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            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
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        "description": "# Modelforge [![docs on gitbook](https://img.shields.io/badge/docs-gitbook-brightgreen.svg)](https://docs.sourced.tech/modelforge/) [![Build Status](https://travis-ci.com/src-d/modelforge.svg)](https://travis-ci.com/src-d/modelforge) [![codecov](https://codecov.io/github/src-d/modelforge/coverage.svg)](https://codecov.io/gh/src-d/modelforge) [![PyPI](https://img.shields.io/pypi/v/modelforge.svg)](https://pypi.python.org/pypi/modelforge)\n\nModelforge is a foundation for sharing trained machine learning models. It is a set of command line\ntools and a Python library. Modelforge maintains model files in a third-party remote storage service\n(\"cloud\") using the backend mechanism. Model metadata (download links, names, descriptions, versions,\netc.) resides in a Git repository called the \"Index\", and documentation is automatically generated\nthere. Modelforge does no assumptions about the models: they can be of any origin, such as TensorFlow,\nscikit-learn, or your custom. The underlying model storage format -\n[Advanced Scientific Data Format](https://github.com/spacetelescope/asdf) - can wrap any data\neasily and efficiently, but it's the developer's responsibility to convert.\n\nLearn more about:\n\n* [Why?](doc/why.md) - what problem Modelforge tries to solve.\n* [Modelforge model](doc/model.md) - what is a model in Modelforge context.\n* [Model storage format](doc/model_storage_format.md) - low-level serialization details.\n* [Backends](doc/backends.md) - extension system to upload and download models from clouds.\n* [Git Index](doc/git_index.md) - how documentation about the models is generated from the structured metadata.\n* [Command line tools](doc/cmdline.md) - how to perform typical operations.\n* [API](doc/api.md) - Modelforge API for developers.\n\n#### Who uses Modelforge?\n\n* source{d}, in [src-d/ml](https://github.com/src-d/ml) and [src-d/lookout-sdk-ml](https://github.com/src-d/lookout-sdk-ml); the public index is [src-d/models](https://github.com/src-d/models).\n\n## Install\n\nYou can run Modelforge through Docker:\n```\ndocker run -it --rm srcd/modelforge --help\n```\n\nor install it using the [Python package manager](https://github.com/pypa/pip):\n\n```\npip3 install modelforge\n```\n\n## Usage\n\nThe project exposes two interfaces: [command line](doc/cmdline.md) and [API](doc/api.md).\n\n## Contributions\n\nContributions are pretty much welcome! Please follow the [contributions guide](doc/contributing.md)\nand the [code of conduct](doc/code_of_conduct.md).\n\nIf you wish to make your MLonCode model available in [src-d/models](https://github.com/src-d/models),\nplease  fork that repository and run `modelforge publish` to upload your model on your fork. Then\ncreate a pull request. You should provide read access to the model file for everybody. If you\nconsider using our Google Cloud Storage bucket, feel free to contact us through GitHub issues.\n\n## License\n\n[Apache 2.0](LICENSE).\n\n\n",
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