> For the complete documentation index, see [llms.txt](https://docs.tensorleap.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.tensorleap.ai/user-interface/project/versions.md).
# 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)
---
# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.
## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.
Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:
```
GET https://docs.tensorleap.ai/user-interface/project/versions.md?ask=&goal=
```
`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.
Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.