Update README.md

baraline · Mar 11, 2023 · 06cc446 · 06cc446
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@@ -31,6 +31,8 @@ We recommend doing this in a new virtual environment using anaconda to avoid any
 
 An optional dependency that can help speed up numba, which is used in our implementation, is the Intel vector math library (SVML). When using conda it can be installed by running `conda install -c numba icc_rt`. I didn't test the behavior with AMD processors, but I suspect it won't work.
 
+If you are using RDST in some specific settings such as an HPC cluster and are getting errors, take a loot at [issue #24](https://github.com/baraline/convst/issues/24), you may need to change the numba compilation settings to not using function caching (see [this example](https://github.com/baraline/convst/blob/main/examples/Changing_numba_options.py)).
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 ## Tutorial
 We give here a minimal example to run the `RDST` algorithm on any dataset of the UCR archive using the sktime API to fect dataset: