> ## Documentation Index
> Fetch the complete documentation index at: https://docs.platform.qubrid.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Quickstart

> Follow these steps to get started with Qubrid Platform: 

## Setting up your Qubrid Account

* **Create** a new account on [platform.qubrid.com](https://platform.qubrid.com)
* SignUp using **Google** or **GitHub** for faster activation
* If you want to use our account creation, enter your name, email, mobile number, organzation & finally set a password
* Agree to the [terms and conditions](https://platform.qubrid.com/terms) & click Sign Up

## Launch your first GPU Virtual Machine

* From the platform, head over to [GPU Instances](https://platform.qubrid.com/create-ai-compute/gpu-instances)
* **Select** your preferred **GPU** Instance (Example: [A100](https://platform.qubrid.com/create-ai-compute/NVIDIA%20A100%20\(40GB\)))
* Choose the **number of GPUs** you'd need, it might be 1,4 or 8
* vCPU Core & RAM is populated based on the GPU Instance which is selected
* Choose your **Root Disk storage** in Gigabytes (Starts at 100 GB & goes till 2 TB)
* Select your **Interface** Console. By default its set to Jupyter, but if you want to access your machine via SSH, enable the SSH Option & provide your Public Key
* Enter your Jupyter Authentication Token only, in case you don't want to access via SSH
* Configure **Auto Stop**, to shuts down the instance after a specific amount of time
* **Review** your selections from the floating wizard at the right part of the dashboard
* Once you have reviewed, click on **Launch** to launch your GPU Instance or click on **Reset** to start over again

<Note>
  **Root Disk Storage** is billed at **10 Cents per GB/month** & is charged even when the instance is stopped. So, 100 GB costs \$10/month.
</Note>

## Check Usage & Credits

* View your available **credits** in navigation bar provided
* Track **usage history** and billing information
* Add credits (Available for **\$5**, **\$10**, **\$30**, **\$50** or some **custom** amount)

## Do whatever you want!

* Run **inference** using a template or your own model
* Perform **fine-tuning** on supported models
* Save and reuse deployed models
* Use our 2 Step **RAG** or define a custom RAG Pipeline
* Deploy **clusters** of GPUs in 1 Click
* Reserve a **Bare Metal** Server

<Accordion icon="download" title="Download our AI Controller">
  1. After logging in, go to the platform
  2. Go to [AI Controller](https://platform.qubrid.com/ai-controller) tab, enter your details & download our controller software
</Accordion>

## Next steps

Now that you have your GPU VM running, explore these key features:

<CardGroup cols={2}>
  <Card title="Convert to Enterprise Account" icon="building" href="Enterprise%20Account">
    Enterprise account comes with additional benefits for Organizations
  </Card>

  <Card title="Customize style" icon="key" href="Manage%20API%20Keys">
    Manage your API Keys, or even generate new API Keys as required
  </Card>

  <Card title="Launch an AI / ML Template" icon="folder-open" href="AI%20Templates">
    AI/ML packages available for quick deployment on high performance GPUs
  </Card>

  <Card title="Fine Tuning" icon="wrench" href="/api-reference/introduction">
    Fine-tune pre-deployed models directly on Platform, without any code
  </Card>
</CardGroup>