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Inside multi-node training: How to scale model training across GPU clusters

This article is a technical guide explaining multi-node GPU training, covering parallelism strategies, network interconnects, checkpointing, and practical steps for scaling model training across GPU clusters, with a production example using Qwen2.5-72B.

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Training foundation models requires orchestrating hundreds or thousands of GPUs working in parallel. This article walks through the infrastructure, techniques, and practical steps for distributed training at scale.

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