this post was submitted on 16 Jun 2025
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I've tried coding and every one I've tried fails unless really, really basic small functions like what you learn as a newbie compared to say 4o mini that can spit out more sensible stuff that works.

I've tried explanations and they just regurgitate sentences that can be irrelevant, wrong, or get stuck in a loop.

So. what can I actually use a small LLM for? Which ones? I ask because I have an old laptop and the GPU can't really handle anything above 4B in a timely manner. 8B is about 1 t/s!

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[–] CrayonDevourer@lemmy.world 4 points 2 days ago* (last edited 2 days ago) (26 children)

Currently I've been using a local AI (a couple different kinds) to first - take the audio from a Twitch stream; so that I have context about the conversation, convert it to text, and then use a second AI; an LLM fed the first AIs translation + twitch chat and store 'facts' about specific users so that they can be referenced quickly for a streamer who has ADHD in order to be more personable.

That way, the guy can ask User X how their mothers surgery went. Or he can remember that User K has a birthday coming up. Or remember that User G's son just got a PS5 for Christmas, and wants a specific game.

It allows him to be more personable because he has issues remembering details about his users. It's still kind of a big alpha test at the moment, because we don't know the best way to display the 'data', but it functions as an aid.

[–] catty@lemmy.world 1 points 2 days ago (1 children)

Surely none of that uses a small LLM <= 3B?

[–] CrayonDevourer@lemmy.world 1 points 2 days ago* (last edited 2 days ago) (3 children)

Yes. The small LLM isn't retrieving data, it's just understanding context of text enough to know what "Facts" need to be written to a file. I'm using the publicly released Deepseek models from a couple of months ago.

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[–] Hadowenkiroast@piefed.social 1 points 2 days ago (1 children)

sounds like salesforce for a twitch setting. cool use case, must make fun moments when he mentions such things.

[–] jlow@discuss.tchncs.de 4 points 2 days ago (1 children)

Esp. if the LLM just hallucinates 50% of the "facts" a about the users 👌

[–] CrayonDevourer@lemmy.world 3 points 2 days ago* (last edited 2 days ago)

That hasn't been a problem at all for the 200+ users it's tracking so far for about 4 months.

I don't know a human that could ever keep up with this kind of thing. People just think he's super personable, but in reality he's not. He's just got a really cool tool to use.

He's managed some really good numbers because being that personal with people brings them back and keeps them chatting. He'll be pushing for partner after streaming for only a year and he's just some guy I found playing Wild Hearts with 0 viewers one day... :P

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[–] hendrik@palaver.p3x.de 3 points 2 days ago* (last edited 2 days ago)

I think that's a size where it's a bit more than a good autocomplete. Could be part of a chain for retrieval augmented generation. Maybe some specific tasks. And there are small machine learning models that can do translation or sentiment analysis, though I don't think those are your regular LLM chatbots... And well, you can ask basic questions and write dialogue. Something like "What is an Alpaca?" will work. But they don't have much knowledge under 8B parameters and they regularly struggle to apply their knowledge to a given task at smaller sizes. At least that's my experience. They've become way better at smaller sizes during the last year or so. But they're very limited.

I'm not sure what you intend to do. If you have some specific thing you'd like an LLM to do, you need to pick the correct one. If you don't have any use-case... just run an arbitrary one and tinker around?

absolutely nothing

[–] 30p87@feddit.org -3 points 2 days ago
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