Subword Tokenization

Subword tokenization is a method used in natural language processing to break down words into smaller, more manageable units called subwords. This technique is particularly useful for handling out-of-vocabulary words and reducing the vocabulary size in language models. By segmenting words into subwords, models can better generalize across different languages and dialects, improving their ability to understand and generate text. Common algorithms for subword tokenization include Byte Pair Encoding (BPE) and WordPiece, which are widely used in models like BERT and GPT. This approach enhances the model's performance in tasks such as translation, text generation, and sentiment analysis.