There have been changes at Paperspace recently that (IMHO) severely negatively impact experience for playing around with deep learning. You’ll notice in the interface that your notebooks might have a “V1” written beside the notebook name (i.e. below your username) - if so, you’re running on their legacy “V1” notebooks service. But as I’ll explain later, that’s where you want to be.
V1 is notoriously slow for the speed of provisioning you mention - my experiments show this is strongly related to the size of your /notebooks folder - even just the git repository of fastbook at 400MB makes provisioning take several minutes, and if you use any decent fraction of your 8GB space allocation you’ll be taking an hour or more to shut down and spin up. However, /storage only has a 5GB allocation, so you’ll often find yourself writing models out during training etc to /notebooks because /storage will fill up with your data. Failing to clean up before shutdown is what causes your slow spin-up/shutdown.
Moving to V2 seems to dramatically improve spin-up/shutdown times - just create a new notebook from their templates to do this. However, the first thing you’ll notice is that you can’t run Free-P5000 machines on the free plan on V2 (contrary to their marketing materials). And Free-GPU instances are much slower than other free options out there, so you’ll be skipping those.
This means the only way you can keep using Free-P5000 instances is to stay on V1, so you’ll be forking notebooks - however they’ve now made it so forks can’t select Free-P5000 on free tier either (and I haven’t tried it, but my guess from the interface is that if you switch a V1 notebook away from Free-P5000, you can’t switch back). The upside of this is that very few people are now using the Free-P5000 instances, to what used to be a lucky gamble to get your hands on one is now practically guaranteed every time you spin up your cherished V1 Free-P5000 instance.
Which means V1 notebooks that happened to have Free-P5000 instances active at whenever the change happened just became gold-dust - just keep your /notebooks folder free
(BTW - it’s not very expensive gold-dust - a Free-P5000 instance has a GPU that is only 2/3 the speed of an AWS g4dn.xlarge instance, which costs about $0.16/hr on spot. Contrast with Paperspace charging $0.78/hr for P5000. Also keep in mind you can only run a single Free-P5000 instance at once, and it times-out after 6 hours so that means the full compute of a single run just saved you a whole $0.66 compared to paying AWS - if you’re learning one of the most highly sought-after skills on the planet, and yet your personal time is not worth more than that, you may wish to consider how you’re valuing your time…).