Category: AWS ParallelCluster

The Institute of Science Tokyo has successfully trained Llama 3.3 Swallow, a 70-billion-parameter large language model (LLM) with enhanced Japanese capabilities, using Amazon SageMaker HyperPod. The model demonstrates superior performance in Japanese language tasks, outperforming GPT-4o-mini and other leading models. This technical report details the training infrastructure, optimizations, and best practices developed during the project.

When it comes to running distributed machine learning (ML) workloads, AWS offers you both managed and self-service offerings. Amazon SageMaker is a managed service that can help engineering, data science, and research teams save time and reduce operational overhead. AWS ParallelCluster is an open-source, self-service cluster management tool for customers who wish to maintain more […]