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LocalLLaMA
Welcome to LocalLLaMA! Here we discuss running and developing machine learning models at home. Lets explore cutting edge open source neural network technology together.
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Rule 2 - No comparing artificial intelligence/machine learning models to cryptocurrency. I.E no comparing the usefulness of models to that of NFTs, no comparing the resource usage required to train a model is anything close to maintaining a blockchain/ mining for crypto, no implying its just a fad/bubble that will leave people with nothing of value when it burst.
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I use Strix Halo
On Linux you can just go into the bios and map like 512mb video and then update your grub config and you’re fine, Linux knows to use the unified memory correctly. I don’t know what your LLM told you, but you do not need a 50/50 split. The whole thing has worked for over a year now smoothly, and there are guides like kuz0’s online to help you get everything set up.
Lemonade is better than Ollama for a few reasons:
However, on the negatives, lemonade lags behind upstream engines, so if you wanted to say use Qwen 3.8 125b that just came out, you have to build it and link to rocm yourself. Usually it’s fine waiting a couple weeks, but sometimes I run a custom build and I point lemonade at it.
My stack is NixOS+Podman. I run lemonade in a container it all works great. I use Caddy + Authelia for networking and i serve it over tailscale to my tailnet.
Ollama is just as Foss as Lemonade
https://github.com/ollama/ollama
I’m wrong, sorry