...
var rp = ResourceProfile.upsert({'id': 'YourProfileName', 'name': 'YourProfileName', 'cpuCount': <cpus>, 'memoryMb': <cpu_memory>, 'diskGb': <disk_memory>, 'gpuCount': <gpus>, 'gpuMemoryMb': <gpu_memory>});
In addition to that, effectively use the total memory requested in your resource profile, you will need to change the memory limits that are set at the user level of your Jupyter type. This can be done from the static console with:
Jupyter.setMemoryOverride(<cpu_memory>, ConfigOverride.USER)
where <cpu_memory>
matches the field 'memoryMb' of your RP instance.
If you want to make this your default profile whenever launching a Jupyter service, you can do so with:
...