A lot of different ways. Every guide on this guidebook runs on a ~$500 gpu or a couple of dollars on a cloud instance with a bigger GPU https://ravinkumar.com/

A lot of different ways. Every guide on this guidebook runs on a ~$500 gpu or a couple of dollars on a cloud instance with a bigger GPU https://ravinkumar.com/GenAiGuidebook/book_intro.html https://ravinkumar.com/GenAiGuidebook/book_intro.html This guidebook covers pretraining, post training (SFT, RL) and a couple other topics. And others authors have also written books that fit on single node reasonable hardware. If you want to start with a pretrained base I built Gemma 270m and released it last year. This fits on a raspberry pi. https://developers.googleblog.com/en/introducing-gemma-3-270m/ https://developers.googleblog.com/en/introducing-gemma-3-270... The fundamentals of AI don't require industrial amounts of large scale. Think of it like this, when I was learning how a plane worked when I was a kid I didn't build a 747 at home, I started with scale sized model planes. Same idea here. And FWIW I'm a staff researcher at Deepmind (opinions here are my own) so I want to specifically encourage all people out there, you can learn a lot about how these LLMs work at home, for (mostly free), using resources like colabs or spot pricing on accelerator providers. There's many great resources out there and I encourage anyone willing to learn to go for it!