---
title: "Get started with TIR Instances"
description: "Create your first TIR Instance from a pre-built image on an hourly plan, open JupyterLab, check its GPU, and keep your files where they last."
content_type: "get-started"
product: "tir-instance"
platform: "TIR"
url: "/tir/tir-instance/get-started/"
---

# Get started with TIR Instances

<!-- cspell:ignore jovyan -->

Launch a TIR Instance on an hourly plan, open JupyterLab in your browser, and run a first command
in it. You need a TIR account with a project, and credit to run the instance; for how much, see
[How much credit do I need to launch an
instance?](/tir/tir-instance/faq/#how-much-credit-do-i-need-to-launch-an-instance)

## Create the instance

1. In TIR, open your project. In the side menu, under **Compute**, select **Containers (Instances)**.
2. Select **Create Instance**.
3. On the **Pre-built** tab, choose the image for the framework you work with, such as PyTorch,
   TensorFlow, or Transformers. These images open JupyterLab. Leave the image on its first version.
4. Keep the name TIR fills in under **Instance Name**, or type your own.
5. Under **Select Computing Resource**, choose what the instance runs on:
   - For a GPU, stay on the **GPU** tab and choose a GPU, such as **NVIDIA H200 SXM** with 141 GB of
     GPU memory. Then pick a size under **Configuration**.
     A GPU marked **Inventory not available** is fully booked right now, so choose another.
   - For a CPU-only instance, switch to the **CPU** tab, choose **C3**, and pick a size.
6. Under **Instance Pricing**, keep **On-Demand**. TIR then bills only the minutes the
   instance runs.
7. Leave **Workspace** at 30 GB. You can make it larger later.
8. Leave **Network & Security** and **Advanced Settings** as they are. JupyterLab opens in your browser, so you can skip the SSH key.
9. Select **Launch Instance**. If your account still needs its billing details, TIR asks for them
   first; complete that step, and the launch goes ahead.

The new instance is **Waiting** in **Manage Instances** while TIR finds capacity and starts the
container. This takes about two minutes. When the status changes to
**Running**, the instance is ready.

## Open JupyterLab

In **Manage Instances**, select the instance's **App URL**. JupyterLab opens in a new browser tab. If your browser blocks the new tab, allow pop-ups for the TIR site in your browser and select the link
again.

## Run your first command

In JupyterLab, open a new notebook with the Python 3 kernel. On a GPU instance, type this in the
first cell and run it:

```python
!nvidia-smi
```

The output lists each GPU in the instance with its memory and use, and the **CUDA Version** that its
driver supports. On a CPU instance, run `!python3 -V` instead, which prints the Python version.

## Keep your files in /home/jovyan

The instance's workspace is the folder `/home/jovyan`, so save your notebooks and data there. Files
in the workspace stay when the instance restarts, stops, or starts. Everything outside it goes
back to the image's contents when the container restarts, so packages you install with `pip` or
`apt` must be installed again after a restart. For where each kind of data lives, see [Where your
files live on an instance](/tir/tir-instance/concepts/where-your-files-live/).

## Stop the instance when you finish

An On-Demand instance is billed for its plan until you stop or delete it. To stop it, open the
instance's actions menu in **Manage Instances**, select **Stop Instance**, tick the confirmation,
and select **Stop**. Once it is **Stopped**,
billing for its plan stops and your workspace is kept. Only the workspace above 30 GB is still
billed. To start it again later, see [Stop, start, and restart an
instance](/tir/tir-instance/how-to/stop-start-and-restart-an-instance/).

## What to do next

- [Create an instance](/tir/tir-instance/how-to/create-an-instance/) explains each choice,
  including committed and Spot billing, storage, SSH keys, start scripts, and add-ons.
- [Connect to an instance over SSH](/tir/tir-instance/how-to/connect-to-an-instance-over-ssh/) to
  work in a terminal from your own machine.
- [Mount datasets and file systems on an
  instance](/tir/tir-instance/how-to/mount-datasets-and-file-systems/) to bring in data that lives
  outside the instance.

If the instance stays on **Waiting** or JupyterLab does not open, see [Troubleshooting TIR
Instances](/tir/tir-instance/troubleshooting/tir-instance/).