Until ROCm v6.2 ships, we wont be able to get accurate free memory
reporting on windows, which makes automatic concurrency too risky.
Users can still opt-in but will need to pay attention to model sizes otherwise they may thrash/page VRAM or cause OOM crashes.
All other platforms and GPUs have accurate VRAM reporting wired
up now, so we can turn on concurrency by default.
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.
Our default behavior today is to try to fit into a single GPU if possible.
Some users would prefer the old behavior of always spreading across
multiple GPUs even if the model can fit into one. This exposes that
tunable behavior.
* envconfig/config.go: Fix wrong description of OLLAMA_LLM_LIBRARY
Signed-off-by: Lei Jitang <leijitang@outlook.com>
* serve: Add more env to help message of ollama serve
Add more enviroment variables to `ollama serve --help`
to let users know what can be configurated.
Signed-off-by: Lei Jitang <leijitang@outlook.com>
---------
Signed-off-by: Lei Jitang <leijitang@outlook.com>
