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This reduces the built-in linux version to not use any vector extensions
which enables the resulting builds to run under Rosetta on MacOS in
Docker.  Then at runtime it checks for the actual CPU vector
extensions and loads the best CPU library available

If the tree has a stale submodule, make sure we clean it up first

* update cmake flags for intel macOS

* remove `LLAMA_K_QUANTS`

* put back `CMAKE_OSX_DEPLOYMENT_TARGET` and disable `LLAMA_F16C`

Refactor where we store build outputs, and support a fully dynamic loading
model on windows so the base executable has no special dependencies thus
doesn't require a special PATH.

This changes the model for llama.cpp inclusion so we're not applying a patch,
but instead have the C++ code directly in the ollama tree, which should make it
easier to refine and update over time.

By default builds will now produce non-debug and non-verbose binaries.
To enable verbose logs in llama.cpp and debug symbols in the
native code, set `CGO_CFLAGS=-g`

This switches the default llama.cpp to be CPU based, and builds the GPU variants
as dynamically loaded libraries which we can select at runtime.

This also bumps the ROCm library to version 6 given 5.7 builds don't work
on the latest ROCm library that just shipped.

This changes the container-based linux build to use an older Ubuntu
distro to improve our compatibility matrix for older user machines

Run the server.cpp directly inside the Go runtime via cgo
while retaining the LLM Go abstractions.