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This adjusts our default settings to enable multiple models and parallel
requests to a single model.  Users can still override these by the same
env var settings as before.  Parallel has a direct impact on
num_ctx, which in turn can have a significant impact on small VRAM GPUs
so this change also refines the algorithm so that when parallel is not
explicitly set by the user, we try to find a reasonable default that fits
the model on their GPU(s).  As before, multiple models will only load
concurrently if they fully fit in VRAM.

If we try to use mmap when the model is larger than the system free space, loading is slower than the no-mmap approach.

The recent refactoring of the memory prediction assumed all layers
are the same size, but for some models (like deepseek-coder-v2) this
is not the case, so our predictions were significantly off.

Prior to this change, we logged the memory prediction multiple times
as the scheduler iterates to find a suitable configuration, which can be
confusing since only the last log before the server starts is actually valid.
This now logs once just before starting the server on the final configuration.
It also reports what library instead of always saying "offloading to gpu" when
using CPU.

On Windows, recent llama.cpp changes make mmap slower in most
cases, so default to off.  This also implements a tri-state for
use_mmap so we can detect the difference between a user provided
value of true/false, or unspecified.

nvcc supports parallelism (threads) and cmake + make can use -j,
while msbuild requires /p:CL_MPcount=8

This reverts commit 0577af98.

We update the PATH on windows to get the CLI mapped, but this has
an unintended side effect of causing other apps that may use our bundled
DLLs to get terminated when we upgrade.

* llm: update llama.cpp submodule to `7c26775`

* disable `LLAMA_BLAS` for now

* `-DLLAMA_OPENMP=off`

Make the build faster

Implement support for GPU env var workarounds, and leverage
this for the Vega RX 56 which needs
HSA_ENABLE_SDMA=0 set to work properly

Still not complete, needs some refinement to our prediction to understand the
discrete GPUs available space so we can see how many layers fit in each one
since we can't split one layer across multiple GPUs we can't treat free space
as one logical block

This reverts commit f5f245cc, reversing
changes made to 94d37fdc.

this change broke gguf v2 which is incorrectly detected as big endian

Critical fix from llama.cpp JSON grammar to forbid un-escaped escape characters inside strings, which breaks parsing. (#3782)

* fix embedding by adding fixes from llama.cpp upstream

* remove assert

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Co-authored-by: Jesper Ek <deadbeef84@gmail.com>

This follows the same pattern for cuda and rocm to allow
disabling the build even when we detect the dependent libraries

* Revert "use `int32_t` for call to tokenize (#4738)"

This reverts commit 763bb65d.

* Revert "vocab only"

This reverts commit bf54c845.

* Revert "use ffi for tokenizing/detokenizing"

This reverts commit 26a00a04.

* use `int32_t` for call to tokenize

* variable naming

* cleanup

* fix crash

* partial offloading: allow flash attention and disable mmap

* allow mmap with num_gpu=0

* update llama.cpp submodule to `5921b8f089d3b7bda86aac5a66825df6a6c10603`

* add patch