Description

Tokenization is a fundamental step in natural language processing where text is divided into smaller units called tokens. These tokens can be words, subwords, or characters, depending on the specific tokenization strategy. Tokenization is crucial for many NLP tasks as it creates the basic units that models use to process and understand text. Different tokenization methods can significantly impact the performance of NLP models.

Examples

• 📝 Word tokenization
• 🧩 Subword tokenization (e.g., BPE, WordPiece)
• 🔤 Character tokenization

Applications