AI Terms Dictionary

Definition

Byte Pair Encoding (BPE) is a data compression technique adapted for natural language processing to handle out-of-vocabulary words. It starts with a vocabulary of individual characters and iteratively merges the most frequent adjacent pairs of symbols. This process creates a hierarchy of subword units, allowing models to balance between character-level flexibility and word-level efficiency. It is widely used in transformer-based models like GPT-2 and BERT to manage vocabulary size while preserving semantic meaning across diverse languages.

Summary

Byte Pair Encoding is an algorithm used for subword tokenization that iteratively merges the most frequent character pairs to build a vocabulary.

Key Concepts

• Subword Tokenization
• Vocabulary Merging
• Frequency Analysis
• Out-of-Vocabulary Handling

Use Cases

• Preprocessing text for Large Language Models
• Handling morphologically rich languages
• Reducing vocabulary size in neural networks

Code Example

1
2
3
4

import tiktoken
enc = tiktoken.get_encoding("cl100k_base")
tokens = enc.encode("unhappiness")
print(tokens)

Related Terms

• WordPiece
• SentencePiece
• Tokenization
• Subword Units