Qwen2.5-Math-72B#
README(From Huggingface)#
Qwen2.5-Math-72B#
[!Warning]
🚨 Qwen2.5-Math mainly supports solving English and Chinese math problems through CoT and TIR. We do not recommend using this series of models for other tasks.
Introduction#
In August 2024, we released the first series of mathematical LLMs - Qwen2-Math - of our Qwen family. A month later, we have upgraded it and open-sourced Qwen2.5-Math series, including base models Qwen2.5-Math-1.5B/7B/72B, instruction-tuned models Qwen2.5-Math-1.5B/7B/72B-Instruct, and mathematical reward model Qwen2.5-Math-RM-72B.
Unlike Qwen2-Math series which only supports using Chain-of-Thught (CoT) to solve English math problems, Qwen2.5-Math series is expanded to support using both CoT and Tool-integrated Reasoning (TIR) to solve math problems in both Chinese and English. The Qwen2.5-Math series models have achieved significant performance improvements compared to the Qwen2-Math series models on the Chinese and English mathematics benchmarks with CoT.

While CoT plays a vital role in enhancing the reasoning capabilities of LLMs, it faces challenges in achieving computational accuracy and handling complex mathematical or algorithmic reasoning tasks, such as finding the roots of a quadratic equation or computing the eigenvalues of a matrix. TIR can further improve the model's proficiency in precise computation, symbolic manipulation, and algorithmic manipulation. Qwen2.5-Math-1.5B/7B/72B-Instruct achieve 79.7, 85.3, and 87.8 respectively on the MATH benchmark using TIR.
Model Details#
For more details, please refer to our blog post and GitHub repo.
Requirements#
transformers>=4.37.0for Qwen2.5-Math models. The latest version is recommended.
[!Warning]
🚨 This is a must becausetransformersintegrated Qwen2 codes since4.37.0.
For requirements on GPU memory and the respective throughput, see similar results of Qwen2 here.
Quick Start#
[!Important]
Qwen2.5-Math-72B-Instruct is an instruction model for chatting;
Qwen2.5-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}
}
Model Files#
LICENSE (6.8 KB)
README.md (3.2 KB)
config.json (672.0 B)
configuration.json (2.0 B)
generation_config.json (138.0 B)
merges.txt (1.6 MB)
model-00001-of-00037.safetensors (3.5 GB)
model-00002-of-00037.safetensors (3.7 GB)
model-00003-of-00037.safetensors (3.6 GB)
model-00004-of-00037.safetensors (3.7 GB)
model-00005-of-00037.safetensors (3.7 GB)
model-00006-of-00037.safetensors (3.7 GB)
model-00007-of-00037.safetensors (3.6 GB)
model-00008-of-00037.safetensors (3.7 GB)
model-00009-of-00037.safetensors (3.7 GB)
model-00010-of-00037.safetensors (3.7 GB)
model-00011-of-00037.safetensors (3.6 GB)
model-00012-of-00037.safetensors (3.7 GB)
model-00013-of-00037.safetensors (3.7 GB)
model-00014-of-00037.safetensors (3.7 GB)
model-00015-of-00037.safetensors (3.6 GB)
model-00016-of-00037.safetensors (3.7 GB)
model-00017-of-00037.safetensors (3.7 GB)
model-00018-of-00037.safetensors (3.7 GB)
model-00019-of-00037.safetensors (3.6 GB)
model-00020-of-00037.safetensors (3.7 GB)
model-00021-of-00037.safetensors (3.7 GB)
model-00022-of-00037.safetensors (3.7 GB)
model-00023-of-00037.safetensors (3.6 GB)
model-00024-of-00037.safetensors (3.7 GB)
model-00025-of-00037.safetensors (3.7 GB)
model-00026-of-00037.safetensors (3.7 GB)
model-00027-of-00037.safetensors (3.6 GB)
model-00028-of-00037.safetensors (3.7 GB)
model-00029-of-00037.safetensors (3.7 GB)
model-00030-of-00037.safetensors (3.7 GB)
model-00031-of-00037.safetensors (3.6 GB)
model-00032-of-00037.safetensors (3.7 GB)
model-00033-of-00037.safetensors (3.7 GB)
model-00034-of-00037.safetensors (3.7 GB)
model-00035-of-00037.safetensors (3.6 GB)
model-00036-of-00037.safetensors (3.7 GB)
model-00037-of-00037.safetensors (3.2 GB)
model.safetensors.index.json (77.2 KB)
tokenizer.json (6.7 MB)
tokenizer_config.json (7.1 KB)
vocab.json (2.6 MB)