Run an AI Large Language Model (LLM) at home on your GPU

Video Description

Download Docker Desktop: https://dockr.ly/46NkFOJ This video is sponsored by Docker. https://www.docker.com/ Large Language Models (LLMs) are a type of AI model that have proven to be extremely powerful and useful for a wide variety of tasks. They may be "large" in the sense that they use billions of parameters, but that doesn't mean you need to be a big company in order to run one. In fact, you can run some of the latest and greatest LLMs on your own machine, on your GPU, completely for free. We'll see how to do all that and more in this video using Docker Desktop! We'll even write an app to detect YouTube comment spam using an LLM. ― mCoding with James Murphy (https://mcoding.io) Docker: https://www.docker.com/ Ollama: https://ollama.com/ Ollama Docker image: https://hub.docker.com/r/ollama/ollama Ollama Python: https://github.com/ollama/ollama-python GPU compatibility: https://developer.nvidia.com/cuda-gpus Docker Tutorial Video: https://youtu.be/b0HMimUb4f0 Fast Pow algorithm Video: https://youtu.be/GrNJE6ogyQU YouTube Data API Video: https://youtu.be/0F9sdRtbwkE Source code: https://github.com/mCodingLLC/VideosSampleCode SUPPORT ME ⭐ --------------------------------------------------- Sign up on Patreon to get your donor role and early access to videos! https://patreon.com/mCoding Feeling generous but don't have a Patreon? Donate via PayPal! (No sign up needed.) https://www.paypal.com/donate/?hosted_button_id=VJY5SLZ8BJHEE Want to donate crypto? Check out the rest of my supported donations on my website! https://mcoding.io/donate Top patrons and donors: Laura M, Neel R, Dragos C, Jameson, Matt R, Pi, Vahnekie, Johan A, Mark M, Mutual Information BE ACTIVE IN MY COMMUNITY 😄 --------------------------------------------------- Discord: https://discord.gg/Ye9yJtZQuN Github: https://github.com/mCodingLLC/ Reddit: https://www.reddit.com/r/mCoding/ Facebook: https://www.facebook.com/james.mcoding CHAPTERS --------------------------------------------------- 0:00 Intro 0:56 Prerequisites 2:24 Running an model 4:33 Building an app 8:33 Containerizing the script