Mathematical Reasoning Performance Enhancement Program
The following methods are recommended for math problem solving scenarios:
- Forced activation of the thinking mode: Settings
enable_thinking=TrueActivate step-by-step reasoning capability, where the model displays the computational process instead of outputting the results directly - Structured input: Organize questions using Markdown formatting, such as
```problemn求解∫(x^2+3x)dx从0到1n``` - parameterization: Appropriate increase
num_beams=5Conduct beam searches to reducetemperature=0.3Reducing randomness
Enhancement Program:
- Combined with the Wolfram Alpha API, the mathematical expressions output from the model are validated for computation
- Mix of GSM8K and MATH datasets for fine-tuning (~100,000 samples of math problems required)
- For engineering calculations, it is recommended to output the results in Python code format for easy verification of execution
Typical error handling: when there is a deviation in the calculation of theprompt="请逐步检查以下推导过程：[粘贴错误答案]"Make the model self-correcting
This answer comes from the articleQwen3-8B-BitNet: an open source language model for efficient compressionThe
May not be reproduced without permission:AI productivity tools " How to optimize the accuracy of complex mathematical reasoning in Qwen3-8B-BitNet?
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