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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

llama3.1 memory

* Update gpu.md

    Seems strange that the laptop versions of 3050 and 3050 Ti would be supported but not the non-notebook, but this is what the page (https://developer.nvidia.com/cuda-gpus

) says.
Signed-off-by: bean5 <2052646+bean5@users.noreply.github.com>

* Update gpu.md

Remove notebook reference

---------
Signed-off-by: bean5 <2052646+bean5@users.noreply.github.com>

Replace "command -v" with encapsulated functionality

Added Enchanted with Apple Vision Pro support

change "dorrect" to "correct"

It looks like driver 525 (aka, cuda driver 12.0) has problems with the cuda v12 library
we compile against, so run v11 on those older drivers if detected.

On systems with low system memory, we can hit allocation failures that are difficult to diagnose
without debug logs.  This will make it easier to spot.

/Users/au/src/ollama/llm/ext_server/server.cpp:289:9: warning: 'sprintf' is deprecated: This function is provided for compatibility reasons only. Due to security concerns inherent in the design of sprintf(3), it is highly recommended that you use snprintf(3) instead.

Signed-off-by: Xiaodong Ye <yeahdongcn@gmail.com>