Update README.md

README.md

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 <!-- Provide a longer summary of what this model is. -->
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+A Byte-Pair Encoding (BPE) tokenizer works by grouping frequently occurring pairs of characters instead of splitting text into words or individual characters. By training on a Sindhi Twitter dataset, this tokenizer captures common letter combinations in Sindhi, preserving the language's phonetic structure.
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+The key advantage of BPE is its ability to handle unknown words. Similar to how we can pronounce a new word by recognizing character pairings, the BPE tokenizer breaks down unfamiliar words into smaller, familiar sub-units, making it robust for unseen terms while maintaining consistency with the language's sound patterns.
 
 - **Developed by:** Fahad Maqsood Qazi
 - **Model type:** BPE Tokenizer
 - **Language(s) (NLP):** Sindhi (Perso-Arabic Script)
 - **License:** [More Information Needed]
 
-## Uses
+## Usage
 
 <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->