for coding tasks you need web search and RAG. It's not the size of the model that matters, since even the largest models find solutions online.
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I have it roleplay scenarios with me and sometimes I verbally abuse it for fun.
As cool and neato as I find AI to be, I haven't really found a good use case for it in the selfhosting/homelabbing arena. Most of my equipment is ancient and lacking the GPU necessary to drive that bus.
Learning/practice, and any use that feeds in sensitive data you want to keep on-prem.
Unless you’re set to retire within the next 5 years, the best reason is to keep your resume up to date with some hands-on experience. With the way they’re trying to shove AI into every possible application, there will be few (if any) industries untouched. If you don’t start now, you’re going to be playing catch up in a few years.
I installed Llama. I've not found any use for it. I mean, I've asked it for a recipe because recipe websites suck, but that's about it.
you can do a lot with it.
I heated my office with it this past winter.
Sorry, I am just gonne dump you some links from my bookmarks that were related and interesting to read, cause I am traveling and have to get up in a minute, but I've been interested in this topic for a while. All of the links discuss at least some usecases. For some reason microsoft is really into tiny models and made big breakthroughs there.
https://reddit.com/r/LocalLLaMA/comments/1cdrw7p/what_are_the_potential_uses_of_small_less_than_3b/
https://github.com/microsoft/BitNet
https://www.microsoft.com/en-us/research/blog/phi-2-the-surprising-power-of-small-language-models/
https://news.microsoft.com/source/features/ai/the-phi-3-small-language-models-with-big-potential/
It'll work for quick bash scripts and one-off things like that. But there's not usually enough context window unless you're using a 24G GPU or such.
Yeah shell scripts are one of those things that you never remember how to do something and have to always look it up!
Snippets are a great use.
I use StableCode on my phone as a programming tutor for learning Python. It is outstanding in both speed and in accuracy for this task. I have it generate definitions which I copy and paste into Anki the flashcard app. Whenever I'm on a bus or airplane I just start studying. Wish that it could also quiz me interactively.
Please be very careful. The python code it'll spit out will most likely be outdated, not work as well as it should (the code isn't "thought out" as if a human did it.
If you want to learn, dive it, set yourself tasks, get stuck, and f around.
I know what you mean. All the code generated with ai was loaded with problems. Specifically it kept forcing my api keys into the code without using environmental variables. But for basic coding concepts it has so far been perfect. even a 3b model seemingly generates great definitions
7b is the smallest I've found useful. I'd try a smaller quant before going lower, if I had super small vram.
Have you tried RAG? I believe that they are actually pretty good for searching and compiling content from RAG.
So in theory you could have it connect to all of you local documents and use it for quick questions. Or maybe connected to your signal/whatsapp/sms chat history to ask questions about past conversations
No, what is it? How do I try it?
RAG is basically like telling an LLM "look here for more info before you answer" so it can check out local documents to give an answer that is more relevant to you.
You just search "open web ui rag" and find plenty kf explanations and tutorials
I think RAG will be surpassed by LLMs in a loop with tool calling (aka agents), with search being one of the tools.
LLMs that train LoRas on the fly then query themselves with the LoRa applied
I've integrated mine into Home Assistant, which makes it easier to use their voice commands.
I haven't done a ton with it yet besides set it up, though, since I'm still getting proxmox configured on my gaming rig.
I've used smollm2:135m for projects in DBeaver building larger queries. The box it runs on is Intel HD 530 graphics with an old i5-6500T processor. Doesn't seem to really stress the CPU.
UPDATE: I apologize to the downvoter for not masochistically wanting to build a 1000 line bulk insert statement by hand.
How, exactly, do you have Intel HD graphics, found on Intel APUs, on a Ryzen AMD system?
Sorry, I was trying to find parts for my daughter's machine while doing this (cheap Minecraft build). I corrected my comment.
I've run a few models that I could on my GPU. I don't think the smaller models are really good enough. They can do stuff, sure, but to get anything out of it, I think you need the larger models.
They can be used for basic things, though. There are coder specific models you can look at. Deepseek and qwen coder are some popular ones
I haven't actually found the coder-specific ones to be much (if at all) better than the generic ones. I wish I could have. Hopefully LLMs can become more efficient in the very near future.
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.
Hey, you're treating that data with the respect it demands, right? And you definitely collected consent from those chat participants before you Hoover'd up their [re-reads example] extremely Personal Identification Information AND Personal Health Information, right? Because if you didn't, you're in violation of a bunch of laws and the Twitch TOS.
If I say my name is Doo doo head, in a public park, and someone happens to overhear it - they can do with that information whatever they want. Same thing. If you wanna spew your personal life on Twitch, there are bots that listen to all of the channels everywhere on twitch. They aren't violating any laws, or Twitch TOS. So, *buzzer* WRONG.
Right now, the same thing is being done to you on Lemmy. And Reddit. And Facebook. And everywhere else.
Look at a bot called "FrostyTools" for Twitch. Reads Twitch chat, Uses an AI to provide summaries of chat every 30 minutes or so. If that's not violating TOS, then neither am I. And thousands upon thousands of people use FrostyTools.
I have the consent of the streamer, I have the consent of Twitch (through their developer API), and upon using Twitch, you give the right to them to collect, distribute, and use that data at their whim.
So, buzzer WRONG.
Quite arrogant after you just constructed a faulty comparison.
If I say my name is Doo doo head, in a public park, and someone happens to overhear it - they can do with that information whatever they want. Same thing.
That's absolutely not the same thing. Overhearing something that is in the background is fundamentally different from actively recording everything going on in a public space. You film yourself or some performance in a park and someone happens to be in the background? No problem. You build a system to identify everyone in the park and collect recordings of their conversations? Absolutely a problem, depending on the jurisdiction. The intent of the recording(s) and the reasonable expectations of the people recorded are factored in in many jurisdictions, and being in public doesn't automatically entail consent to being recorded.
See for example https://www.freedomforum.org/recording-in-public/
(And just to clarify: I am not arguing against your explanation of Twitch's TOS, only against the bad comparison you brought.)
You're both getting side-tracked by this discussion of recording. The recording is likely legal in most places.
It's the processing of that unstructured data to extract and store personal information that is problematic. At that point you go from simply recording a conversation of which you are a part, to processing and storing people's personal data without their knowledge, consent, or expectation.
True.
Although in Germany for example it can also be an issue when recording. If you have a security camera pointed at a public space (that can include the sidewalk infront of your house), passersby can sue you to take it down and potentially get you fined. Even pretending to constantly record such an area can yield that result.
I'm not a lawyer but I suppose it would depend on the ToS and if the user agrees to the recording and processing. But if it allows the extraction of the real identity of the user it's probably a GDPR issue.
@kattfisk That seems to imply that you cannot personally listen to or watch recordings that you have made in public. In doing so, you are abstracting personal details that you might have missed before, refreshing your memory, and so on. What is the material difference between you doing this without machine help versus with automation that makes it ethically problematic? What if a friend helped you, not a machine?
Doesn't Twitch own all data that is written and their TOS will state something like you can't store data yourself locally.