Tutorials for Open FinLLM Leaderboard (OFLL): Evaluation and Benchmarking Suite for FinAI Readiness and Governance

We provide tutorials for the Open Financial Large Language Models (FinLLM) Leaderboard - an open platform for evaluating and advancing capabilities of Financial LLMs and agents.

📖 Documentation

Access at link: https://finllm-leaderboard.readthedocs.io/en/latest/

🚀 Features

• Standardized Evaluation: Multi-dimensional assessment framework for financial AI systems
• Continuous Benchmarking: Real-time tracking of model performance
• Open Collaboration: Community-driven improvements and contributions
• Practical Use Cases: Demonstrated applications in legal, regulatory, and financial analysis

📚 Highlights

Core Components

• Introduction: Project vision and ecosystem overview
• Key Features: Technical capabilities and differentiation
• Motivation: Financial AI challenges and opportunities

Implementation Guide

• Setup Instructions:
  • CUDA environment configuration
  • API key management
• Benchmarking Tutorials:
  • Local models (e.g., LLama3.1)
  • API-based models (e.g., ChatGPT)

Use Cases and Applications

• Simple Questions: Definitions and financial event analysis
• Efficient Legal Consultation: LLM-assisted legal prep workflows
• Financial Document Analysis: Professional-grade report processing
• Regulatory Compliance: AI-driven capital markets solutions

🔗 Links

• Leaderboard on HuggingFace: Hugging Face Space
• Codebase: GitHub Repository
• Search Agent: FinGPT-Search-Agent

🤝 How to Contribute

We welcome contributions through:

1. New financial question sets and datasets 📊
2. Model submissions 🧠
3. Task proposals 💡
4. Documentation improvements 📝

See our Contribution Guide for details.

📜 Citation

@inproceedings{lin2024open,
  title={Open FinLLM Leaderboard: Towards Financial AI Readiness},
  author={Lin, Shengyuan Colin and Tian, Felix and Wang, Keyi and Zhao, Xingjian and Huang, Jimin and Xie, Qianqian and Borella, Luca and White, Matt and Wang, Christina Dan and Xiao, Kairong and Liu, Xiao-Yang and Deng, Li},
  booktitle={International Workshop on Multimodal Financial Foundation Models (MFFMs) at 5th ACM International Conference on AI in Finance},
  year={2024}
}