Chain-of-Thought Hub

Overview

Chain-of-Thought Hub is a community-maintained benchmarking framework for evaluating large language models on complex reasoning tasks using chain-of-thought prompting. It provides datasets, prompts, and evaluation scripts in Jupyter Notebook format to measure and compare model performance.

Best for

Best for
Researchers and developers evaluating LLM reasoning capabilities with chain-of-thought prompting

Use cases

• Benchmark LLM reasoning abilities with chain-of-thought prompts
• Compare multiple models on standardized reasoning tasks
• Reproduce and extend research on chain-of-thought prompting

Notes

Chain-of-Thought Hub is a community-maintained benchmarking framework for evaluating large language models on complex reasoning tasks using chain-of-thought prompting. It provides datasets, prompts, and evaluation scripts in Jupyter Notebook format to measure and compare model performance.

2,773 stars on GitHub. Last updated 2024-08-04. Licensed MIT.

Use cases

• Benchmark LLM reasoning abilities with chain-of-thought prompts
• Compare multiple models on standardized reasoning tasks
• Reproduce and extend research on chain-of-thought prompting

Pros

• Open source with a focused, well-defined scope
• Community-driven with active development and 2,773 stars
• Provides ready-to-use datasets and evaluation code

Cons

• Jupyter Notebook format limits production deployment
• Primarily a benchmarking tool, not a runtime or inference framework
• Requires manual setup and model API keys or local models

Indexed from awesome-llm and enriched against its public facts.