#federated learning

FedScale is an open-source platform for federated learning, featuring scalable deployment and extensive evaluation tools for diverse environments. It supports FL experiments with advanced APIs and diverse datasets, including tasks such as image classification and language modeling. FedScale offers scalable and extensible solutions for realistic FL training, proving itself as a vital resource for research and development in federated learning.

OpenFedLLM is an open-source resource for training large language models using federated learning. It offers seven federated learning methods, two methods for instruction tuning and value alignment, and more than 30 metrics for assessing capabilities in tasks such as medical and financial QA, code generation, and math solving. This project includes FedLLM-Bench, a benchmarking tool for evaluating federated LLM training. The platform enables the installation, training script access for instruction tuning and value alignment, and comprehensive evaluation tools. OpenFedLLM aids in maintaining decentralized data privacy while pushing forward in the field of language model training.