> For the complete documentation index, see [llms.txt](https://docs.console.zenlayer.com/welcome/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.console.zenlayer.com/welcome/gpu-cloud/virtual-machines/access-an-instance.md).

# Access an Instance

## Access Instances with `Ollama` Image

Once your instance is launched, access it via `WebUI` or `JupyterLab`:

1. Go to instance list page and click <img src="/files/dZ23MiifkySFwROPzDUm" alt="" data-size="line"> or <img src="/files/NaMukpwmvWFZU2RUFwYl" alt="" data-size="line"> in the **Instance Access** column.
2. Once logged in, you'll have access to pre-installed software, such as Llama, JupyterLab, Python, and CUDA, to begin running your tasks.

## Access Instances with `Ubuntu` Image

1. Use an SSH client to connect to the instance with the provided key pair.

   ```bash
   ssh -i <path_to_key> ubuntu@<instance_ip_address>
   ```
2. Once logged in, you'll have access to pre-installed software, such as cuDNN, NvidiaDriver, and CUDA, to begin running your tasks.

## Running AI/ML Workloads

With JupyterLab and Python installed, you can run AI/ML tasks seamlessly by leveraging the GPU's power for fast model training and inference.

Example command to check GPU usage:

```bash
nvidia-smi
```