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In this fashion, your original data is never truly changed, ensuring reproducibility of your work. If you are doing data cleaning, you can do so in a workspace and save it as a new csv, or clean the data locally if that is easier.
From your lab folder:
uhhh figure this out, maybe install nvidia CLI somewhere on lmm?The Nvidia CLI is installed on LLM and Headnode. Simply follow the same CLI setup as before, including your API key generation, and you will be able to upload your data directly from the University network. Make sure you are on a VPN if you are off-campus or you will be blocked by Nvidia's firewall. In addition, you can use Powershell to navigate to mapped network drives and upload this way as well.
Starting a Job
The default time limit of a job is 30 days. There are 2 ways to start a job on DGX cloud, via web interface or via CLI. The web interface is graphical, easy to use, and also generates a CLI prompt for you to use if you wish. In this example, we will submit a job to launch a jupyternotebook instance where we can access our data from inside the notebook.
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