LongRecipe: Recipe for Efficient Long Context Generalization in Large Language Models

Zhiyuan Hu; Yuliang Liu; Jinman Zhao; Suyuchen Wang; Yan Wang; Wei Shen; Qing Gu; Anh Tuan Luu; See-Kiong Ng; Zhiwei Jiang; Bryan Hooi

arXiv · 2409.00509

LongRecipe: Recipe for Efficient Long Context Generalization in Large Language Models

Zhiyuan Hu·Yuliang Liu·Jinman Zhao·Suyuchen Wang·Yan Wang·Wei Shen·Qing Gu·Anh Tuan Luu·See-Kiong Ng·Zhiwei Jiang·Bryan Hooi

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Abstract

Large language models (LLMs) face significant challenges in handling long-context tasks because of their limited effective context window size during pretraining, which restricts their ability to generalize over extended sequences. Meanwhile, extending the context window in LLMs through post-pretraining is highly resource-intensive. To address this, we introduce LongRecipe, an efficient training strategy for extending the context window of LLMs, including impactful token analysis, position index transformation, and training optimization strategies. It simulates long-sequence inputs while maintaining training efficiency and significantly improves the model's understanding of long-range dependencies. Experiments on three types of LLMs show that LongRecipe can utilize long sequences while requiring only 30% of the target context window size, and reduces computational training resource over 85% compared to full sequence training. Furthermore, LongRecipe also preserves the original LLM's capabilities in general tasks. Ultimately, we can extend the effective context window of open-source LLMs from 8k to 128k, achieving performance close to GPT-4 with just one day of dedicated training using a single GPU with 80G memory. Our code is released at https://github.com/zhiyuanhubj/LongRecipe.

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BibTeX RIS

Zhiyuan Hu, Yuliang Liu, Jinman Zhao, Suyuchen Wang, Yan Wang, Wei Shen, Qing Gu, Anh Tuan Luu, See-Kiong Ng, Zhiwei Jiang, Bryan Hooi. 2024-09-04. LongRecipe: Recipe for Efficient Long Context Generalization in Large Language Models. https://arxiv.org/abs/2409.00509

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