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Computer Science > Computation and Language

arXiv:2404.01744 (cs)
[Submitted on 2 Apr 2024]

Title:Octopus v2: On-device language model for super agent

Authors:Wei Chen, Zhiyuan Li
View a PDF of the paper titled Octopus v2: On-device language model
for super agent, by Wei Chen and 1 other authors
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    Abstract:Language models have shown effectiveness in a variety of
    software applications, particularly in tasks related to automatic
    workflow. These models possess the crucial ability to call
    functions, which is essential in creating AI agents. Despite the
    high performance of large-scale language models in cloud
    environments, they are often associated with concerns over
    privacy and cost. Current on-device models for function calling
    face issues with latency and accuracy. Our research presents a
    new method that empowers an on-device model with 2 billion
    parameters to surpass the performance of GPT-4 in both accuracy
    and latency, and decrease the context length by 95\%. When
    compared to Llama-7B with a RAG-based function calling mechanism,
    our method enhances latency by 35-fold. This method reduces the
    latency to levels deemed suitable for deployment across a variety
    of edge devices in production environments, aligning with the
    performance requisites for real-world applications.

Subjects: Computation and Language (cs.CL)
Cite as:  arXiv:2404.01744 [cs.CL]
          (or arXiv:2404.01744v1 [cs.CL] for this version)
          https://doi.org/10.48550/arXiv.2404.01744
          Focus to learn more
          arXiv-issued DOI via DataCite

Submission history

From: Wei Chen [view email]
[v1] Tue, 2 Apr 2024 09:01:32 UTC (1,595 KB)
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    model for super agent, by Wei Chen and 1 other authors
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