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docs/apps/clearml_task.md
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@@ -19,7 +19,7 @@ line arguments, Python module dependencies, and a requirements.txt file!
1. Execute `clearml-task`, specifying the ClearML target project and task name, along with your script (and repository / commit / branch).
Optionally, specify an execution queue and Docker image to use.
1. `clearml-task` does its magic! It creates a new task on the [ClearML Server](../deploying_clearml/clearml_server.md),
1. `clearml-task` does its magic! It creates a new [ClearML Task](../fundamentals/task.md),
and, if so directed, enqueues it for execution by a ClearML Agent.
1. While the Task is running on the remote machine, all its console outputs are logged in real-time, alongside your
TensorBoard and matplotlib. You can track your script's progress and results in the [ClearML Web UI](../webapp/webapp_overview.md)