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Start Training Models With One Line

· 2 min read
trainml job create notebook "name"

Get up and running with a GPU-enabled instance with as few as 5 words. With the 0.2.0 release of the trainML python module, you can create, monitor, and remove trainML resources directly from your terminal window. If you already have the trainML module installed, upgrade to the latest version with:

pip install -U trainml

If you are using the trainML module for the first time, be sure you configure authentication before continuing.

The command line interface is rooted in the trainml command. To see the available options, run:

trainml --help

To list all jobs:

trainml job list

To list all datasets:

trainml dataset list

To connect to a job that requires the connection capability:

trainml job connect <job ID or name>

To watch the realtime job logs:

trainml job attach <job ID or name>

For more details of how to use the cli to create, monitor, and remove trainML resources, review the readme readme file on Github.

Additionally, the web downloaded version of the connection utility has been removed. The trainML CLI is now required to use any functionaliy that requires local connection capability.