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        "description": ".. _Tutorial: https://kur.deepgram.com/tutorial.html\n\n******************************\nKur: Descriptive Deep Learning\n******************************\n\nIntroduction\n============\n\nWelcome to Kur! You've found the future of deep learning!\n\n- Install Kur easily with ``pip install kur``.\n- Design, train, and evaluate models *without ever needing to code*.\n- Describe your model with easily understandable concepts.\n- Quickly explore better versions of your model with the power of the `Jinja2\n  <http://jinja.pocoo.org>`_ templating engine.\n- Supports Theano, TensorFlow, and PyTorch, and supports **multi-GPU**\n  out-of-the-box.\n- **COMING SOON**: Share your models with the community, making it incredibly\n  easy to collaborate on sophisticated models.\n\nGo ahead and give it a whirl: `Get the Code`_ and then jump into\nthe `Examples`_! Then build your own model in our Tutorial_. Remember to check\nout our `homepage <https://kur.deepgram.com>`_ for complete documentation and\nthe newest news.\n\nWhat is Kur?\n------------\n\nKur is a system for quickly building and applying state-of-the-art deep\nlearning models to new and exciting problems. Kur was designed to appeal to the\nentire machine learning community, from novices to veterans. It uses\nspecification files that are simple to read and author, meaning that you can\nget started building sophisticated models *without ever needing to code*. Even\nso, Kur exposes a friendly and extensible API to support advanced deep learning\narchitectures or workflows. Excited? Jump straight into the `Examples`_.\n\n.. _get_the_code:\n\nGet the Code\n============\n\nKur is really easy to install! You can pick either one of these two options for\ninstalling Kur.\n\n**NOTE**: Kur requires **Python 3.4** or greater. Take a look at our\n`installation guide <https://kur.deepgram.com/install.html>`_ for\nstep-by-step instructions for installing Kur and setting up a `virtual\nenvironment <https://virtualenv.pypa.io/>`_.\n\nLatest Pip Release\n------------------\n\nIf you know what you are doing, then this is easy:\n\n.. code-block:: bash\n\n\tpip install kur\n\nLatest Development Release\n--------------------------\n\nJust check it out and run the setup script:\n\n.. code-block:: bash\n\n\tgit clone https://github.com/deepgram/kur\n\tcd kur\n\tpip install .\n\n**Quick Start**: Or, if you already have `Python 3 installed\n<https://kur.deepgram.com/installing.html>`_, then here's a few quick-start\nlines to get you training your first model:\n\n**Quick Start For Using pip:**\n\n.. code-block:: bash\n\n\tpip install virtualenv                      # Make sure virtualenv is present\n\tvirtualenv -p $(which python3) ~/kur-env    # Create a Python 3 environment for Kur\n\t. ~/kur-env/bin/activate                    # Activate the Kur environment\n\tpip install kur                             # Install Kur\n\tkur --version                               # Check that everything works\n\tgit clone https://github.com/deepgram/kur   # Get the examples\n\tcd kur/examples                             # Change directories\n\tkur train mnist.yml                         # Start training!\n\n**Quick Start For Using git:**\n\n.. code-block:: bash\n\n\tpip install virtualenv                      # Make sure virtualenv is present\n\tvirtualenv -p $(which python3) ~/kur-env    # Create a Python 3 environment for Kur\n\t. ~/kur-env/bin/activate                    # Activate the Kur environment\n\tgit clone https://github.com/deepgram/kur   # Check out the latest code\n\tcd kur                                      # Change directories\n\tpip install .                               # Install Kur\n\tkur --version                               # Check that everything works\n\tcd examples                                 # Change directories\n\tkur train mnist.yml                         # Start training!\n\nUsage\n-----\n\nIf everything has gone well, you shoud be able to use Kur:\n\n.. code-block:: bash\n\n\tkur --version\n\nYou'll typically be using Kur in commands like ``kur train model.yml`` or ``kur\ntest model.yml``. You'll see these in the `Examples`_, which is\nwhere you should head to next!\n\nTroubleshooting\n---------------\n\nIf you run into any problems installing or using Kur, please check out our\n`troubleshooting <https://kur.deepgram.com/troubleshooting.html>`_ page for\nlots of useful help. And if you want more detailed installation instructions,\nwith help on setting up your environment, before sure to see our `installation\n<https://kur.deepgram.com/installing.html>`_ page.",
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