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Follow general lemmy guidelines.
Fully open and accessible: Fully open-source release of model weights, training hyperparameters, datasets, and code, fostering innovation and collaboration within the AI community.
That's actually pretty good. Seems to be open source as the OSI defines it, rather than the much more common "this model is open source, but the dataset is a secret".
Got it up and running on a Debian distrobox… now I need to figure out how to train it. Will be my first steps into this type of thing – so prob will take me a bit to figure out how it all works
I need to catch up on training. I need an LLM that I can train on all my ebooks and digitized music, and can answer questions "what's that book where the girl goes to the thing and does that deed?"
Existing implementations can probably do that already.
I'm sure; I just don't know how. I need to set aside some time and educate myself.
Frankly, this generation of AI I find rather dull. It won't directly lead a AGI, although I'm sure it'll be a component, but I think that'll be another 10-20 years before the next breakthrough. I personally don't think it's as interesting as the symbolic, knowledge-based systems of the mid-80's; at least those were reasoning systems. LLMs look impressive to lay people (including myself - I understand the general concepts, but have no experience with the programming or training, so I'm just another lay user), but there's no reasoning or understanding behind it, and if what it produces is truthful or accurate, it's largely on accident. So I've had trouble getting excited about it.
I mean literally just go to chatgpt or whatever and ask it "what's that movie with Morgan Freeman playing God" and it'll give a few guesses. For common info, it's usually pretty good.
I don't want ChatGPT to remember that I was searching for Cafe Flesh by description.
Interesting idea!
Well, it's either that or finding a Lemmy community for "what's that book" and posting a long description of how you remember the book.
I did this recently about a TV show I once saw an episode or two on broadcast TV in the early 90's. Only I completely misremembered it; I thought one of the main characters was a little girl when, in fact, it was a grizzled old woodworker. I mean, really, Brain? What the actual fuck? Luckily, from the context and time period, someone recognized it, but I no longer trust my own memory (if I ever really did).
"So, I read this book once - I think there were two or three in the series - and it was about some little furry girls who find a magic potion in a cave, but the potion is poison that can kill everyone in the world, and they had to take it to a special magic hole and throw it in. And they're being chased the entire time by ghosts on ghost horses. I think there are trees in it." - me, trying to describe the LOTR. Thanks, Brain; you're a big help.
I see all these graphs about how much better this LLM is than another, but do those graphs actually translate to real world usefulness?
I have yet to see a 3B model that's not dumb.
I think more of the issue is what constitutes actual open source. This is actually open source, and it performs well. If you're familiar with the space, then it's a big deal.
I'm not familiar with the space but realised this was a big deal.
I feel like I need to shower after interacting with any of the other LMs.
Something fully open source will hopefully be embraced by the community and be used for some interesting, useful, and value producing things instead of just attracting venture capital.
I see, thank you.
Damn, they even chose a dataset with a open license.
Is it really or is it just a binary release like everything else?
Edit: It is actually Foss
Everything is explained and linked in the project, so...
Yeah I noticed that after writing this. Really cool stuff
Thank god for this. Setting up deepseek to utilize my AMD GPU through llama was near impossible
The problem is... How do we run it if rocm is still a mess for most of their gpus? Cpu time?
Is it still a mess? I thought it was reasonably well supported on Linux with GPUs from the past few years.
Well it's not necessarily geared towards consumer devices. As mentioned in the writeup, it's not trained on consumer gear.
Smart people, I beg of thee, explain! What can it do?
Edit: looks to be another text based one, not image generation right?
It's language only, hence, LM
To be fair, I didn't know if that language included programming language, and thus maybe still consider image based AI to be included in LLM. Is there a different designation for the type of AI that does image generation?