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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, to 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:
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If you are not sure about how to make your choice, but you know you need more than 1 CPU core, we recommend using the QuarterNode_cpu Resource Profile:
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If you are using GPUs, we recommend using the entire node, since each node has only one GPU. You can do that by creating this the FullNode_gpu Resource Profile:
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