This project demonstrates using local Large Language Models (LLMs) for financial data analysis, specifically for automatically categorizing bank transactions. It targets individuals seeking to leverage LLMs for personal finance management and data labeling tasks.

How It Works

The project utilizes Llama2, a local LLM, to process and categorize bank transaction data. The core approach involves setting up and running LLMs locally via Ollama, then feeding transaction data to the model for automated labeling. This method offers privacy and control over sensitive financial information.

Quick Start & Requirements

• Install Ollama: https://ollama.ai/
• Supported OS: macOS and Linux
• Tutorial video: https://www.youtube.com/watch?v=h_GTxRFYETY

Highlighted Details

• Explores practical application of local LLMs for data labeling.
• Focuses on categorizing personal bank transactions.
• Leverages Llama2 model for analysis.

Maintenance & Community

No specific community channels or maintenance details are provided in the README.

Licensing & Compatibility

The README does not specify a license.

Limitations & Caveats

The project is presented as a personal exploration and may not be production-ready. Ollama currently supports only macOS and Linux. The example data is fictitious.