Merge and Conquer: Instructing Multilingual Models by Adding Target Language Weights

1. 1Identify a pre-trained multilingual model as a base model
2. 2Add target language weights to the base model to adapt it to a specific low-resource language
3. 3Fine-tune the model on a small amount of target language data to improve performance
4. 4Evaluate the model's performance on the target language task

NLP engineers and researchers working on multilingual models can benefit from this approach, as it provides a lightweight alternative to existing adaptation methods

💡 Adding target language weights can be a lightweight and effective way to adapt multilingual models to low-resource languages

💡 Improve multilingual models with target language weights! 🌎