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license: llama2

WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct (RLEIF)

πŸ€— HF Repo β€’πŸ± Github Repo β€’ 🐦 Twitter β€’ πŸ“ƒ [WizardLM] β€’ πŸ“ƒ [WizardCoder] β€’ πŸ“ƒ [WizardMath]

πŸ‘‹ Join our Discord

Model Checkpoint Paper HumanEval MBPP Demo License
WizardCoder-Python-34B-V1.0 πŸ€— HF Link πŸ“ƒ [WizardCoder] 73.2 61.2 Demo Llama2
WizardCoder-15B-V1.0 πŸ€— HF Link πŸ“ƒ [WizardCoder] 59.8 50.6 -- OpenRAIL-M
WizardCoder-Python-13B-V1.0 πŸ€— HF Link πŸ“ƒ [WizardCoder] 64.0 55.6 -- Llama2
WizardCoder-Python-7B-V1.0 πŸ€— HF Link πŸ“ƒ [WizardCoder] 55.5 51.6 Demo Llama2
WizardCoder-3B-V1.0 πŸ€— HF Link πŸ“ƒ [WizardCoder] 34.8 37.4 -- OpenRAIL-M
WizardCoder-1B-V1.0 πŸ€— HF Link πŸ“ƒ [WizardCoder] 23.8 28.6 -- OpenRAIL-M
Model Checkpoint Paper GSM8k MATH Online Demo License
WizardMath-70B-V1.0 πŸ€— HF Link πŸ“ƒ [WizardMath] 81.6 22.7 Demo Llama 2
WizardMath-13B-V1.0 πŸ€— HF Link πŸ“ƒ [WizardMath] 63.9 14.0 Demo Llama 2
WizardMath-7B-V1.0 πŸ€— HF Link πŸ“ƒ [WizardMath] 54.9 10.7 Demo Llama 2
Model Checkpoint Paper MT-Bench AlpacaEval GSM8k HumanEval License
WizardLM-70B-V1.0 πŸ€— HF Link πŸ“ƒComing Soon 7.78 92.91% 77.6% 50.6 pass@1 Llama 2 License
WizardLM-13B-V1.2 πŸ€— HF Link 7.06 89.17% 55.3% 36.6 pass@1 Llama 2 License
WizardLM-13B-V1.1 πŸ€— HF Link 6.76 86.32% 25.0 pass@1 Non-commercial
WizardLM-30B-V1.0 πŸ€— HF Link 7.01 37.8 pass@1 Non-commercial
WizardLM-13B-V1.0 πŸ€— HF Link 6.35 75.31% 24.0 pass@1 Non-commercial
WizardLM-7B-V1.0 πŸ€— HF Link πŸ“ƒ [WizardLM] 19.1 pass@1 Non-commercial

Github Repo: https://github.com/nlpxucan/WizardLM/tree/main/WizardMath

Twitter: https://twitter.com/WizardLM_AI/status/1689998428200112128

Discord: https://discord.gg/VZjjHtWrKs

Comparing WizardMath-V1.0 with Other LLMs.

πŸ”₯ The following figure shows that our WizardMath-70B-V1.0 attains the fifth position in this benchmark, surpassing ChatGPT (81.6 vs. 80.8) , Claude Instant (81.6 vs. 80.9), PaLM 2 540B (81.6 vs. 80.7).

WizardMath

❗Note for model system prompts usage:

Please use the same systems prompts strictly with us, and we do not guarantee the accuracy of the quantified versions.

Default version:

"Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\n{instruction}\n\n### Response:"

CoT Version: οΌˆβ—For the simple math questions, we do NOT recommend to use the CoT prompt.οΌ‰

"Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\n{instruction}\n\n### Response: Let's think step by step."

Inference WizardMath Demo Script

We provide the WizardMath inference demo code here.

❗To commen concern about dataset:

Recently, there have been clear changes in the open-source policy and regulations of our overall organization's code, data, and models. Despite this, we have still worked hard to obtain opening the weights of the model first, but the data involves stricter auditing and is in review with our legal team . Our researchers have no authority to publicly release them without authorization. Thank you for your understanding.

Citation

Please cite the repo if you use the data, method or code in this repo.

@article{luo2023wizardmath,
  title={WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct},
  author={Luo, Haipeng and Sun, Qingfeng and Xu, Can and Zhao, Pu and Lou, Jianguang and Tao, Chongyang and Geng, Xiubo and Lin, Qingwei and Chen, Shifeng and Zhang, Dongmei},
  journal={arXiv preprint arXiv:2308.09583},
  year={2023}
}