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docs/guides/clearml_agent/executable_exp_containers.md
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title: Executable Experiment Containers
---
This tutorial demonstrates using [`clearml-agent`](../../clearml_agent.md)’s [`build`](../../clearml_agent/clearml_agent__ref#build)
This tutorial demonstrates using [`clearml-agent`](../../clearml_agent.md)’s [`build`](../../clearml_agent/clearml_agent_ref.md#build)
command to package an experiment into an executable container. In this example, you will build a Docker image that, when
run, will automatically execute the [keras_tensorboard.py](https://github.com/allegroai/clearml/blob/master/examples/frameworks/keras/keras_tensorboard.py)
script.

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docs/guides/ide/google_colab.md
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Users can transform a Google Colab instance into an available resource in ClearML using [ClearML Agent](../../clearml_agent.md).
This tutorial goes over how to create a ClearML worker node in a Google Colab notebook. Once the worker is up
and running, users can send Tasks to be executed on the Google Colab's HW.
and running, users can send Tasks to be executed on Google Colab's HW.
## Prerequisites
* Be signed up for ClearML (Or have a server deployed).