My first experiment running AI locally using Ollama, Python, and Hugging Face
Running AI Locally: My First Experiment As part of my journey to understand Artificial Intelligence and Large Language Models , I wanted to go beyond simply using cloud-based AI tools. Instead, I decided to try something more hands-on: Running an AI model locally on my own machine. Running AI locally offers several advantages: More control over the models Better privacy No dependency on external APIs Ability to experiment freely Deeper understanding of how AI systems actually work This post summarizes the tools I used and the steps I followed to run AI locally. Tools and Technologies Used To set up a local AI environment, I used the following tools. 1. WSL (Windows Subsystem for Linux) Since I was working on Windows , I first installed WSL . WSL allows you to run a Linux environment inside Windows , which is extremely useful because most AI tools are designed to run on Linux systems. Benefits include: Linux development environment Better compatibility with AI frameworks Easier in...