🌍 Multilingual Tokenization Challenges

🎯 Common Challenges

1. No Word Boundaries (Chinese, Japanese, Thai)

Chinese: "你好世界" → No spaces!
Solution: Character-level or SentencePiece

2. Right-to-Left Text (Arabic, Hebrew)

Arabic: "مرحبا" → RTL direction
Solution: Bidirectional-aware tokenizers

3. Combining Characters (Indic Scripts)

Hindi: "नमस्ते" → Complex character combinations
Solution: Unicode normalization (NFC)

💻 Best Practices

import unicodedata
from transformers import AutoTokenizer

# 1. Always normalize Unicode
text = unicodedata.normalize('NFC', text)

# 2. Use multilingual tokenizers
tokenizer = AutoTokenizer.from_pretrained("xlm-roberta-base")

# 3. Test with real data
texts = ["Hello", "你好", "مرحبا", "नमस्ते"]
for t in texts:
    tokens = tokenizer.tokenize(t)
    print(f"{t} → {tokens}")