FinGPT: Open-Source Financial Large Language Models

Let us not expect Wall Street to open-source LLMs or open APIs, due to FinTech institutes' internal regulations and policies.

Blueprint of FinGPT

https://huggingface.co/FinGPT

Project Contributors

FinGPT is an open-source financial large language model project developed and maintained by the AI4Finance Foundation.

Key contributors include:

• Hongyang (Bruce) Yang – research and development on financial large language models and related applications
• [other contributors…]

What's New:

• [Model Release] Nov, 2023: We release FinGPT-Forecaster! 🔥Demo, Medium Blog & Model are available on Huggingface🤗!
• [Paper Acceptance] Oct, 2023: "FinGPT: Instruction Tuning Benchmark for Open-Source Large Language Models in Financial Datasets" is accepted🎉 by Instruction Workshop @ NeurIPS 2023
• [Paper Acceptance] Oct, 2023: "FinGPT: Democratizing Internet-scale Data for Financial Large Language Models" is accepted🎉 by Instruction Workshop @ NeurIPS 2023
• [Model Release] Oct, 2023: We release the financial multi-task LLMs 🔥 produced when evaluating base-LLMs on FinGPT-Benchmark
• [Paper Acceptance] Sep, 2023: "Enhancing Financial Sentiment Analysis via Retrieval Augmented Large Language Models" is accepted🎉 by ACM International Conference on AI in Finance (ICAIF-23)
• [Model Release] Aug, 2023: We release the financial sentiment analysis model 🔥
• [Paper Acceptance] Jul, 2023: "Instruct-FinGPT: Financial Sentiment Analysis by Instruction Tuning of General-Purpose Large Language Models" is accepted🎉 by FinLLM 2023@IJCAI 2023
• [Paper Acceptance] Jul, 2023: "FinGPT: Open-Source Financial Large Language Models" is accepted🎉 by FinLLM 2023@IJCAI 2023
• [Medium Blog] Jun 2023: FinGPT: Powering the Future of Finance with 20 Cutting-Edge Applications

Why FinGPT?

1). Finance is highly dynamic. BloombergGPT trained an LLM using a mixture of finance data and general-purpose data, which took about 53 days, at a cost of around $3M). It is costly to retrain an LLM model like BloombergGPT every month or every week, thus lightweight adaptation is highly favorable. FinGPT can be fine-tuned swiftly to incorporate new data (the cost falls significantly, less than $300 per fine-tuning).

2). Democratizing Internet-scale financial data is critical, say allowing timely updates of the model (monthly or weekly updates) using an automatic data curation pipeline. BloombergGPT has privileg