OpenMath-MATH-masked

# OpenMath GSM8K Masked

We release a *masked* version of the [MATH](https://github.com/hendrycks/math) solutions.
This data can be used to aid synthetic generation of additional solutions for MATH dataset
as it is much less likely to lead to inconsistent reasoning compared to using
the original solutions directly.

This dataset was used to construct [OpenMathInstruct-1](https://huggingface.co/datasets/nvidia/OpenMathInstruct-1):
a math instruction tuning dataset with 1.8M problem-solution pairs
generated using permissively licensed [Mixtral-8x7B](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1) model.

For details of how the masked solutions were created, see our [paper](https://arxiv.org/abs/2402.10176).

You can re-create this dataset or apply similar techniques to mask solutions for other datasets
by using our [open-sourced code](https://github.com/Kipok/NeMo-Skills).

## Citation

If you find our work useful, please consider citing us!

```bibtex
@article{toshniwal2024openmath,
title = {OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset},
author = {Shubham Toshniwal and Ivan Moshkov and Sean Narenthiran and Daria Gitman and Fei Jia and Igor Gitman},
year = {2024},
journal = {arXiv preprint arXiv: Arxiv-2402.10176}
}
```

## License

The use of this dataset is governed by the [NVIDIA License](LICENSE) which permits commercial usage.

# OpenMath GSM8K 掩码版

我们发布了[MATH](https://github.com/hendrycks/math)解题方案的**掩码版**。相较于直接使用原始解题方案，该数据集可辅助生成MATH数据集的额外合成解题方案，且更不易出现推理不一致的问题。

本数据集被用于构建[OpenMathInstruct-1](https://huggingface.co/datasets/nvidia/OpenMathInstruct-1)：这是一个包含180万道题解对的数学指令微调数据集，其生成过程使用了获得宽松许可的[Mixtral-8x7B](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1)模型。

若需了解掩码解题方案的具体生成细节，请参阅我们的[研究论文](https://arxiv.org/abs/2402.10176)。

你可通过我们的[开源代码库](https://github.com/Kipok/NeMo-Skills)复现本数据集，或使用类似技术为其他数据集的解题方案添加掩码。

## 引用

若您认为本工作对您有所帮助，请引用我们的成果！

bibtex
@article{toshniwal2024openmath,
title = {OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset},
author = {Shubham Toshniwal and Ivan Moshkov and Sean Narenthiran and Daria Gitman and Fei Jia and Igor Gitman},
year = {2024},
journal = {arXiv preprint arXiv: Arxiv-2402.10176}
}

## 许可证

本数据集的使用受[NVIDIA许可协议](LICENSE)约束，该协议允许商业使用。