Creating a Personal Assistant with LLaMA 3.2

One of the most immediately usable applications of AI has to be the chatbot. Though they have been around in some capacity for 30 years, the last two have seen the true rise of these personal assistants chat interfaces. They have percolated out from high technical circles into all walks of life, social situations, and business use cases.

While they are available and easy to use, many of the best chatbots are locked behind walled gardens of closed source technology. These environments come with their own advantages, like internet search connectivity, custom profiles to interact with the agents, and access to some of the best Large Language Models (LLMs) available. However, the open-source community has always been in step with these developments, and open-source tools come with their own advantages, namely customization, fine-tuning, and complex integrations with other technologies.

In this article, we are going to take a look at one of the latest and greatest open-source model suites: LLaMA 3.2. These 11b parameter, vision enabled models boast comparable performance to GPT-4o mini and Claude 3 - Haiku across a wide variety of vision-instruction tuned benchmarks at significantly lower cost. Additionally, their lightweight 2b parameter models offer comparable performance to SOTA edge models like PHI mini it and Gemma 2b. We will begin this tutorial with a breakdown of what makes these models special. Afterwards, we will show how to take this powerful open-source model, and create a personal assistant chatbot. This personal assistant can help with anything from writing to coding to translation, and is fully enabled to work with image data as easily as text.

Follow along with us to get a deeper dive into the advantages of using these incredible models on DigitalOcean GPU Droplets with our guide to running an powerful assistant application, adapted from HuggingFace Projects staffer merve’s original project.