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

I had an LLM create a playlist for me.

I’m tired of the bad playlists I get from algorithms, so I made a specific playlist with an Llama2 based on several songs I like. I started with 50, removed any I didn’t like, and added more to fill in the spaces. The small models were pretty good at this. Now I have a decent fixed playlist. It does get “tired” after a few weeks and I need to add more to it. I’ve never been able to do this myself with more than a dozen songs.

I have tired but chinese to english but it isn't good(none of them are), because for Chinese words meaning different depending on context so i am just stuck with large model but sometimes even they leave chinese text in translation(like google gemina 2),

I really hope there would be some amazing models this year for translation.

I built auto-summarization and grouping in an experimental branch of my hobby-retrospective tool: https://github.com/Sebazzz/Return/tree/experiment/ai-integra...

I’m now just wondering if there is any way to build tests on the input+output of the LLM :D

I bought a tiny business in Brazil, the database (Excel) I inherited with previous customer data *do not include gender*. I need gender to start my marketing campaigns and learn more about my future customer. I used Gemma-2B and Python to determine gender based on the data and it worked perfect

Apple’s on device models are around 3B if I’m nit mistaken, and they developed some nice tech around them that they published, if I’m not mistaken - where they have just one model, but have switchable finetunings of that model so that it can perform different functionalities depending on context.

I'm using ollama for parsing and categorizing scraped jobs for a local job board dashboard I check everyday.

Although there are better ways to test, I used a 3B model to speed up replies from my local AI server when testing out an application I was developing. Yes I could have mocked up HTTP replies etc., but in this case the small model let me just plug in and go.

Is there any experiments in a small models that does paraphrasing? I tried hsing some off-the-shelf models, but it didn't go well.

I was thinking of hooking them in RPGs with text-based dialogue, so that a character will say something slightly different every time you speak to them.

I'm using ollama, llama3.2 3b, and python to shorten news article titles to 10 words or less. I have a 3 column web site with a list of news articles in the middle column. Some of the titles are too long for this format, but the shorter titles appear OK.

I am building a private text editor that runs LLMs locally https://manzoni.app/

I'm interested in finding tiny models to create workflows stringing together several function/tools and running them on device using mcp.run servlets on Android (disclaimer: I work on that)

I am moderating a playlists manager to restrict them to a range of genders so it classifies song requests as accepted/rejected.

Many interesting projects, cool. I'm waiting to LLMs in games. That would make them much more fun. Any time now...

I'm working on using them for agentic voice commands of a limited scope.

My needs are narrow and limited but I want a bit of flexibility.

Pretty sure they are mostly used as fine tuning targets, rather than as-is.

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