You can run it on a variety of Linux, Mac and Windows based devices, including the Raspberry Pi and most laptops / servers you might have. But you still need a few GBs of memory in order to fit the model itself.
I got this project[0] running on a Pixel. Looks like it works on some iPhones/iPads as well.
You'd probably be better off downloading an edition of wikipedia for that purpose. Entropy, and stuff.
I have a successful-ish commercial iOS app[0] for that. I'd originally built it using ggml, and then subsequently ported it to be based on mlc-llm when I found it.
Says MacOS 13 when I followed your link. Too bad I'm still on MacOS 12. (Is there a reason to require MacOS 13?)
No specific reason, but SwiftUI improved tremendously between macOS 12 and 13, and I use a couple of the newer SwiftUI features. Also, if I could go back, I’d rather not support Intel Macs. I’d built the original version of the app on an Intel Mac 6 months ago, but the performance difference between Intel Macs and Apple Silicon Macs for LLM inference with Metal is night and day. Apple won’t let me drop support for Intel Macs now, so I’ll begrudgingly support it.
Too bad about SwiftUI (not being as good on 12), but that's fair.