title: Octopus v4: Graph of language models
summary: Language models have been effective in a wide range of applications, yet the
  most sophisticated models are often proprietary. For example, GPT-4 by OpenAI
  and various models by Anthropic are expensive and consume substantial energy.
  In contrast, the open-source community has produced competitive models, like
  Llama3. Furthermore, niche-specific smaller language models, such as those
  tailored for legal, medical or financial tasks, have outperformed their
  proprietary counterparts. This paper introduces a novel approach that employs
  functional tokens to integrate multiple open-source models,
  each optimized for particular tasks. Our newly developed Octopus v4 model
  leverages functional tokens to intelligently direct user queries to
  the most appropriate vertical model and reformat the query to achieve the best
  performance. Octopus v4, an evolution of the Octopus v1, v2, and v3 models,
  excels in selection and parameter understanding and reformatting. Additionally,
  we explore the use of graph as a versatile data structure that effectively
  coordinates multiple open-source models by harnessing the capabilities of the
  Octopus model and functional tokens. Use our open-sourced GitHub
  (https://www.nexa4ai.com/) to try Octopus v4 models
  (https://huggingface.co/NexaAIDev/Octopus-v4), and contrite to a larger
  graph of language models. By activating models less than 10B parameters, we
  achieved SOTA MMLU score of 74.8 among the same level models.
paper_authors._id: 663197a6a2354b0f50ae1605
paper_authors.name: Wei Chen
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-05-02T07:51:10.068Z
paper_authors._id: 65c082c626c639b0009a3c82
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/65c082c626c639b0009a3c82/w_Q_5iLOM-nh_drd9Tu4X.jpeg
paper_authors.fullname: Alex Chen
paper_authors.type: user
paper_authors.user: alexchen4ai
paper_authors._id: 663197a6a2354b0f50ae1606
paper_authors.name: Zhiyuan Li
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2024-05-02T08:01:51.908Z
paper_authors._id: 644de55076c0ab1880b9cb4d
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/644de55076c0ab1880b9cb4d/zKm7baOIzt_a4py8mYkck.jpeg
paper_authors.fullname: Zack Li
paper_authors.type: user
paper_authors.user: zackli4ai
paper_title: Octopus v4: Graph of language models
paper_summary: Language models have been effective in a wide range of applications, yet the
  most sophisticated models are often proprietary. For example, GPT-4 by OpenAI
  and various models by Anthropic are expensive and consume substantial energy.
  In contrast, the open-source community has produced competitive models, like
  Llama3. Furthermore, niche-specific smaller language models, such as those
  tailored for legal, medical or financial tasks, have outperformed their
  proprietary counterparts. This paper introduces a novel approach that employs
  functional tokens to integrate multiple open-source models,
  each optimized for particular tasks. Our newly developed Octopus v4 model
  leverages functional tokens to intelligently direct user queries to
  the most appropriate vertical model and reformat the query to achieve the best
  performance. Octopus v4, an evolution of the Octopus v1, v2, and v3 models,
  excels in selection and parameter understanding and reformatting. Additionally,
  we explore the use of graph as a versatile data structure that effectively
  coordinates multiple open-source models by harnessing the capabilities of the
  Octopus model and functional tokens. Use our open-sourced GitHub
  (https://www.nexa4ai.com/) to try Octopus v4 models
  (https://huggingface.co/NexaAIDev/Octopus-v4), and contrite to a larger
  graph of language models. By activating models less than 10B parameters, we
  achieved SOTA MMLU score of 74.8 among the same level models.
paper_ai_keywords: functional tokens multiple open-source models Octopus v4 model Octopus v1 Octopus v2 Octopus v3 models graph SOTA MMLU score