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Which of the following is the correct way to tokenize multilingual text for sentiment analysis using a pretrained transformer model?

easy📝 Syntax Q3 of 15
NLP - Sentiment Analysis Advanced
Which of the following is the correct way to tokenize multilingual text for sentiment analysis using a pretrained transformer model?
ASplit text by spaces only, ignoring tokenizer
BUse a tokenizer designed only for English
CUse the model's multilingual tokenizer to split text into tokens
DManually split text into characters
Step-by-Step Solution
Solution:

  1. Step 1: Understand tokenization for transformers

    Pretrained multilingual models come with tokenizers that handle multiple languages properly.

  2. Step 2: Evaluate other options

    Simple space splitting or English-only tokenizers miss language-specific tokens; manual splitting is inefficient.

  3. Final Answer:

    Use the model's multilingual tokenizer to split text into tokens -> Option C

  4. Quick Check:

    Multilingual tokenizer = correct token splitting [OK]
Quick Trick: Use tokenizer that matches your multilingual model [OK]
Common Mistakes:
MISTAKES
  • Using English-only tokenizers for other languages
  • Ignoring tokenizer and splitting by spaces
  • Splitting text into characters manually

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