Setting Up WSL2 to Run Local Language Models for Trading Systems
Summary
This article walks through configuring Windows Subsystem for Linux 2 on Windows to run a local large language model. It covers installation choices, starting and managing Linux distributions, moving a distribution to another drive, and setting memory and swap limits. It then describes configuring a Linux environment for model inference with llama.cpp and gives a small example of loading a model and generating text.
The material is infrastructure guidance for developers exploring local models in algorithmic trading workflows; it does not describe a trading signal, strategy, or performance evaluation. The setup is specific to Windows with WSL2, and commands and requirements may vary with Windows versions, hardware, model size, and software updates. The inference example demonstrates basic operation, not integration with an Expert Advisor or trading validation.
Key ideas
- WSL2 provides a Linux environment within Windows for local model workloads.
- The guide covers distribution installation, storage migration, and memory and swap configuration.
- It demonstrates basic local inference with llama.cpp and a downloaded model.
- The article does not evaluate trading performance or show an Expert Advisor integration.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.