How do LLMs handle multiple languages?

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Answer

LLMs handle multiple languages by being trained on multilingual datasets, allowing them to understand and generate text in different languages. They use shared representations to capture language patterns, enabling cross-lingual capabilities. However, their performance can vary depending on the language's representation in the training data. While LLMs excel in widely spoken languages, less common languages may require additional fine-tuning and data to achieve comparable performance.

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