Tokenization Advanced

Advanced tokenization breaks text into semantic units (tokens) efficiently while preserving meaning and enabling language models to process text. Modern techniques like byte-pair encoding (BPE), WordPiece, and SentencePiece balance vocabulary size, coverage, and model efficiency. Advanced tokenization also handles multilingual text, special characters, and domain-specific terminology. Tokenization is often overlooked, but it directly impacts model accuracy, training speed, and inference latency. A poorly tokenized corpus can reduce accuracy by 10%+; optimal tokenization improves it.