mediumNewNVIDIAMetaDatabricks

Your distributed training run died six hours into an epoch on preemptible GPUs. What happens next, and how do you design for it?

A training job is an hours-long computation with no user watching. Whether an interruption costs four minutes or four days is decided entirely by checkpoint cadence and restart semantics designed before the run.

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Next in this trackA team wants to fine-tune a model every time their labelled data grows. Build them the pipeline.Next in this trackHow often should a large training run checkpoint, and what does the answer depend on?Next in this trackA training run from three months ago cannot be reproduced. Same code, same data, different result. Where does the difference come from?

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