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To manage the computational demands of training Large Language Models at scale, distributed training strategies are a crucial consideration.

Distributed Training for Large-Scale LLMs

Critically evaluate the team's decision to use only data parallelism. Will this strategy succeed in training the model? Justify your answer by explaining the fundamental limitation of their chosen approach in this specific context, and propose a more suitable strategy or combination of strategies.

Evaluating a Distributed Training Strategy

Match each distributed training strategy with the primary computational challenge it is designed to address when training very large models.

A machine learning team is training a language model whose parameters are too large to fit into the memory of a single accelerator. Which of the following statements most accurately analyzes the trade-offs between the primary strategies they could employ to address this specific problem?

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