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metadata
license: apache-2.0
datasets:
  - dyyyyyyyy/ScaleQuest-Math
language:
  - en
metrics:
  - accuracy
library_name: transformers
pipeline_tag: text-generation

Unleashing Reasoning Capability of LLMs via Scalable Question Synthesis from Scratch

Model Card for Qwen2-Math-7B-ScaleQuest

We introduce ScaleQuest, a scalable and novel data synthesis method that utilizes small-size open-source models to generate questions from scratch without the need for seed data with complex augmentation constraints.

Datasets & Models

Math Dataset: link

We release two question generator models and four problem-solving models.

Model Type MATH Olympiad Bench πŸ€— HuggingFace
Download Link
ScaleQuest-DeepSeekMath-7B-QGen question generator - - link
ScaleQuest-Qwen2-Math-7B-QGen question generator - - link
Mistral-7B-ScaleQuest problem solver 62.9 26.8 link
Llama3-8B-ScaleQuest problem solver 64.4 25.3 link
DeepSeekMath-7B-ScaleQuest problem solver 66.6 29.9 link
Qwen2-Math-7B-ScaleQuest problem solver 73.4 38.5 link

Demo usage

Below is an example using Qwen2-Math-7B-ScaleQuest


Citation

@article{ding2024unleashing,
    title={Unleashing Reasoning Capability of LLMs via Scalable Question Synthesis from Scratch}, 
    author={Ding, Yuyang and Shi, Xinyu and Liang, Xiaobo and Li, Juntao and Zhu, Qiaoming and Zhang, Min},
    journal={https://arxiv.org/abs/2410.18693}, 
    year={2024}
}