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Computer Science > Computation and Language

arXiv:2402.13753 (cs)
[Submitted on 21 Feb 2024]

Title:LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens

Authors:Yiran Ding, Li Lyna Zhang, Chengruidong Zhang, Yuanyuan Xu,
Ning Shang, Jiahang Xu, Fan Yang, Mao Yang
Download a PDF of the paper titled LongRoPE: Extending LLM Context
Window Beyond 2 Million Tokens, by Yiran Ding and 7 other authors
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    Abstract:Large context window is a desirable feature in large
    language models (LLMs). However, due to high fine-tuning costs,
    scarcity of long texts, and catastrophic values introduced by new
    token positions, current extended context windows are limited to
    around 128k tokens. This paper introduces LongRoPE that, for the
    first time, extends the context window of pre-trained LLMs to an
    impressive 2048k tokens, with up to only 1k fine-tuning steps at
    within 256k training lengths, while maintaining performance at
    the original short context window. This is achieved by three key
    innovations: (i) we identify and exploit two forms of
    non-uniformities in positional interpolation through an efficient
    search, providing a better initialization for fine-tuning and
    enabling an 8x extension in non-fine-tuning scenarios; (ii) we
    introduce a progressive extension strategy that first fine-tunes
    a 256k length LLM and then conducts a second positional
    interpolation on the fine-tuned extended LLM to achieve a 2048k
    context window; (iii) we readjust LongRoPE on 8k length to
    recover the short context window performance. Extensive
    experiments on LLaMA2 and Mistral across various tasks
    demonstrate the effectiveness of our method. Models extended via
    LongRoPE retain the original architecture with minor
    modifications to the positional embedding, and can reuse most
    pre-existing optimizations.

Subjects: Computation and Language (cs.CL)
Cite as:  arXiv:2402.13753 [cs.CL]
          (or arXiv:2402.13753v1 [cs.CL] for this version)
          https://doi.org/10.48550/arXiv.2402.13753
          Focus to learn more
          arXiv-issued DOI via DataCite

Submission history

From: Li Lyna Zhang [view email]
[v1] Wed, 21 Feb 2024 12:30:33 UTC (944 KB)
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