SmallPebble VS picoGPT

You can implement autograd as a library. Just take a look at this

https://github.com/sradc/SmallPebble

The first line of the description is:

  > SmallPebble is a minimal automatic differentiation and deep learning library written from scratch in Python, using NumPy/CuPy.

Thanks for this. My approach to speeding up an autodiff system like this was to write it in terms of nd-arrays rather than scalars, using numpy/cupy [1]. But it's still slower than deep learning frameworks that compile / fuse operations. Wondering how it compares to the approach in this post. (Might try to benchmark at some point.)

[1] https://github.com/sradc/SmallPebble

Located here: https://github.com/sradc/SmallPebble

In that case, you might also enjoy https://jaykmody.com/blog/gpt-from-scratch/

(here's the raw code: https://github.com/jaymody/picoGPT/blob/main/gpt2.py)

I wrote a minimal implementation in NumPy here (the forward pass code is only 40 lines): https://github.com/jaymody/picoGPT

Although this is for a decoder-only transformer (aka GPT) and doesnt include the encoder part.

Take a look at https://github.com/jaymody/picoGPT/blob/a750c145ba4d09d57648...

Yes, this is GPT-2 not 4 and it‘s not the Chat, only the model and it‘s basically only the inference part, not the training loop and it‘s somewhat simplified.

Still, take a good look.

That‘s essentially what it is and a single sheet of paper.

There is nothing specifically about language in „language model“, we just call it that. Better to call it just LLM.

Nobody knows exactly what it learns, although there would be ways to poke around given some research programs. But it seems like the interest in that is limited currently, everyone is busy with improving it or with applications.

Perhaps the answer is that we overestimated what a mind is. It‘s like we used to ask what life is and it turned out that there is nothing special about life, not even the DNA is controlling anything. It‘s merely a chemical process, even though a complex process.

(The hardest part was just designing a math function that has the capability of getting good at this game, but when all is said and done, it need not be a whole lot of code).