Qwen2-Math-1.5B#
README(From Huggingface)#
Qwen2-Math-1.5B#
[!Warning]
🚨 Temporarily this model mainly supports English. We will release bilingual (English & Chinese) models soon!
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 and GitHub repo.
Requirements#
transformers>=4.40.0for Qwen2-Math models. The latest version is recommended.
[!Warning]
🚨 This is a must because `transformers` integrated Qwen2 codes since `4.37.0`.
For requirements on GPU memory and the respective throughput, see similar results of Qwen2 here.
[!Important]
Qwen2-Math-1.5B-Instruct is an instruction model for chatting;
Qwen2-Math-1.5B 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#
README.md (2.2 KB)
config.json (671.0 B)
configuration.json (73.0 B)
generation_config.json (138.0 B)
merges.txt (1.6 MB)
model.safetensors (2.9 GB)
tokenizer.json (6.7 MB)
tokenizer_config.json (1.3 KB)
vocab.json (2.6 MB)