[dreamer7]

Did you find out :D?

[arpankapoor]

I did! There are a few places it transcribes incorrectly, but overall I'm very impressed. Here's the first ~30 seconds:

    [00:00.000 --> 00:09.000]  Look, I was going to go easy on you, not to hurt your feelings, but I'm only going to get this one chance.
    [00:09.000 --> 00:11.000]  Something's wrong, I can feel it.
    [00:11.000 --> 00:17.000]  It's just a feeling I've got, like something's about to happen, but I don't know what.
    [00:17.000 --> 00:21.000]  If that means what I think it means, we're in trouble, big trouble.
    [00:21.000 --> 00:24.000]  Had to be as bananas as you say, I'm not taking any chances.
    [00:24.000 --> 00:26.000]  You're just one to die for.
    [00:26.000 --> 00:32.000]  I'm beginning to feel like a rap god, rap god. All my people from the front to the back nod, back nod.

[NaturalPhallacy]

It was doing it slowly, but hadn't got to the insane bit when I killed it to try and get it working with CUDA, so I had to do some digging and it turns out I need a version of pytorch with CUDA enabled, and so I had to go and install Anaconda, and now now conda is stuck trying to "solve" my environment to install pytorch with CUDA.

So...probably?

Pre-post edit: I can't get it to work.

I've installed pytorch with cuda via pip3, installed the nVidia toolkit and it doesn't see it:

>>> import torch >>> torch.cuda.is_available() False

I've wasted like an hour and a half on it now. I'm not a python dev, and don't have any ML experience so this was just for fun and now it's not anymore.

[forgingahead]

Welcome to every single Python ML project - dependency hell will quickly kill any enthusiasm one may have for trying out projects. It really feels archaic to have these issues with such cutting edge technology.

[mlboss]

Try running pytorch/pytorch docker. But you will need nvidia container runtime installed. I am sure somebody will soon release docker for this also.