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:
- 
Parallel aligned sentence pairs for knowledge transfer.
 
- 
The monolingual model acts as a teacher, multilingual as a student.
 
- 
MSE loss is used to align logits across languages.
 
Hence, distillation enables effective knowledge transfer from monolingual to multilingual models using shared semantic examples.