Hello, I am experimenting with pennylane’s QML algorithms such as variational classifiers (w keras).
All working correctly on pennylane simulator and also on ibmq_qasm_simulator.
However, when running on ibm’s quantum computers such as imbq_quito, due to the iterative nature of the variational classifier: it is launching too many jobs and I get long queues on ibmq. To the point it will take days before even getting metric results for the first epoch, even if I already run like 10/20 jobs.
I desperately need to get some full results (this week) of a single, simple ML classification algorithm using an actual IBM quantum computer.
What pennylane Demo algorithm and small, simple dataset do you suggest I use?
I need to minimize the jobs launched to ibmq and get some full results such as accuracy, even if not good.
Thank you very much in advance for any suggestions and help!