Comment by Dylan16807
1 day ago
It's not completely impossible, depending on what your expectations are. That language model that was built out of redstone in minecraft had... looks like 5 million parameters. And it could do mostly coherent sentences.
Ummm...
Which is a lot more than 888kb... Supposing your ESP32 could use qint8 (LOL) that's still 1 byte per parameter and the k in kb stands for thousand, not million.
https://www.youtube.com/watch?v=VaeI9YgE1o8
Yes I know how much a kilobyte is. But cutting down to 2 million 3 bit parameters or something like that would definitely be possible.
And a 32 bit processor should be able to pack and unpack parameters just fine.
Edit: Hey look what I just found https://github.com/DaveBben/esp32-llm "a 260K parameter tinyllamas checkpoint trained on the tiny stories dataset"
Sure, but there's no free lunch
I've even personally built smaller "L"LMs. The first L is in quotes because it really isn't large (So maybe lLM?) and they aren't anything like what you'd expect and certainly not what the parent was looking for. The utility of them is really not that high... (there are special cases though) Can you "do" it? Yeah. I mean you can make a machine learning model of essentially arbitrary size. Will it be useful? Obviously that's not guaranteed. Is it fun? Yes. Is it great for leaning? Also yes.
And remember, Tiny Stories is 1GB of data. Can you train it for longer and with more data? Again, certainly, BUT again, there are costs. That Minecraft one is far more powerful than this thing.
Also, remember that these models are not RLHF'd, so you really shouldn't expect it to act like you're expecting a LLM to work. It is only at stage 0, the "pre-training", or what Karpathy calls a "babbler".
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