Where politicians fear to tread…

A nation weeps, a mother cries,
Tiny hands clutch at crimson skies.
“Just keep them safe,” they whisper low,
But hollow words, the truth don’t show.

In halls of power, shadows dance,
While children tremble, afraid to glance.
Gutless men, in ivory towers,
Bow to pressure, silencing powers.

They cater to a lobby’s plea,
For profits made and safety fee.
Blind eye they turn on innocent lives,
Clandestine deals beneath the tides.

The echo of their promises rings hollow,
A symphony of fear in every poll.
While school halls become battlegrounds rife,
And innocence fades into the knife.

How can they stand and claim “common sense,”
When lives are lost in this gun-fueled trance?
Their cowardice a bitter pill to swallow,
As innocence bleeds on the playground’s hollow.

They preach of freedom, but at what cost?
While children pay for their moral frost.
Rise from slumber, break the chains of fear,
Stand for justice, let the truth be clear!

Poem from Gemma2 Large Language Model from a writing prompt. “Write a poem about the plight of gutless politicians craven to the gun lobby while children lives are endangered in America’s classrooms.”

Harnessing the Power of Local AI: Exploring Ollama and Llama 3.1 for Advanced Language Modeling

Just yesterday, I came across Ollama, an open-source project developed by Meta. I had been helping a friend learn more about locally hosted large language models, and my internet search led me to Ollama. I installed it quickly on my Linux Mint desktop using the code supplied on the community website.

curl -fsSL https://ollama.com/install.sh | sh

It didn’t take too long to install the software and then I wanted to explore how it worked. I decided to download and install the recommended Llama3.1 model. I followed the instructions and in the terminal entered the following command:

$ ollama run llama3.1

The model began to install, which took a couple of minutes. This could vary depending on your CPU and internet connection. I have an Intel i7 with 64 GB RAM and a robust internet connection. Once the model was downloaded, I was presented with a prompt to ‘talk’ with the LLM.

>>> What is the history of St. Bonaventure University? 

“St. Bonaventure University, a private Franciscan university located in Allegany County, New York, has a rich and storied history that spans over
160 years.”

It’s not bad, but it’s not entirely accurate either. The results were rendered in MarkDown, which is a real plus. I also knew that having a GPU would render the results much quicker. I wanted to install Ollama on my M2 MacBook Air.

I followed the much easier directions: Download the Ollama-darwin.zip, unzip the archive, and double-click on the Ollama icon. The program is installed in the MacBook’s Application folder. When the program is launched, it directs me to the Mac Terminal app, where I can enter the same commands I had entered on my Linux computer.

I ran the same commands on the Mac to install Llama3.1 the first time. I asked for the history of St. Bonaventure University in Olean, New York. The results appeared much more quickly, but their accuracy was skewed even more. They were so inaccurate that they were comical.

“The institution was founded in 1858 by five Jesuit priests from the Buffalo Diocese as St. Bonaventure College. The college was established on a 200-acre farm in Deerpark, New York, with the goal of providing a Catholic education to young men.”

I downloaded and installed the Gemma 2 model from Google to see if it was faster and more accurate. The commands are the same whether using the Linux or Mac terminal.

$ ollama run gemma2:2b

Gemma 2:2b is the smallest model, at 1.6 GB, and it was downloaded and installed quickly. The results were similarly inaccurate, but they rendered much more quickly on both the Mac and Linux computers. Llama3.1 was only mildly accurate for information that occurred in 2021 and prior. I asked Gemma2 who was running for President of the United States and its information was only accurate as of October 26, 2023.

Despite the results, I am encouraged that it is possible to run large language models on PCs.