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The new buildx based build no longer leaves the dist/linux-* directories
around, so we don't have to clean them up before uploading.

The rocm CI step for RCs was incorrectly tagging them as the latest rocm build.
The multiarch manifest was incorrectly tagged twice (with and without the
prefix "v").  Static windows artifacts weren't being carried between build
jobs.  This also fixes the latest tagging script.

The runners don't have emulation set up so the default multi-platform build
wont work.

scripts: fix incremental builds on linux or similar

Corrects x86_64 vs amd64 discrepancy

* Optimize container images for startup

This change adjusts how to handle runner payloads to support
container builds where we keep them extracted in the filesystem.
This makes it easier to optimize the cpu/cuda vs cpu/rocm images for
size, and should result in faster startup times for container images.

* Refactor payload logic and add buildx support for faster builds

* Move payloads around

* Review comments

* Converge to buildx based helper scripts

* Use docker buildx action for release

runner: Flush pending responses before returning

If there are any pending reponses (such as from potential stop
tokens) then we should send them back before ending the sequence.
Otherwise, we can be missing tokens at the end of a response.

Fixes #6707

refactor show ouput

fixes line wrapping on long texts

This adds back a check which was lost many releases back to verify /dev/kfd permissions
which when lacking, can lead to confusing failure modes of:
  "rocBLAS error: Could not initialize Tensile host: No devices found"

This implementation does not hard fail the serve command but instead will fall back to CPU
with an error log.  In the future we can include this in the GPU discovery UX to show
detected but unsupported devices we discovered.

add *_proxy to env map for debugging

* Quiet down dockers new lint warnings

Docker has recently added lint warnings to build.  This cleans up those warnings.

* Fix go lint regression

Includes small improvements to document layout and code blocks

When we determine a GPU is too small for any layers, it's not always clear why.
This will help troubleshoot those scenarios.

This reverts commit a60d9b89.

With the new very large parameter models, some users are willing to wait for
a very long time for models to load.

Provide a mechanism for users to set aside an amount of VRAM on each GPU
to make room for other applications they want to start after Ollama, or workaround
memory prediction bugs