> For the complete documentation index, see [llms.txt](https://paperspace.gitbook.io/gradient/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://paperspace.gitbook.io/gradient/explore-train-deploy/notebooks/notebook-tensorboards.md).

# TensorBoard

This guide explains how to use TensorBoard within Gradient Notebooks

## Introduction to TensorBoard

TensorBoard is a [visualization toolkit](https://www.tensorflow.org/tensorboard/) from TensorFlow. It is useful for a variety of applications including visualizing metrics and histograms, displaying images, and more. 

![Example TensorBoard](https://s3-ap-southeast-1.amazonaws.com/blob.blankcursor.com/uploads/editor_attachment/attachment/5650/792a03f09ffcf0db65f4f6fccfe20e561571de8d_2_1117x586.png)

To get started with TensorBoard, we'll need to run a command in the terminal and then access a special URL.

## How to configure a TensorBoard in Gradient Notebooks

To run TensorBoard in a notebook, first make sure that the notebook has TensorBoard installed. 

Next, open a notebook [terminal](/gradient/explore-train-deploy/notebooks/notebook-terminals.md) and run the following command:

```
tensorboard --logdir . --bind_all
```

If needed, the `--logdir` path may be changed to a different value. 

The TensorBoard is now available at the following URL:

```
https://tensorboard-NOTEBOOKID.CLUSTERID.paperspacegradient.com
```

`NOTEBOOKID` may be found on the notebook list view in the Gradient console. 

The default `CLUSTERID` value is `clg07azjl`. Private clusters will have a `CLUSTERID` on the clusters page.