Distributed Training interview questions

Train at scale: data and model parallelism, synchronization, and the infrastructure trade-offs of multi-GPU and multi-node training.

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FSDP Fine-Tuning of a 70B Parameter ModelML Engineeringmedium

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Real Distributed Training questions reported from interviews at 50+ AI companies, with the golden answer and full production scoring. Unlock with Pro →

Distributed Training — ZeRO Stages and Communication TradeoffsReported at Metamedium
Distributed Training — Fitting and Scaling a 70B ModelReported at Metahard
Distributed Training Pipeline for Trillion-Parameter Language ModelReported at Nvidiahard

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