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The build tags rocm or cuda must be specified to both go generate and go build.
ROCm builds should have both ROCM_PATH set (and the ROCM SDK present) as well
as CLBlast installed (for GGML) and CLBlast_DIR set in the environment to the
CLBlast cmake directory (likely /usr/lib/cmake/CLBlast). Build tags are also
used to switch VRAM detection between cuda and rocm implementations, using
added "accelerator_foo.go" files which contain architecture specific functions
and variables. accelerator_none is used when no tags are set, and a helper
function addRunner will ignore it if it is the chosen accelerator. Fix go
generate commands, thanks @deadmeu for testing.

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

- remove ggml runner
- automatically pull gguf models when ggml detected
- tell users to update to gguf in the case automatic pull fails
Co-Authored-By: Jeffrey Morgan <jmorganca@gmail.com>

* Support cuda build in Windows
* Enable dynamic NumGPU allocation for Windows

When CUDA peer access is enabled, multi-gpu inference will produce
garbage output. This is a known bug of llama.cpp (or nvidia). Until the
upstream bug is fixed, we can disable CUDA peer access temporarily
to ensure correct output.

See #961.

pin to 9e70cc03229df19ca2d28ce23cc817198f897278 for now since
438c2ca83045a00ef244093d27e9ed41a8cb4ea9 is breaking

- this makes it easier to see that the subprocess is associated with ollama

* subprocess improvements

- increase start-up timeout
- when runner fails to start fail rather than timing out
- try runners in order rather than choosing 1 runner
- embed metal runner in metal dir rather than gpu
- refactor logging and error messages

* Update llama.go

* Update llama.go

* simplify by using glob

* enable packaging multiple cuda versions
* use nvcc cuda version if available

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Co-authored-by: Michael Yang <mxyng@pm.me>

* linux gpu support
* handle multiple gpus
* add cuda docker image (#488)
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Co-authored-by: Michael Yang <mxyng@pm.me>