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Large Language ModelsAI Coding Assistantsr/MachineLearningPublished: Sep 23, 2026, 06:00 JST

Templar's Crucible: stage skipping keeps training alive at 1% failure rate

Templar's Crucible: stage skipping keeps training alive at 1% failure rate

Templar's Crucible, a distributed pre-training platform with data-parallel replicas and pipeline parallelism, simulated stage skipping on a 178M model with eight replicas and four stages per replica. At a 1% per-replica failure probability per global step, validation loss stayed close to the no-failure baseline even when each outage removed a stage for six global steps.

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