Hello everyone, I am Weixue AI. Today, I will introduce to you Deep Learning Practice 42-Introduction to the principle of developing MathGPT based on large models, making it possible to intelligently answer mathematical problems. After the release of ChatGPT last year, various large language models at home and abroad have emerged one after another, but everyone knows that the current models are criticized for their lack of mathematical ability. Even simple math problems may be wrong. Today I will introduce it to you. MathGPT's model is used to solve GPT to solve mathematical problems. It can solve simple junior high school mathematics and high school mathematics, so that accurate answers to mathematical questions can be realized.
Article directory structure:
Introduction
1.1 Background and Significance
1.2 Research Purpose
1.3 Overview of Paper Structure
Introduction to MathGPT model
2.1 Model overview
2.2 Model training data set
2.3 Model architecture
2.4 Model pre-training and fine-tuning methods
2.5 Mathematical problem representation
Application of MathGPT in Mathematical Problem Solving
3.1 Mathematical Problem Solving Process
3.2 Data Preprocessing
3.3 Mathematical Problem Representation Conversion
3.4 Implementation Code Overview
Discussion and Prospect
4.1 Model Limitation and Improvement Direction
4.2 Algorithm Application Scenario Expansion
4.3 Future Development Trend
Conclusion
5.1 Research summary
5.2 The importance and application prospect of MathGPT model
preface
1.1 Background and significance
In the past six months, the rapid development and wide application of artificial intelligence technology have had a profound impact on various fields, especially after the release of ChatGPT, various large language models at home and abroad have been released one after another, and applications based on ChatGPT have already been released. There are hundreds of them. Mathematics as a scientific research and practical application