# Quick Start ## Prerequisites To begin using Gradient, follow these preliminary steps: 1. [Create a Paperspace account ](https://console.paperspace.com/signup?gradient=true) 2. Optional: [Create a team ](https://support.paperspace.com/hc/en-us/articles/360010359213-Creating-and-Managing-Paperspace-Teams)to invite collaborators Now you can create Notebooks, Workflows, Deployments, and more! {% embed url="" %} ## Logging in for the first time When you first log into the Paperspace Console, you can select Gradient from the product dropdown: ![](https://3486137344-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-LHZRFUkajubOAmgu6Rd%2F-MYbc85fM-C7AcWZ2W6E%2F-MYbdsyLINABf1-rLkRn%2Fimage.png?alt=media\&token=5025bf85-bea3-4113-b5de-67e0fe5b13d9) ## First Create a Project Projects help organize your work. To get started, just choose a name and click create. ![](https://3486137344-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-LHZRFUkajubOAmgu6Rd%2F-Mkri5f959BUzXzcwFWX%2F-MkrlryiZjN9Z-N80zb2%2Fproject_create_2.png?alt=media\&token=8eeef2e4-8d6c-4468-ac63-92520f348787) ## Create a Notebook After creating a Project, Notebooks can be created on the Notebooks tab within the Project. Just select a [template](https://paperspace.gitbook.io/gradient/explore-train-deploy/notebooks/notebook-containers), choose your [instance type](https://paperspace.gitbook.io/gradient/more/instance-types), and then click create. {% hint style="success" %} Check out the [FREE GPU](https://paperspace.gitbook.io/gradient/more/instance-types/free-instances) option when launching Notebooks! {% endhint %} ![](https://3486137344-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-LHZRFUkajubOAmgu6Rd%2F-Mkx_vPkPkZApHyR4RCa%2F-MkxdAl_RIJYmM3tU4YD%2Fnotebook_create.png?alt=media\&token=b5125ed0-c309-4928-8166-716376f35e00) {% hint style="success" %} Check out the [ML Showcase](https://ml-showcase.paperspace.com/) for a list of projects you can fork into your own account {% endhint %} You can stop, start, fork, and swap out the instance type anytime. Choose from a wide selection of pre-configured templates or bring your own. ## Create a Workflow You can automate machine learning tasks using Workflows. You can define a workflow once and use it repeatedly to perform simple or complex MLOps activities, such as pre-processing data, training models, and creating or updating deployments. ![](https://3486137344-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-LHZRFUkajubOAmgu6Rd%2F-MkwwsA2W9w6mHVFUv1U%2F-MkwzmTHv5RfUmiyV6In%2Fworkflow_create.png?alt=media\&token=fd4f8cd9-7bd0-4962-b2e7-d022bc4c74c3) ### Run a Workflow from a GitHub trigger (recommended) This requires the project to be linked to a GitHub repository. Follow the instructions on the page to install the Gradient **Github App** into your Github account, and select the git repo you want to associate with project. Alternatively you can select one of the **sample repos.** If you choose to use your own git repo, you will be prompted to add a YAML file to your repo that defines the Workflow steps. ### **Run a Workflow from the CLI (advanced)** 1. [**Install the Gradient CLI**](https://paperspace.gitbook.io/gradient/get-started/quick-start/install-the-cli) 2. [**Connect your account**](https://paperspace.gitbook.io/gradient/get-started/install-the-cli#connecting-your-account) 3. **Create a Workflow** This step is only needed if you didn't already create a default `demo workflow` in the web interface. Specify a name for the Workflow and a `projectId`. Use the `projectId` from the project you created earlier. ```bash gradient workflows create \ --name \ --projectId ``` To see a list of your projects and `projectIds` run `gradient projects list`. For a list of Workflows within a project run `gradient workflows list --projectId `. 4. **Download or copy the sample Workflow Spec to your computer** Here is the Workflow Spec for reference: ```yaml jobs: CloneRepo: resources: instance-type: C5 outputs: repo: type: volume uses: git-checkout@v1 with: url: https://github.com/NVlabs/stylegan2.git StyleGan2: resources: instance-type: P4000 needs: - CloneRepo inputs: repo: CloneRepo.outputs.repo outputs: generatedFaces: type: dataset with: ref: demo-dataset uses: script@v1 with: script: |- pip install scipy==1.3.3 pip install requests==2.22.0 pip install Pillow==6.2.1 cp -R /inputs/repo /stylegan2 cd /stylegan2 python run_generator.py generate-images \ --network=gdrive:networks/stylegan2-ffhq-config-f.pkl \ --seeds=6600-6605 \ --truncation-psi=0.5 \ --result-dir=/outputs/generatedFaces image: tensorflow/tensorflow:1.14.0-gpu-py3 ``` Place the contents in a file named `workflow.yaml`. 5. **Run the Workflow from the CLI** The following command will run an instance of the Workflow in your project. Be sure to replace `` with your **Workflow ID**. ```bash gradient workflows run \ --id \ --path ./workflow.yaml ``` {% hint style="info" %} **Note:** We recommend stashing your API key with `gradient apiKey XXXXXXXXXXXXX` or you can add your API key as an option on each command. See [Connecting Your Account](https://paperspace.gitbook.io/gradient/get-started/install-the-cli#connecting-your-account). {% endhint %} Behind the scenes, your Workflow will be executed on the Gradient public cluster. Congratulations! You ran your first Workflow on Gradient 🚀 ## Explore the rest of the platform From [Models](https://paperspace.gitbook.io/gradient/data/models) to [Deployments](https://docs.paperspace.com/gradient/explore-train-deploy/deployments-preview), there's a lot more to the Gradient platform. We recommend using the Web UI to explore the primary components, including Notebooks, and basic usage of Workflows & Deployments. For more advanced non-GUI-based usage, be sure to install the [CLI](https://paperspace.gitbook.io/gradient/get-started/quick-start/install-the-cli) and check out the [SDK](https://paperspace.gitbook.io/gradient/more/gradient-python-sdk-1).