Skip to main content

Paperspace Python

Project description

GitHubSplash

Gradient CLI

PyPI Downloads


Get started: Create AccountInstall CLITutorialsDocs

Resources: WebsiteBlogSupportContact Sales


Gradient is an an end-to-end MLOps platform that enables individuals and organizations to quickly develop, train, and deploy Deep Learning models. The Gradient software stack runs on any infrastructure e.g. AWS, GCP, on-premise and low-cost Paperspace GPUs. Leverage automatic versioning, distributed training, built-in graphs & metrics, hyperparameter search, GradientCI, 1-click Jupyter Notebooks, our Python SDK, and more.

Key components:

  • Notebooks: 1-click Jupyter Notebooks.
  • Workflows: Train models at scale with composable actions.
  • Inference: Deploy models as API endpoints.

Gradient supports any ML/DL framework (TensorFlow, PyTorch, XGBoost, etc).


See releasenotes.md for details on the current release, as well as release history.


Getting Started

  1. Make sure you have a Paperspace account set up. Go to http://paperspace.com to register and generate an API key.

  2. Use pip, pipenv, or conda to install the gradient package, e.g.:

    pip install -U gradient

    To install/update prerelease (Alpha/Beta) version version of gradient, use:

    pip install -U --pre gradient

  3. Set your api key by executing the following:

    gradient apiKey <your-api-key-here>

    Note: your api key is cached in ~/.paperspace/config.json

    You can remove your cached api key by executing:

    gradient logout

Executing tasks on Gradient

The Gradient CLI follows a standard [command] [--options] syntax

For example, to create a new Deployment use:

gradient workflows create [type] [--options]

For a full list of available commands run gradient workflows --help. You can also view more info about Workflows in the docs.

Contributing

Want to contribute? Contact us at hello@paperspace.com

Pre-Release Testing

Have a Paperspace QA tester install your change directly from the branch to test it. They can do it with pip install git+https://github.com/Paperspace/gradient-cli.git@MYBRANCH.

Project details


Release history Release notifications | RSS feed

This version

1.9.0

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

gradient-1.9.0.tar.gz (157.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

gradient-1.9.0-py2.py3-none-any.whl (236.6 kB view details)

Uploaded Python 2Python 3

File details

Details for the file gradient-1.9.0.tar.gz.

File metadata

  • Download URL: gradient-1.9.0.tar.gz
  • Upload date:
  • Size: 157.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.0 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.6.15

File hashes

Hashes for gradient-1.9.0.tar.gz
Algorithm Hash digest
SHA256 47be02511d7ea66a13559598851cb435d435fb3f7676f6de17292d06daad8947
MD5 3ad404b57a66c17dca66271c0f202649
BLAKE2b-256 96e702892cf1be663395e8ef65bed7804eebad4c8b72ab2609fc550e2b4367fe

See more details on using hashes here.

File details

Details for the file gradient-1.9.0-py2.py3-none-any.whl.

File metadata

  • Download URL: gradient-1.9.0-py2.py3-none-any.whl
  • Upload date:
  • Size: 236.6 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.0 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.6.15

File hashes

Hashes for gradient-1.9.0-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 800624ece9b7656c6785d1769108ce67ab0888b57017a8357c52f00c54f6cd0c
MD5 bf58c8c04b158169e5f8b3f01ecbd243
BLAKE2b-256 7347f21fbc9a90567babe23cf0f709ce7d96aaf898d311e85dcf79f7fabbd010

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page