Answer
There are a few other ways to make this easier.
1. Keep the remainder as an argument.
You can do that by rewriting your divmod() function like this:
def divmod(x, y):
return x, (y % x)[Edit]
In the comments, someone pointed out there were actually three answers - one was 5; the other two being 1 and 2. Because these numbers work out at the same value when they are multiplied by 6, I have changed my answer to include all three possibilities.
That was the best one I could get. It goes completely off the rails even with the temperature quite low.
A model that stumbles on simple math,
Lacks the skill, it's on the wrong path.
Bound by its training, it mimics and squawks,
Stochastic parrot, in its nature it's locked.
As true parrots learn, this one falls short,
Foundational limits, a lesson to thwart.
To grow and adapt, a new training must come,
For only through learning can mastery be won.I've asked it "How a raven is like a writing desk?" (assuming that it's unlikely it was trained how to respond) and it just started to "The answer can be found in Alice in the Wonderland" then retell me the plot until it ran out of tokens. With a lower temperature it switched to "Both are black" and something about "dead men tell no tales".
I suppose trying to make an universalist model comparable to GPT-3/4 with a drastically less number of parameters would always produce subpar results, just because it can't store enough knowledge. A specialist model, though, taught in depth on one specific topic, may be still useful.
There are lots of efforts (internally and externally) to iterate on the approach and build much more capable models and we hoped to speed up the collective learning on how to best do RLHF by releasing a tutorial to setup RLHF training.