Gradient Docs
Gradient HomeHelp DeskCommunitySign up free
1.0.0
1.0.0
  • About Paperspace Gradient
  • Get Started
    • Quick Start
    • Core Concepts
    • Install the Gradient CLI
    • Common Errors
  • Tutorials
    • Tutorials List
      • Getting Started with Notebooks
      • Train a Model with the Web UI
      • Train a Model with the CLI
      • Advanced: Distributed training sample project
      • Registering Models in Gradient
      • Using Gradient Deployments
      • Using Custom Containers
  • Notebooks
    • Overview
    • Using Notebooks
      • The Notebook interface
      • Notebook metrics
      • Share a Notebook
      • Fork a Notebook
      • Notebook Directories
      • Notebook Containers
        • Building a Custom Container
      • Notebook Workspace Include Files
      • Community (Public) Notebooks
    • ML Showcase
    • Run on Gradient (GitHub badge)
  • Projects
    • Overview
    • Managing Projects
    • GradientCI
      • GradientCI V1 (Deprecated)
  • Workflows
    • Overview
      • Getting Started with Workflows
      • Workflow Spec
      • Gradient Actions
  • Experiments
    • Overview
    • Using Experiments
      • Containers
      • Single-node & multi-node CLI options
      • Experiment options
      • Gradient Config File
      • Environment variables
      • Experiment datasets
      • Git Commit Tracking
      • Experiment metrics
        • System Metrics
        • Custom Metrics
      • Experiment Logs
      • Experiment Ports
      • GradientCI Experiments
      • Diff Viewer
      • Hyperparameter Tuning
    • Distributed Training
      • Distributed Machine Learning with Tensorflow
      • Distributed Machine Learning with MPI
        • Distributed Training using Horovod
        • Distributed Training Using ChainerMN
  • Jobs
    • Overview
    • Using Jobs
      • Stop a Job
      • Delete a Job
      • List Jobs
      • Job Logs
      • Job Metrics
        • System Metrics
        • Custom Metrics
      • Job Artifacts
      • Public Jobs
      • Building Docker Containers with Jobs
  • Models
    • Overview
    • Managing Models
      • Example: Prepare a TensorFlow Model for Deployments
      • Model Path, Parameters, & Metadata
    • Public Models
  • Deployments
    • Overview
    • Managing Deployments
      • Deployment Containers
        • Custom Deployment Containers
      • Deployment States
      • Deployment Logs
      • Deployment Metrics
      • A Deployed Model's API Endpoint
        • Gradient + TensorFlow Serving
      • Deployment Autoscaling
      • Optimize Models for Inference
  • Data
    • Types of Storage
      • Managing Data in Gradient
        • Managing Persistent Storage with VMs
    • Storage Providers
    • Versioned Datasets
    • Public Datasets Repository
  • TensorBoards
    • Overview
    • Using Tensorboards
      • TensorBoards getting started with Tensorflow
  • Metrics
    • Metrics Overview
    • View and Query Metrics
    • Push Metrics
  • Secrets
    • Overview
    • Using Secrets
  • Gradient SDK
    • Gradient SDK Overview
      • Projects Client
      • Experiments Client
      • Models Client
      • Deployments Client
      • Jobs Client
    • End to end tutorial
    • Full SDK Reference
  • Instances
    • Instance Types
      • Free Instances (Free Tier)
      • Instance Tiers
  • Gradient Cluster
    • Overview
    • Setup
      • Managed Private Clusters
      • Self-Hosted Clusters
        • Pre-installation steps
        • Gradient Installer CLI
        • Terraform
          • Pre-installation steps
          • Install on AWS
          • Install on bare metal / VMs
          • Install on NVIDIA DGX
        • Let's Encrypt DNS Providers
        • Updating your cluster
    • Usage
  • Tags
    • Overview
    • Using Tags
  • Machines (Paperspace CORE)
    • Overview
    • Using Machines
      • Start a Machine
      • Stop a Machine
      • Restart a Machine
      • Update a Machine
      • Destroy a Machine
      • List Machines
      • Show a Machine
      • Wait For a Machine
      • Check a Machine's utilization
      • Check availability
  • Paperspace Account
    • Overview
    • Public Profiles
    • Billing & Subscriptions
    • Hotkeys
    • Teams
      • Creating a Team
      • Upgrading to a Team Plan
  • Release Notes
    • Product release notes
    • CLI/SDK Release notes
Powered by GitBook
On this page
  1. Projects

Overview

PreviousRun on Gradient (GitHub badge)NextManaging Projects

Last updated 3 years ago

This section of the documentation covers our previous generation of Gradient. For the current version go to .

A Gradient Project is a workspace for you or your team to run Experiments and Jobs, store Artifacts such as Models, and manage Deployments (deployed models). You can create a basic "standalone" project or a project which provides more advanced CI/CD pipelining capabilities.

With Standalone Projects, you submit Experiments from the UI or CLI manually. To create a standalone Project via the Paperspace Console:

  1. Begin the Create Project flow and supply a Project name.

  2. Run Experiments manually for the Project via the Experiment Builder or the CLI. See instructions on , and instructions on how to

GradientCI Projects allow you to run Experiments automatically simply by pushing code to a GitHub repository. See for information on setting up our continuous integration service that will run a new experiment whenever:

  1. a new commit is pushed to the linked repo's default branch;

  2. a PR is opened against that default branch;

  3. a commit is pushed to such a PR's branch.

Gradient Next
GradientCI
installing the CLI
GradientCI
run an experiment from the CLI.