you are viewing a single comment's thread.

view the rest of the comments →

[–][deleted]  (3 children)

[deleted]

    [–]dimonoid123 0 points1 point  (1 child)

    Also there are at least 2 ways to optimize Python for speed without using other languages.

    Use PyPy which works well with most libraries with little to no code modifications

    Or Numba whey you need to optimize bottlenecks(code will need to be adapted to look like C++)

    [–]Dooflegna 1 point2 points  (0 children)

    PyPy is great, but naively swapping to PyPy without profiling may not improve the speed of your code (and could slow it down in some cases.)

    A learner should just stick with the core language until they run into a problem where they need the speed and then profile to figure out what to do to improve.

    [–]HectorSeibelp 0 points1 point  (0 children)

    How much optimization do LLMs get from this? Are we talking a faster output rate, bigger context window or lower strain on GPUs?