Harnessing the power of Large Language Models locally with Ollama and LM studio

In the rapidly evolving landscape of artificial intelligence, Large Language Models (LLMs) have been powering everything from chatbots to content generation tools. As great as these capabilities are, their accessibility was often limited by the necessity of having substantial computation resources, typically available only through some cloud provider’s service. This opens a new horizon to democratize the use of LLMs on local systems which is being made possible with the advent of tools like Ollama and LM studio for developers, researchers, or hobbyists. This article discusses the implications, setup, and potential of running LLMs locally using Ollama and LM studio.

Why run LLMs locally?

The benefits of running LLMs locally are many.

• It enhances privacy and data security, as sensitive information does not need to be transmitted over the internet to a cloud service.
• It can significantly reduce latency, as the data processing occurs on the local machine without the need for internet connection.
• It offers potential cost savings in the long run, especially for heavy users of LLMs.

What is Ollama?