Tokenization Explorer

⚙️ Input & Controls

Enter text to tokenize:

Vocabulary Size:

1000

Smaller vocabulary = more splitting, Larger vocabulary = less splitting

Tokenization Method:

Character-Level

Split every character individually

Word-Level

Keep words intact (fails on rare words)

Subword (BPE)

Optimal balance: common words intact, rare words split

Tokens

Vocab Used

Efficiency

Common words

Medium frequency

Rare/split tokens

📝 Character-Level

Pros: No vocabulary limits, handles any text
Cons: Very long sequences, loses word meaning

📖 Word-Level

Pros: Preserves word meaning, intuitive
Cons: Huge vocabulary needed, fails on rare words

🎯 Subword (BPE)

Pros: Balanced approach, handles rare words, efficient
Cons: Slightly more complex to implement