Paperspace Python
Project description
Gradient CLI
Get started: Create Account • Install CLI • Tutorials • Docs
Resources: Website • Blog • Support • Contact 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.
- Experiments: Run experiments from a web interface, CLI, SDK, or GradientCI bot.
- Models: Store, analyze, and version models.
- 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
-
Make sure you have a Paperspace account set up. Go to http://paperspace.com to register and generate an API key.
-
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
-
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 experiment use:
gradient experiments create [type] [--options]
The two available experiment types are singlenode
and multinode
. Various command options include setting the instance type, container, project, etc. Note that some options are required to create new experiment.
For a full list of available commands run gradient experiments --help
. You can also view more info about Experiments 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
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for gradient-1.4.2-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 40b25309ee6473ccb820be1b8ff5b173ae90419c968e9de38ee9810fc5f8f671 |
|
MD5 | 641791bccfbd0a234f6e91e1085dbc69 |
|
BLAKE2b-256 | d507b057c06608c57c0e765b1db9bd2b5c71bef3e084951540edc906c5f7e108 |