Learn how to run Gemma locally on your laptop using Llama.cpp and quantized models. Watch more videos of Gemma Developer Day 2024 → goo.gle/440EAIV Subscribe to Google for Developers → goo.gle/developers #Gemma #GemmaDeveloperDay
I've used gemma for a benchmark in a research project I'm working on, where I compared human results against AI, gemma was the closest after bloom 176B, followed by models like mistral instruct 7Band llama 34B, even the 2b version did pretty well, great work team 👏🏻
Very interesting demo! What kind of extra work would be required to run this without LM Studio? Does Llama.cpp contain the necessarry functions to load models as servers you can interrogate?
Is this meant to be super accessible? If I have an APU, on a laptop with no GPU or NPU(?), that means I can expect it to run fairly well? Also considerations for a lighter yet usable model?
If anyone faces an error on Mac about "network error: self signed certificate", close the app and use terminal, run "NODE_TLS_REJECT_UNAUTHORIZED=0 open -a "LM Studio" " This reopens the app and the error should go away. I have no idea where to put this info sooooo...
Has anyone else tried doing this? I tried following this exactly with LM Studio using the exact model and prompt but I am consistently getting atrocious outputs; the gemma model is just outputting gibberish or incorrectly formatted JSON. I wish there were more details on the presets used.
Just my two cents: 1. No explanation on how to connect LM Studio to the Llama.cpp, 2. newest hardware required - at least it doesn't work on my M1 with eight performance cores and 32 GB Ram
It's cool now, but what if each application starts deploying local models. It'll turn our phones into what data centers were meant for thereby reducing costs for large corporations. Trading a few megabytes for faster and more expensive chips.
Please Elaborate. What were data centres meant for? Asides hardware to run inference of worldwide requests. If it’s done locally, surely it’s better for redundant tasks. Also, the data centres use a lot of megabytes and expensive chips.