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How does GPT handle out-of-vocabulary or rare words?

Q: How does GPT handle out-of-vocabulary or rare words?

GPT uses a technique called Byte Pair Encoding (BPE) to handle out-of-vocabulary or rare words. This method breaks down words into smaller subword units, allowing GPT to generate meaningful predictions even for unseen words. By leveraging a large training dataset, GPT learns to associate subword units with their correct meaning, enabling it to handle rare words effectively.

When it encounters an unfamiliar word, GPT can deconstruct it into subword units using BPE, which are already part of its vocabulary. By combining these known subword units, GPT can approximate the meaning of the rare word and generate a sensible response. This approach helps GPT maintain context and coherence in its output, even when faced with limited vocabulary.

Additionally, GPT’s training data includes a diverse range of words and phrases, allowing it to generalize patterns and infer meanings for novel words based on context. This capability enhances GPT’s ability to handle out-of-vocabulary words effectively while maintaining its natural language generation capabilities.

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