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Related Questions
- Can you explain the concept of data parallelism in distributed training of large language models?
- What are the key differences between data parallelism and model parallelism in distributed training?
- How can you implement synchronous and asynchronous training strategies in a distributed setting?
- What role does gradient accumulation play in improving the efficiency of distributed training?
- Can you discuss the impact of communication overhead on the performance of distributed training?
- How can you leverage techniques like model pruning and knowledge distillation to improve the scalability of large language models?
- What are some strategies for managing and optimizing the memory usage of large language models during distributed training?
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