Building a Tokenizer from Scratch

#Learning Objectives

• Build a production-grade BPE tokenizer that handles Unicode, whitespace normalization, and special tokens
• Implement byte-level fallback so the tokenizer can encode any input (including emoji, CJK, and code) without unknown tokens
• Add pre-tokenization regex patterns that split text at word boundaries before applying BPE merges
• Train a custom tokenizer on a corpus and evaluate its compression ratio against tiktoken on multilingual text