Interactive exploration of different tokenization techniques used in NLP
Explore how different tokenizers break down text into tokens using BPE, WordPiece, and SentencePiece algorithms.
Tokenization is the process of breaking down text into smaller units (tokens) that can be processed by machine learning models. Different tokenization strategies have various trade-offs in terms of vocabulary size, handling of out-of-vocabulary words, and computational efficiency.
Our Tokenizer Explorer allows you to compare different tokenization algorithms side-by-side and understand how they handle various types of text.
Try tokenizing text in different languages to see how different algorithms handle multilingual input!