I have meant to do a proper write-up on the Ollama project for a while. Instead of putting it off any longer, I decided to publish my outline and notes, hoping that someone might find it helpful if you wanted to run your own local, offline LLM.

Why Ollama?

• Open-source LLM server
• Runs over two dozen models, with new ones released every week
• My personal favorite: Ollama

My Journey with Ollama

• Discovered Ollama a year ago
• One of the first accessible projects for M-series Mac
• User-friendly and performed well.

Ollama’s Growing Compatibility

• Expanded to support Windows and Linux
• Became AMD-friendly
• More accessible to users with various hardware setups

The Llama3 model changes everything

• Llama3 70b model introduction
• 70b model runs on Mac Studio with 64 GB of RAM
• Enables running a powerful LLM locally
• Benefits: privacy, customization, offline access

Making Life Easier with the LLM Python Project

• Installed llm-ollama plugin into LLM Python project
• Simplifies switching between different LLMs
• Quicker and easier testing of new models compared to Ollama’s CLI

Ollama’s Library and APIs

• ollama-python library for integrating Ollama models into Python projects
• Ollama’s built-in OpenAI compatible API for seamless use with existing OpenAI-based applications

Final Thoughts

• Ollama: a top choice for open-source, locally-run LLM
• Expanding compatibility
• Impressive Llama3 model
• Easy integration with LLM Python project
• Handy libraries and APIs
• Recommended for researchers, developers, and curious individuals