Kannada-Instruct-dataset)** by Cognitive Lab  
 
-Together, these datasets amount to approximately **4.5 million Kannada sentences**, covering a wide range of topics including general conversation, instruction-following data, and parallel text.
+Together, these datasets amount to approximately **4.5 million Kannada sentences**