FederatedScope-LLM: A Comprehensive Package for Fine-tuning Large Language Models in Federated Learning

Understand

LLMs have demonstrated great capabilities in various NLP tasks.

• Different entities can further improve the performance of those LLMs on their specific downstream tasks by fine-tuning LLMs.
• When several entities have similar interested tasks, but their data cannot be shared because of privacy concerns regulations, federated learning (FL) is a mainstream solution to leverage the data of different entities.
• However, fine-tuning LLMs in federated learning settings still lacks adequate support from existing FL frameworks because it has to deal with optimizing the consumption of significant communication and computational resources, data preparation for different tasks, and distinct information protection demands.