Jeff Triplett

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

Originally posted on: https://micro.webology.dev/2024/06/11/exploring-ollama-an.html