Good question! I am collecting human data on how quantization affects outputs. See here for more information: ggml-org/llama.cpp#5962
In the meantime, use the largest that fully fits in your GPU. If you can comfortably fit Q4_K_S, try using a model with more parameters.
See the wiki upstream: https://github.com/ggerganov/llama.cpp/wiki/Feature-matrix
Some notes, tools, and techniques for reverse engineering macOS binaries.
Ramp up your Kubernetes development, CI-tooling or testing workflow by running multiple Kubernetes clusters on Ubuntu Linux with KVM and minikube.
In this tutorial we will combine the popular minikube tool with Linux's Kernel-based Virtual Machine (KVM) support. It is a great way to re-purpose an old machine that you found on eBay or have gathering gust under your desk. An Intel NUC would also make a great host for this tutorial if you want to buy some new hardware. Another popular angle is to use a bare metal host in the cloud and I've provided some details on that below.
We'll set up all the tooling so that you can build one or many single-node Kubernetes clusters and then deploy applications to them such as OpenFaaS using familiar tooling like helm. I'll then show you how to access the Kubernetes clusters from a remote machine such as your laptop.
