从这个角度看，像林俊旸、郁博文这样的技术负责人，固然是Qwen系列模型的重要贡献者，但Qwen的成功本质上仍然是组织能力的产物，而不是某一个人的成果。
Last week we released NanoGPT Slowrun , an open repo for data-efficient learning algorithms. The rules are simple: train on 100M tokens from FineWeb, use as much compute as you want, lowest validation loss wins. Improvements are submitted as PRs to the repo and merged if they lower val loss. The constraint is the inverse of speedruns like modded-nanogpt , which optimize wall-clock time. Those benchmarks have been hugely productive, but optimizing for speed filters out expensive ideas: heavy regularization, second-order optimizers, gradient descent alternatives. Slowrun is built for exactly those ideas.
，这一点在im钱包官方下载中也有详细论述
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