Hello, I am trying to use TensorFlow on an AWS ec2 instance. I am using Google’s universal sentence encoder, which is around 1 Gb in size. My ec2 instance has 2Gb of ram I am trying to avoid upping the ram to avoid increasing my costs. At the moment, I just have a small docker image running on the server. How do I go about increasing the max memory usage, I am okay with the fact that it may cause issues and am prepared to increase the overall RAM if necessary but I would prefer to try it this way first.
I am currently using hub.load( ‘TensorFlow Hub’) but can go to hub.keraslayer that would use less RAM