Papers › WizardLM: Empowering Large Language Models to Follow Complex Instructions

WizardLM: Empowering Large Language Models to Follow Complex Instructions

24 Apr 2023arXiv:2304.12244archive 2025-07-28

Can Xu, Qingfeng Sun, Kai Zheng, Xiubo Geng, Pu Zhao, Jiazhan Feng, Chongyang Tao, Daxin Jiang

Training large language models (LLMs) with open-domain instruction following data brings colossal success. However, manually creating such instruction data is very time-consuming and labor-intensive. Moreover, humans may struggle to produce high-complexity instructions. In this paper, we show an avenue for creating large amounts of instruction data with varying levels of complexity using LLM instead of humans. Starting with an initial set of instructions, we use our proposed Evol-Instruct to rewrite them step by step into more complex instructions. Then, we mix all generated instruction data to fine-tune LLaMA. We call the resulting model WizardLM. Human evaluations on a complexity-balanced test bed and Vicuna's testset show that instructions from Evol-Instruct are superior to human-created ones. By analyzing the human evaluation results of the high complexity part, we demonstrate that outputs from our WizardLM are preferred to outputs from OpenAI ChatGPT. In GPT-4 automatic evaluation, WizardLM achieves more than 90\% capacity of ChatGPT on 17 out of 29 skills. Even though WizardLM still lags behind ChatGPT in some aspects, our findings suggest that fine-tuning with AI-evolved instructions is a promising direction for enhancing LLMs. Our code and data are public at https://github.com/nlpxucan/WizardLM

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Code

Syntology Ran 2 of 3 code samples harvested from 2 repositories linked to this paper; 1 has no recorded run. Of those that ran: 1 ran · our draft was wrong; 1 ran with no contract checked.

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nlpxucan/wizardlm officialmentioned in papermentioned on GitHubpytorch report
lcw99/evolve-instruct mentioned on GitHubpytorch report
nlpxucan/evol-instruct mentioned on GitHub report
togethercomputer/llama-2-7b-32k-instruct mentioned on GitHubApache-2.0 report

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1ran · our draft was wrong
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createConstraintsPrompt nlpxucan/wizardlm/Evol_Instruct/depth.py official repository ran · our draft was wrong fingerprinted no licence file found · pointer only · e549385d87bbf8ef · report
WizardLM lcw99/evolve-instruct/evolve.py community (archive-listed) ran no licence file found · pointer only · 3c2c841067eae10b · report
Mutation lcw99/evolve-instruct/evolve.py community (archive-listed) unverified no licence file found · pointer only · 153ae3af5c36701d · report

Tasks

Instruction Following

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Methods

Absolute Position EncodingsAdamAttentionBPEDense ConnectionsDropoutGPT-4Label SmoothingLayer NormalizationLinear LayerMulti-Head AttentionPosition-Wise Feed-Forward LayerResidual ConnectionSoftmaxTestTransformer

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