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CoLLiE是一个可以帮助您从零开始训练大模型的完整工具箱，它提供了数据预处理、模型微调、模型保存以及训练过程各项指标监测等功能。CoLLiE集成了现有的并行策略、高效参数微调方法和高效优化器，以加快训练的速度，提高训练的质量，降低训练的开销 ...

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CoLLiE 具有很多的功能，例如tutorial-1中示例代码所提到的：通过配置类CollieConfig设置并行策略，通过监视器Monitor观察训练过程、输出评测结果，以及如后续tutorial所示，通过回调函数Callback自定义训练过程，通过评测单元Evaluator来进行评测。

2023年12月1日 · This paper introduces CoLLiE, an efficient library that facilitates collaborative training of large language models using 3D parallelism, parameter-efficient fine-tuning (PEFT) methods, and optimizers such as Lion, Adan, Sophia, LOMO and AdaLomo.

首先，CoLLiE 致力于涵盖包含适用于各种特异场景的并行方式，整合四种并行策略： 数据并行 DP 、 流水线并行 PP 、 张量并行 TP （ 以及 3D并行）、 零冗余优化器 ZeRO （tutorial-3） 其次，CoLLiE 致力于涵盖大语言模型从预训练、全量微调、参数高效微调的全流程，提出面向全参数高效微调的 LOMO算法，支持 LoRA 、 PrefixTuning 、 PromptTuning 等参数高效微调方 …

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