Introduction to Ollama Ft. Sarin Suriyakoon

This video is about introducing Ollama, a library for running large language models (LLMs) locally on your device.
The speaker, Paco from PALO IT, a tech enthusiast, is sharing his knowledge on LLMs and LM engines. He explains the benefits of running LLMs locally and why someone might choose to do so over using cloud-based services. Here are the key points covered in the video.
Benefits of running LLMs locally:
Improves developer learning curve by allowing experimentation on your own machine without any cost.
Enhances prompt writing skills because local LLMs are not as sophisticated as mainstream models, requiring more precise prompts.
What is Ollama?
Ollama is a rapper for LLM in C++. It enables running LLMs on CPUs or local laptops by converting them into a format compatible with CPUs.
Ollama improves developer experience by allowing them to run LM APIs directly. This means you can leverage large language models through R APIs, making them usable in various environments like Docker and Kubernetes. Ollama can also be called through Node.js, Python, etc.
Additional benefits of Ollama:
Supports multimodal models, meaning it can handle different input formats like text and image.
Integrates with other tools and libraries, making it a versatile solution.