Ensntalice! What Would a ‘True Steake’ Spell Do? Prompted D&D Spells

When I was working on the first post about D&D spells from a neural network I generally let the network run wild and create the spells from nothing, which also created the spell names. But I did try ‘prompting’ the network with the spell names from @JanelleCShane’s neural network D&D spell names post and asking it to fill in the rest of the spell information.

I made a ton but they were a bit harder to skim through since you can’t rely on a catchy spell name to jump out. I was going to make better sifting tools but figured I’ll post what I’ve got for now. Thanks to my friend Sam for picking out some good ones. Be warned a lot these samples were from a terrible model and it went way off the rails and just generated absolute nonsense — but it also gave us such delights as a spell that is just “No,No,No,No” over and over.

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Dungeons and Dragons Spells from a Neural Network Are Bonescrackling

In my last post I trained GPT-2 to write Star Trek scripts. Lately I’ve been experimenting with Dungeons and Dragons spells with some amazing results.

I like tabletop roleplaying material for generation because tabletop rules often require a good faith effort at human interpretation anyway. That same effort can make some sense of the silliest of machine generated rules.

I picked out a bunch of of my favorites and there are a lot more spells at the bottom of this blog post for anyone who wants to hunt for some more good stuff. Also I’ll be posting more on my twitter.

Continue reading “Dungeons and Dragons Spells from a Neural Network Are Bonescrackling”

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