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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

* dont clamp ctx size in `PredictServerFit`

* minimum 4 context

* remove context warning

This records more GPU usage information for eventual UX inclusion.

This moves all the env var reading into one central module
and logs the loaded config once at startup which should
help in troubleshooting user server logs

If we get our predictions wrong, this can be used to
set a lower memory limit as a workaround.  Recent multi-gpu
refactoring accidentally removed it, so this adds it back.

This change adds support for multiple concurrent requests, as well as
loading multiple models by spawning multiple runners. The default
settings are currently set at 1 concurrent request per model and only 1
loaded model at a time, but these can be adjusted by setting
OLLAMA_NUM_PARALLEL and OLLAMA_MAX_LOADED_MODELS.