WizardLMTeam/WizardMath-70B-V1.0

Model

125

stars

41

commits

1

repos using this model

1

linked in READMEs

Dec 20, 2023

updated

endpoints_compatible
llama
pytorch
text-generation
text-generation-inference
transformers
Browse cluster: Large Language Model Training & Inference β†’

README

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

🏠 Home Page

πŸ€— HF Repo β€’πŸ± Github Repo β€’ 🐦 Twitter

πŸ“ƒ [WizardLM] β€’ πŸ“ƒ [WizardCoder] β€’ πŸ“ƒ [WizardMath]

πŸ‘‹ Join our Discord

News

[12/19/2023] πŸ”₯ We released WizardMath-7B-V1.1 trained from Mistral-7B, the SOTA 7B math LLM, achieves 83.2 pass@1 on GSM8k, and 33.0 pass@1 on MATH.

[12/19/2023] πŸ”₯ WizardMath-7B-V1.1 outperforms ChatGPT 3.5, Gemini Pro, Mixtral MOE, and Claude Instant on GSM8K pass@1.

[12/19/2023] πŸ”₯ WizardMath-7B-V1.1 is comparable with ChatGPT 3.5, Gemini Pro, and surpasses Mixtral MOE on MATH pass@1.

ModelCheckpointPaperGSM8kMATH
WizardMath-7B-V1.1πŸ€— HF LinkπŸ“ƒ [WizardMath]83.233.0
WizardMath-70B-V1.0πŸ€— HF LinkπŸ“ƒ [WizardMath]81.622.7
WizardMath-13B-V1.0πŸ€— HF LinkπŸ“ƒ [WizardMath]63.914.0
WizardMath-7B-V1.0πŸ€— HF LinkπŸ“ƒ [WizardMath]54.910.7

[12/19/2023] Comparing WizardMath-7B-V1.1 with other open source 7B size math LLMs.

ModelGSM8k Pass@1MATH Pass@1
MPT-7B6.83.0
Llama 1-7B11.02.9
Llama 2-7B12.32.8
Yi-6b32.65.8
Mistral-7B37.89.1
Qwen-7b47.89.3
RFT-7B50.3--
MAmmoTH-7B (COT)50.510.4
WizardMath-7B-V1.054.910.7
Abel-7B-00159.713
MetaMath-7B66.519.8
Arithmo-Mistral-7B74.725.3
MetaMath-Mistral-7B77.728.2
Abel-7B-00280.429.5
WizardMath-7B-V1.183.233.0

[12/19/2023] Comparing WizardMath-7B-V1.1 with large open source (30B~70B) LLMs.

ModelGSM8k Pass@1MATH Pass@1
Llemma-34B51.525.0
Minerva-62B52.427.6
Llama 2-70B56.813.5
DeepSeek 67B63.4--
Gork 33B62.923.9
MAmmoTH-70B72.421.1
Yi-34B67.915.9
Mixtral 8x7B74.428.4
MetaMath-70B82.326.6
WizardMath-7B-V1.183.233.0

❗ Data Contamination Check:

Before model training, we carefully and rigorously checked all the training data, and used multiple deduplication methods to verify and prevent data leakage on GSM8k and MATH test set.

ModelCheckpointPaperMT-BenchAlpacaEvalGSM8kHumanEvalLicense
WizardLM-70B-V1.0πŸ€— HF Link πŸ“ƒComing Soon7.7892.91%77.6% 50.6 pass@1 Llama 2 License
WizardLM-13B-V1.2πŸ€— HF Link 7.0689.17%55.3%36.6 pass@1 Llama 2 License
WizardLM-13B-V1.1 πŸ€— HF Link 6.7686.32%25.0 pass@1Non-commercial
WizardLM-30B-V1.0πŸ€— HF Link7.0137.8 pass@1Non-commercial
WizardLM-13B-V1.0πŸ€— HF Link 6.3575.31% 24.0 pass@1 Non-commercial
WizardLM-7B-V1.0 πŸ€— HF Link πŸ“ƒ [WizardLM] 19.1 pass@1 Non-commercial
ModelCheckpointPaperHumanEvalMBPPDemoLicense
WizardCoder-Python-34B-V1.0πŸ€— HF LinkπŸ“ƒ [WizardCoder]73.261.2DemoLlama2
WizardCoder-15B-V1.0πŸ€— HF LinkπŸ“ƒ [WizardCoder]59.850.6--OpenRAIL-M
WizardCoder-Python-13B-V1.0πŸ€— HF LinkπŸ“ƒ [WizardCoder]64.055.6--Llama2
WizardCoder-Python-7B-V1.0πŸ€— HF LinkπŸ“ƒ [WizardCoder]55.551.6DemoLlama2
WizardCoder-3B-V1.0πŸ€— HF LinkπŸ“ƒ [WizardCoder]34.837.4--OpenRAIL-M
WizardCoder-1B-V1.0πŸ€— HF LinkπŸ“ƒ [WizardCoder]23.828.6--OpenRAIL-M

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}
}

Contributors

WizardLM

30 commits

haipeng1

8 commits

Ziyang

3 commits

WizardLMTeam/WizardMath-70B-V1.0

Model

125

stars

41

commits

1

repos using this model

1

linked in READMEs

Dec 20, 2023

updated

endpoints_compatible
llama
pytorch
text-generation
text-generation-inference
transformers
Browse cluster: Large Language Model Training & Inference β†’

README

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

🏠 Home Page

πŸ€— HF Repo β€’πŸ± Github Repo β€’ 🐦 Twitter

πŸ“ƒ [WizardLM] β€’ πŸ“ƒ [WizardCoder] β€’ πŸ“ƒ [WizardMath]

πŸ‘‹ Join our Discord

News

[12/19/2023] πŸ”₯ We released WizardMath-7B-V1.1 trained from Mistral-7B, the SOTA 7B math LLM, achieves 83.2 pass@1 on GSM8k, and 33.0 pass@1 on MATH.

[12/19/2023] πŸ”₯ WizardMath-7B-V1.1 outperforms ChatGPT 3.5, Gemini Pro, Mixtral MOE, and Claude Instant on GSM8K pass@1.

[12/19/2023] πŸ”₯ WizardMath-7B-V1.1 is comparable with ChatGPT 3.5, Gemini Pro, and surpasses Mixtral MOE on MATH pass@1.

ModelCheckpointPaperGSM8kMATH
WizardMath-7B-V1.1πŸ€— HF LinkπŸ“ƒ [WizardMath]83.233.0
WizardMath-70B-V1.0πŸ€— HF LinkπŸ“ƒ [WizardMath]81.622.7
WizardMath-13B-V1.0πŸ€— HF LinkπŸ“ƒ [WizardMath]63.914.0
WizardMath-7B-V1.0πŸ€— HF LinkπŸ“ƒ [WizardMath]54.910.7

[12/19/2023] Comparing WizardMath-7B-V1.1 with other open source 7B size math LLMs.

ModelGSM8k Pass@1MATH Pass@1
MPT-7B6.83.0
Llama 1-7B11.02.9
Llama 2-7B12.32.8
Yi-6b32.65.8
Mistral-7B37.89.1
Qwen-7b47.89.3
RFT-7B50.3--
MAmmoTH-7B (COT)50.510.4
WizardMath-7B-V1.054.910.7
Abel-7B-00159.713
MetaMath-7B66.519.8
Arithmo-Mistral-7B74.725.3
MetaMath-Mistral-7B77.728.2
Abel-7B-00280.429.5
WizardMath-7B-V1.183.233.0

[12/19/2023] Comparing WizardMath-7B-V1.1 with large open source (30B~70B) LLMs.

ModelGSM8k Pass@1MATH Pass@1
Llemma-34B51.525.0
Minerva-62B52.427.6
Llama 2-70B56.813.5
DeepSeek 67B63.4--
Gork 33B62.923.9
MAmmoTH-70B72.421.1
Yi-34B67.915.9
Mixtral 8x7B74.428.4
MetaMath-70B82.326.6
WizardMath-7B-V1.183.233.0

❗ Data Contamination Check:

Before model training, we carefully and rigorously checked all the training data, and used multiple deduplication methods to verify and prevent data leakage on GSM8k and MATH test set.

ModelCheckpointPaperMT-BenchAlpacaEvalGSM8kHumanEvalLicense
WizardLM-70B-V1.0πŸ€— HF Link πŸ“ƒComing Soon7.7892.91%77.6% 50.6 pass@1 Llama 2 License
WizardLM-13B-V1.2πŸ€— HF Link 7.0689.17%55.3%36.6 pass@1 Llama 2 License
WizardLM-13B-V1.1 πŸ€— HF Link 6.7686.32%25.0 pass@1Non-commercial
WizardLM-30B-V1.0πŸ€— HF Link7.0137.8 pass@1Non-commercial
WizardLM-13B-V1.0πŸ€— HF Link 6.3575.31% 24.0 pass@1 Non-commercial
WizardLM-7B-V1.0 πŸ€— HF Link πŸ“ƒ [WizardLM] 19.1 pass@1 Non-commercial
ModelCheckpointPaperHumanEvalMBPPDemoLicense
WizardCoder-Python-34B-V1.0πŸ€— HF LinkπŸ“ƒ [WizardCoder]73.261.2DemoLlama2
WizardCoder-15B-V1.0πŸ€— HF LinkπŸ“ƒ [WizardCoder]59.850.6--OpenRAIL-M
WizardCoder-Python-13B-V1.0πŸ€— HF LinkπŸ“ƒ [WizardCoder]64.055.6--Llama2
WizardCoder-Python-7B-V1.0πŸ€— HF LinkπŸ“ƒ [WizardCoder]55.551.6DemoLlama2
WizardCoder-3B-V1.0πŸ€— HF LinkπŸ“ƒ [WizardCoder]34.837.4--OpenRAIL-M
WizardCoder-1B-V1.0πŸ€— HF LinkπŸ“ƒ [WizardCoder]23.828.6--OpenRAIL-M

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}
}

Contributors

WizardLM

30 commits

haipeng1

8 commits

Ziyang

3 commits