You can transfer knowledge from a monolingual model to a multilingual LLM by distilling task-specific representations from the source model into the multilingual target using aligned datasets.
Here is the code snippet below:

In the above code we are using the following key points:
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Parallel aligned sentence pairs for knowledge transfer.
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The monolingual model acts as a teacher, multilingual as a student.
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MSE loss is used to align logits across languages.
Hence, distillation enables effective knowledge transfer from monolingual to multilingual models using shared semantic examples.