Ask HN: Is anyone doing anything cool with tiny language models?

https://gophersignal.com – I built GopherSignal!

It's a lightweight tool that summarizes Hacker News articles. For example, here’s what it outputs for this very post, "Ask HN: Is anyone doing anything cool with tiny language models?":

"A user inquires about the use of tiny language models for interesting applications, such as spam filtering and cookie notice detection. A developer shares their experience with using Ollama to respond to SMS spam with unique personas, like a millennial gymbro or a 19th-century British gentleman. Another user highlights the effectiveness of 3B and 7B language models for cookie notice detection, with decent performance achieved through prompt engineering."

I originally used LLaMA 3:Instruct for the backend, which performs much better, but recently started experimenting with the smaller LLaMA 3.2:1B model.

It’s been cool seeing other people’s ideas too. Curious—does anyone have suggestions for small models that are good for summaries?

Feel free to check it out or make changes: https://github.com/k-zehnder/gophersignal

That's cool, I really like it. One piece of feedback: I am usually more interested in the HN comments than in the original article. If you'd include a link to the comments then I might switch to GopherSignal as a replacement for the HN frontpage.

My flow is generally: Look at the title and the amount of upvotes to decide if I'm interested in the article. Then view the comments to see if there's interesting discussion going on or if there's already someone adding essential context. Only then I'll decide if I want to read the article or not.

Of course no big deal if you're not interested in my patronage, just wanted to let you know your page already looks good enough for me to consider switching my most visited page to it if it weren't for this small detail. And maybe the upvote count.

May be even rate each post on the comments activity level.