---
title: Qwen2-Math-72B
canonical_url: "https://www.modelscope.cn/models/Qwen/Qwen2-Math-72B"
md_url: "https://www.modelscope.cn/models/Qwen/Qwen2-Math-72B.md"
repository: Qwen/Qwen2-Math-72B
chinese_name: "千问2-数学-72B"
last_updated: 2024-08-13
license: other
pipeline_tag: text-generation
tasks:
  - text-generation
model_type:
  - qwen2
architectures:
  - Qwen2ForCausalLM
parameters: 72.7B
tensor_type:
  - BF16
library_name:
  - safetensors
  - pytorch
frameworks:
  - pytorch
language:
  - en
inference_backends:
  - "deploy_task text/emb"
  - "lmdeploy 0.9.1"
  - "lmdeploy_turbomind 0.9.1"
  - "sglang 0.5.2"
  - "vllm 0.9.2"
downloads: 2647
stars: 4
tags:
  - chat
---

# Qwen2-Math-72B

> Qwen2-Math-72B - Qwen 在 ModelScope 开源的模型。Qwen2-Math 是一系列基于 Qwen2 LLM 构建的专门用于数学解题的语言模型，其数学能力显著超越了开源模型，甚至超过了闭源模型（如 GPT-4o）。我们希望Qwen2-Math能够为科学界解决需要复杂多步逻辑推理的高级数学问题做出贡献。

Qwen/Qwen2-Math-72B 是 ModelScope 魔搭社区上的 72.7B 参数text-generation模型，采用 other 许可，可用 deploy_task text/emb、lmdeploy 0.9.1、lmdeploy_turbomind 0.9.1 部署。

- **Repository**: Qwen/Qwen2-Math-72B
- **License**: other
- **Tasks**: text-generation
- **Parameters**: 72.7B
- **Inference backends**: deploy_task text/emb, lmdeploy 0.9.1, lmdeploy_turbomind 0.9.1, sglang 0.5.2, vllm 0.9.2
- **Tags**: chat
- **Downloads**: 2647
- **Stars**: 4
- **Last updated**: 2024-08-13

Source: https://www.modelscope.cn/models/Qwen/Qwen2-Math-72B

---

# Qwen2-Math-72B

> [!Warning]
> <div align="center">
> <b>
> 🚨 Temporarily this model mainly supports English. We will release bilingual (English & Chinese) models soon!
> </b>
> </div>

## Introduction

Over the past year, we have dedicated significant effort to researching and enhancing the reasoning capabilities of large language models, with a particular focus on their ability to solve arithmetic and mathematical problems. Today, we are delighted to introduce a serise of math-specific large language models of our Qwen2 series,  Qwen2-Math and Qwen2-Math-Instruct-1.5B/7B/72B. Qwen2-Math is a series of specialized math language models built upon the Qwen2 LLMs, which significantly outperforms the mathematical capabilities of open-source models and even closed-source models (e.g., GPT4o). We hope that Qwen2-Math can contribute to the scientific community for solving advanced mathematical problems that require complex, multi-step logical reasoning.


## Model Details


For more details, please refer to our [blog post](https://qwenlm.github.io/blog/qwen2-math/) and [GitHub repo](https://github.com/QwenLM/Qwen2-Math).


## Requirements
* `transformers>=4.40.0` for Qwen2-Math models. The latest version is recommended.

> [!Warning]
> <div align="center">
> <b>
> 🚨 This is a must because `transformers` integrated Qwen2 codes since `4.37.0`.
> </b>
> </div>

For requirements on GPU memory and the respective throughput, see similar results of Qwen2 [here](https://qwen.readthedocs.io/en/latest/benchmark/speed_benchmark.html).

> [!Important]
>
> **Qwen2-Math-72B-Instruct** is an instruction model for chatting;
>
> **Qwen2-Math-72B** is a base model typically used for completion and few-shot inference, serving as a better starting point for fine-tuning.
> 

## Citation

If you find our work helpful, feel free to give us a citation.

```
@article{yang2024qwen2,
  title={Qwen2 technical report},
  author={Yang, An and Yang, Baosong and Hui, Binyuan and Zheng, Bo and Yu, Bowen and Zhou, Chang and Li, Chengpeng and Li, Chengyuan and Liu, Dayiheng and Huang, Fei and others},
  journal={arXiv preprint arXiv:2407.10671},
  year={2024}
}
```