ByteDance Seed 研究者将在 PyTorch Conference 介绍 LLM 训练调试工具 OpGuard
训练 LLM 时 loss 突然炸了却找不到原因？OpGuard 能逐比特比对两次训练，直接定位出错的那个算子。
LLM 生产级训练中，微小的比特级错误往往在 loss 曲线出现异常之前就已存在，排查难度很高。密歇根大学博士生、ByteDance Seed 学生研究员 Ziming 开发了 OpGuard，它通过逐比特对比两次训练运行，精确定位执行开始分歧的第一个算子。该工具将在 10 月 20 日至 21 日于 San Jose 举办的 PyTorch Conference North America 上进行讲解。
Debugging LLM training in production is notoriously challenging because subtle bitwise errors can surface long before they ever trigger a spike in the loss curve.
Ziming, a PhD student at the University of Michigan and student researcher at @ByteDanceSeed_ , will speak at PyTorch Conference North America on how to solve this issue using OpGuard. OpGuard compares separate training runs bit by bit to pinpoint the exact initial operation where executions diverge.
Join us in San Jose, October 20 to 21, to learn how bitwise alignment delivers faster, more precise LLM training debugging: https://t.co/jBApW8nESi
#PyTorchCon @UMich
