An open-source framework for financial large language models, enabling cost-effective fine-tuning for tasks like sentiment analysis and forecasting.
FinGPT is an open-source framework and collection of large language models specifically fine-tuned for financial applications. It solves the problem of high cost and inaccessibility of proprietary financial LLMs by providing a data-centric, lightweight adaptation pipeline that allows developers and researchers to efficiently create models for tasks like sentiment analysis, forecasting, and financial Q&A.
Financial data scientists, AI researchers in fintech, quantitative analysts, and developers building financial NLP applications who need cost-effective, adaptable, and state-of-the-art language models.
Developers choose FinGPT because it offers a transparent, open-source alternative to closed models like BloombergGPT, with significantly lower fine-tuning costs (under $300), support for multiple base LLMs, and a full-stack framework that simplifies building and deploying financial AI solutions.
FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
Leverages LoRA to adapt base LLMs for under $300, compared to millions for full retraining, as highlighted in benchmarks against BloombergGPT's $3M cost.
FinGPT v3.3 outperforms GPT-4 and ChatGPT in financial sentiment benchmarks, achieving weighted F1 scores up to 0.882 on datasets like FPB and TFNS.
Offers pre-trained models for various tasks including sentiment analysis, relation extraction, and named entity recognition, all available on Hugging Face for easy access.
Uses an automatic data curation pipeline to ensure models can be updated with timely financial information, democratizing access without proprietary dependencies.
The full-stack framework involves five layers from data sourcing to applications, requiring significant expertise in NLP, financial data engineering, and GPU management.
Performance and capabilities vary based on the chosen base LLM (e.g., Llama2, Falcon), which users must source, fine-tune, and maintain, adding complexity.
Optimized for batch processing and periodic fine-tuning rather than ultra-low-latency applications, making it less suitable for instant decision-making systems.
FinGPT is an open-source alternative to the following products: