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![](\"https://img.shields.io/badge/slack-runwayml.slack.com-33b279.svg\"){kind=icon}
\n\nThe Runway Model SDK allows you to port new and existing machine learning models to the Runway platform. With a few lines of code, you can modify your Python model to be used and shared by others on [Runway](https://runwayml.com).\n\n## Installing\n\nThe SDK supports Python 3.6+. You can install the module using either pip or pip3 like so:\n\n```\npip3 install runway-python\n```\n\nNow head over to [the sdk docs](https://sdk.runwayml.com) to learn how to use the Runway Model SDK.\n\n## Docs\n\nReference and documentation for the Runway Model SDK is hosted at [sdk.runwayml.com](https://sdk.runwayml.com). These docs provide an overview of how to use the SDK to port your own ML models.\n\nThe [Runway Model Template repo](https://github.com/runwayml/model-template) also contains a simple example of how to get started porting a model to Runway.\n\nSee the *Importing Models into Runway* [tutorial](https://docs.runwayapp.ai/#/importing) for a walk-through illustrating how to port a model to Runway.\n\n## Developing\n\nIf you'd like to contribute to the development of the Runway Python SDK, you can clone and modify this repository by following the instructions below.\n\n```bash\ngit clone https://github.com/runwayml/model-sdk runway-model-sdk\ncd runway-model-sdk\n\n## optionally use a virtual environment\n# virtualenv -p python3 venv && source venv/bin/activate\n\n# install dependencies\npython3 setup.py install\n\n# install the dev dependencies\nmake dev\n```\n\n### Testing\n\nAutomated tests for the Runway Model SDK are written using `pytest` and live in the `tests/` directory. We also provide support for code coverage via `pytest-cov`. \n\n```bash\n## Create and activate a python3 virtual environment if you need to.\n# virtualenv -p python3 venv && source ./venv/bin/activate\n\n# make sure you have the development dependencies installed\nmake dev\n\n# run the tests\nmake test\n\n# by default pytest suppresses stdout and stderr during testing, so run tests\n# like this if you'd like to see the output from your print() statements during\n# testing\nmake test-debug\n\n# to generate coverage statistics while running tests, use this command.\n# it prints test coverage to the console and also generates a more detailed HTML\n# report in htmlcov/.\nmake coverage\n```\n\nIf you make a PR against this repo, please be sure to include automated tests to validate that your code works as expected. PRs will be automatically blocked by a [Codecov](https://codecov.io/) bot if their changes reduce the overall test coverage of the Runway Model SDK package.\n\n### Building the Docs\n\nThe Model SDK documentation is generated from inline source code using docstrings, [Sphinx](http://www.sphinx-doc.org/en/master/), and a modified Read the Docs HTML theme. The version of Sphinx that we are using (v2.0.1) requires Python 3.\n\n```bash\n## Create and activate a python3 virtual environment if you need to.\n# virtualenv -p python3 venv && source ./venv/bin/activate\n\n# make sure you have the docs dependencies installed\nmake dev-docs\n\n# build the docs\nmake docs\n```\n\nYour auto-generated HTML docs should now appear in `docs/build/html`.\n\n### Questions\n\nWe have a `#model-sdk` channel in our public [Slack](https://runwayml.com/joinslack) workspace that you can use to ask questions or chat with the Runway team about this Python module. Feel free to open an issue as well!\n\n\n",
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