Ray OOM issue when the ray serve is launched

I have always got this OOM problem as I try to launch the “ray serve” to establish a ML backend service. May I know how to set the memory of “7.68G”? how to enhance this threshold according to the ray dashboard.

the dashboard memory limit is 7.68GB from the ray dashboard. How to enhance this value?

The ML code is just like this with higher num_replicas set and then the OOM will happen since more replicants occupy much more memory?

The specific error (RayOutOfMemoryError) you are seeing here is being removed in Ray 2.2 - you may want to give it a try

As for the error you are seeing, it seems the node does not have enough memory to serve 2 replicas - you may want to increase the memory of the node or add another node