← Back to context

Comment by Dylan16807

18 hours ago

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"

4 comments

Dylan16807

Reply
godelski  16 hours ago 

  > But cutting down to 2 million 3 bit parameters or something like that would definitely be possible.

Sure, but there's no free lunch

  > Hey look what I just found

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".

  • Dylan16807  13 hours ago

    A reminder that what I said was "not completely impossible, depending on what your expectations are"

    And I was focused more on the ESP32 part than the exact number of bytes. As far as I'm concerned you can port the model from the minecraft video and you still win the challenge.

    Also, that last link isn't supposed to represent the best you can do in 800KB. 260k parameters is way way under the limit.