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llm-benchmarks

Go straight to the simple math benchmark ^_^

Introduction

Welcome to the llm-benchmarks repository! This repository is dedicated to providing benchmarks for large language models (LLMs), with a focus on mathematical capabilities. These benchmarks are designed to assess the performance and accuracy of LLMs in handling various mathematical problems, from simple arithmetic to complex equations.

Why Simple Math Benchmarks?

  1. Foundation for Complexity: Simple mathematical benchmarks provide a baseline for understanding how well an LLM can handle basic arithmetic operations, which are fundamental to more complex mathematical and scientific tasks.

  2. Performance Metrics: They offer clear metrics for performance evaluation, such as speed, accuracy, and computational efficiency, which are crucial for optimizing algorithms.

  3. Debugging and Improvement: Identifying weaknesses in basic operations through these benchmarks can guide further improvements in model architecture and training processes.

  4. Comparison Across Models: Simple benchmarks allow for straightforward comparisons between different models, helping users select the right model for their specific needs based on empirical data.

  5. Educational Tool: They serve as an excellent educational tool for new users who are learning about LLMs and their applications in computational mathematics.

How to Contribute

We welcome contributions to the llm-benchmarks repository! If you have ideas for new benchmarks or improvements to existing ones, please follow these steps:

  1. Fork the Repository: Make a copy of this repository under your GitHub account.

  2. Make Your Changes: Add new benchmarks or enhance existing ones.

  3. Submit a Pull Request: Once you're happy with your changes, submit a pull request to the main repository for review.

License

This project is licensed under the MIT License - see the LICENSE file for details.

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benchmarking large language models (LLMs) with a focus on their mathematical capabilities

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