Alright, so I got this hair-brained idea the other week. I was out on this little course, nothing fancy, out in the sticks, you know? And my game was just… awful. And I kept thinking, wouldn’t it be neat to have a little helper, but without needing to be tethered to the internet? That’s where the “llama golf caddy nc” thing started cookin’ in my head. The “nc” for me was kinda like “no connection” needed, or maybe just “North Carolina” inspired, who knows, it just stuck.
Getting Started with the Bits and Pieces
First thing I did was grab a Llama model. Didn’t want anything too massive, my old rig wouldn’t handle it. Found a smaller one, I think it was a 7B parameter model, seemed like a good starting point. Getting that thing running locally, well, that took a bit of fiddling. Had to make sure all the Python stuff was in order, installed a couple of libraries I always forget the names of. You know how it is. My main goal here was to keep it all on my machine, no cloud stuff, just plain old local processing. That felt important for this little experiment.
Teaching a Llama About Golf Swings
Okay, so the Llama model is up and running. Now what? It doesn’t magically know about golf. I started by just throwing questions at it. “What club should I use for 150 yards?” Stuff like that. The initial answers were, uh, creative, let’s say. Sometimes it would tell me about llamas on a golf course. Not quite what I was aiming for.
So, I spent a good chunk of an afternoon, maybe even into the evening, just tweaking how I asked the questions. This is what they call “prompt engineering,” I guess. Sounds fancy, but it’s mostly just trying different ways to phrase things until the computer sort of gets what you’re after. I fed it some basic rules, like “if the distance is X and the wind is Y, suggest Z.” Super simple logic, nothing too complex.
Building the “Interface” – If You Can Call It That
Now, for interacting with this digital caddy. I didn’t build some flashy app. No way. Keeping with the “nc” spirit – no complications. I just used a simple command line. I’d type in my situation, like “130 yards, slight headwind, ball sitting up nicely,” and hit enter. Then I’d wait for the Llama to churn out a suggestion. It wasn’t pretty, just text on a screen, but it worked for what I needed. Sometimes it was slow, especially if I asked a tricky one.
So, Did It Actually Help My Golf Game?
Well, let’s be honest. It’s not about to win me any tournaments. But it was surprisingly… not terrible. After a lot of tweaking, it started giving some half-decent advice.
- It got pretty good at suggesting clubs for standard distances once I’d given it enough examples.
- Sometimes it would throw in a funny comment, which I guess is a side effect of how these Llama things work. Not always helpful, but amusing.
- Where it really struggled was with more nuanced stuff – like reading tricky greens or dealing with really weird lies. That kind of intuition is still very human, I reckon.
I remember one time I asked it about a shot from deep rough, and it suggested I might want to consider a “tactical layup to the fairway, or perhaps a moment of quiet reflection.” Smart aleck computer.
What I Reckon After All That Tinkering
This whole “llama golf caddy nc” project was more about the fun of building it and seeing if I could, rather than creating a perfect product. It was a good way to spend a weekend, getting my hands dirty with a local AI model. It’s pretty cool what you can do on your own machine these days without needing some giant company’s servers.
It definitely showed me how much these AI models are about the data you feed them and how you ask the questions. Garbage in, garbage out, as they say. But when you get it right, even with a simple setup, it’s kinda neat. Not sure I’ll take it out on the course for real, my playing partners would think I’ve finally lost it. But as a little project? Yeah, it was a good time. Learned a fair bit, mostly about my own patience.
