FinGPT (21,031 Stars) Financial LLM Guide 2026: Open Source Sentiment Analysis and Stock Insights

FinGPT (21,031 stars) is the leading open-source financial LLM family - fine-tuned on market news, filings and sentiment data. Here is how to run sentiment analysis on financial text locally.

💡 What You Will Learn

FinGPT (21,031 stars) is the leading open-source financial LLM family - fine-tuned on market news, filings and sentiment data. Here is how to run sentiment analysis on financial text locally.

## The short answer **AI4Finance-Foundation/FinGPT** (21,031 stars, Jupyter Notebook) is an open-source family of financial large language models. Unlike closed finance AIs, FinGPT models are fine-tuned on public market data - news headlines, earnings calls, SEC filings - and can be downloaded and run on your own hardware. ## What you can build - **Sentiment scoring**: classify news headlines as bullish/bearish/neutral - **Earnings-call Q&A**: ask questions about a company transcript - **Report summarization**: compress 10-K filings into key points - **Research automation**: combine with pandas for backtest studies ## Quick start with Hugging Face The easiest entry point is loading a fine-tuned model with Transformers (163,376 stars): ```python from transformers import pipeline pipe = pipeline("text-classification", model="FinGPT/fingpt-sentiment_llama2-13b") print(pipe("Apple beats earnings estimates on strong iPhone sales")) ``` For a smaller footprint, use the 7B variants or quantized checkpoints. Full fine-tuning recipes (LoRA) are in the repo finetune notebooks, and they run on a single 24 GB GPU. ## Real-world notes - Financial sentiment is domain-specific: generic sentiment models misread terms like risk or charge-off. FinGPT fine-tuning fixes that. - Always pair model output with fundamental data; models describe probability, not certainty. - Data pipelines in the repo give you reproducible backtest baselines. ## FAQ **Is it free?** The models are open weights (many under Apache-2.0/MIT-style licenses for research). **Can I fine-tune my own?** Yes - the repo provides LoRA fine-tuning notebooks that work on consumer GPUs. **Is this investment advice?** No - it is a research tool. Always do your own due diligence.