Tangential (but topical in that "The threat is comfortable drift toward not understanding what you're doing" is also on the front page):
Is the generated python code in the example wrong?
The prompt
> Develop a Python function that removes any falsey values from a list. Return the modified list without creating a new one.
Is answered with list comprehension, which makes a new list and leaves the original unmodified (never mind that the *args input necessarily can't be a modifiable list?)
def remove_falsey_values(*args): return [val for val in args if val]
Whereas I'd expect something like
def remove_falsey_values(l):
for i in reversed(range(len(l))):
if not l[i]: l.pop(i)
# returned list is linked to input l
return l
a = [1, 0, False, 'foo']
x = remove_falsey_values(a)
x[0] = 2
print(a) # [2,'foo']
This is a great question. You definitely aren't training this to use it, you're training it to understand how things work. It's an educational project, if you're interested in experimenting with things like distributed training techniques in JAX, or preference optimisation, this gives you a minimal and hackable library to build on.
Is the generated python code in the example wrong?
The prompt
> Develop a Python function that removes any falsey values from a list. Return the modified list without creating a new one.
Is answered with list comprehension, which makes a new list and leaves the original unmodified (never mind that the *args input necessarily can't be a modifiable list?)
Whereas I'd expect something likeWhy would people want to spend $200 to train a coding model when there are free coding models?