# Versions
The **Versions** view is where you track all the saved versions of code-model pairs in your project. From here, you can [select](#switching-and-modifying-model-versions) which model to examine in the [Network Tab](/user-interface/project/network.md), add a model run (i.e. a specific [evaluation](/user-interface/project/menu-bar/evaluate-a-model.md)) for analysis in the [dashboard](/user-interface/dashboards.md), [delete](#deleting-and-renaming-models-and-model-runs), [export](#export-and-upload-a-model-from-tensorleap), and [upload](#export-and-upload-a-model-from-tensorleap) new models via the Platform.
## Versions Layout Overview
Click  on the top left to open the **Versions** view. Once open, you can choose to minimize the view by clicking 
The version view pinned using the top right pinning
The **Versions** view lists all the code-model pairs you have in your project. The selected version is also highlighted in a different background color than the other versions 
Many [evaluation](/user-interface/project/menu-bar/evaluate-a-model.md) of the same model could be made. Each of these would result in a model run, that could be viewed within the version control by expanding a version. hovering over a Run would present it's start time.
{% hint style="info" %}
Models that were not yet evaluated would not show any available runs
{% endhint %}
## Switching & modifying Model versions
To review and modify different version that exists in the platform - simply hover the mouse over the required model, and click "Add to Dashboard"
Switching Models in the Network view
{% hint style="info" %}
Switching Reviewed versions in the Network Tab has no effect on the Dashboard analysis
{% endhint %}
## Deleting and renaming Models and Model Runs
To delete a model or a model run: hover over it, and click the trash can icon.
To rename a model or a model run: click over the name of the requested version and enter a new name.
### Adding a model run to dashboard analysis
Once an evaluate is completed, multiple Model Runs could be added to the dashboard panel for analysis purposes. To do so, click the "Add To Dashboard" Icon that is to right of each Model Run.
{% hint style="info" %}
If the "Add To Dashboard" Icon is not selectable next to a Model Run it indicates that the evaluate didn't start yet or it was finished unsuccessfully, and there's no data to analyze.
{% endhint %}
## Export & Upload a model from Tensorleap
### Exporting a model
To export a trained model out of Tensorleap:
1. With the **Versions** view open, search for the model
2. Hover your mouse on the model, then click on the right to open the **Export Model** window.
3. On the **Export Model** window, select the format in which the model will be saved.
4. Click to start the export process.
5. The job appears on the list to the right with status set to ***Pending***. A notification message also appears briefly on your screen.
6\. Once Tensorleap completes compiling the file, status is set to ***Finished***.
{% hint style="info" %}
If status is still set to ***Pending*** after some time, you may need to refresh the page to see the change in status to ***Finished***.
{% endhint %}
7\. Click to save the file to your computer.
The available export formats are [Json](https://www.tensorflow.org/api_docs/python/tf/keras/models/model_from_json) (Tensorflow 2), [H5](https://www.tensorflow.org/tutorials/keras/save_and_load) (Tensorflow 2), [ONNX](https://pytorch.org/docs/stable/onnx.html) , [SavedModel](https://www.tensorflow.org/api_docs/python/tf/keras/models/save_model) (Tensorflow)
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