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    "info": {
        "author": "Christian Puhrsch",
        "author_email": "cpuhrsch@fb.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Operating System :: MacOS",
            "Operating System :: Microsoft :: Windows",
            "Operating System :: POSIX",
            "Operating System :: Unix",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Scientific/Engineering",
            "Topic :: Software Development"
        ],
        "description": "fastText\n========\n\n`fastText <https://fasttext.cc/>`__ is a library for efficient learning\nof word representations and sentence classification.\n\nRequirements\n------------\n\n`fastText <https://fasttext.cc/>`__ builds on modern Mac OS and Linux\ndistributions. Since it uses C++11 features, it requires a compiler with\ngood C++11 support. These include :\n\n-  (gcc-4.8 or newer) or (clang-3.3 or newer)\n\nYou will need\n\n-  `Python <https://www.python.org/>`__ version 2.7 or >=3.4\n-  `NumPy <http://www.numpy.org/>`__ &\n   `SciPy <https://www.scipy.org/>`__\n-  `pybind11 <https://github.com/pybind/pybind11>`__\n\nBuilding fastText\n-----------------\n\nThe easiest way to get the latest version of `fastText is to use\npip <https://pypi.python.org/pypi/fasttext>`__.\n\n::\n\n    $ pip install fasttext\n\nIf you want to use the latest unstable release you will need to build\nfrom source using setup.py.\n\nNow you can import this library with\n\n::\n\n    import fastText\n\nExamples\n--------\n\nIn general it is assumed that the reader already has good knowledge of\nfastText. For this consider the main\n`README <https://github.com/facebookresearch/fastText/blob/master/README.md>`__\nand in particular `the tutorials on our\nwebsite <https://fasttext.cc/docs/en/supervised-tutorial.html>`__.\n\nWe recommend you look at the `examples within the doc\nfolder <https://github.com/facebookresearch/fastText/tree/master/python/doc/examples>`__.\n\nAs with any package you can get help on any Python function using the\nhelp function.\n\nFor example\n\n::\n\n    +>>> import fastText\n    +>>> help(fastText.FastText)\n\n    Help on module fastText.FastText in fastText:\n\n    NAME\n        fastText.FastText\n\n    DESCRIPTION\n        # Copyright (c) 2017-present, Facebook, Inc.\n        # All rights reserved.\n        #\n        # This source code is licensed under the BSD-style license found in the\n        # LICENSE file in the root directory of this source tree. An additional grant\n        # of patent rights can be found in the PATENTS file in the same directory.\n\n    FUNCTIONS\n        load_model(path)\n            Load a model given a filepath and return a model object.\n\n        tokenize(text)\n            Given a string of text, tokenize it and return a list of tokens\n    [...]\n\nIMPORTANT: Preprocessing data / enconding conventions\n-----------------------------------------------------\n\nIn general it is important to properly preprocess your data. In\nparticular our example scripts in the `root\nfolder <https://github.com/facebookresearch/fastText>`__ do this.\n\nfastText assumes UTF-8 encoded text. All text must be `unicode for\nPython2 <https://docs.python.org/2/library/functions.html#unicode>`__\nand `str for\nPython3 <https://docs.python.org/3.5/library/stdtypes.html#textseq>`__.\nThe passed text will be `encoded as UTF-8 by\npybind11 <https://pybind11.readthedocs.io/en/master/advanced/cast/strings.html?highlight=utf-8#strings-bytes-and-unicode-conversions>`__\nbefore passed to the fastText C++ library. This means it is important to\nuse UTF-8 encoded text when building a model. On Unix-like systems you\ncan convert text using `iconv <https://en.wikipedia.org/wiki/Iconv>`__.\n\nfastText will tokenize (split text into pieces) based on the following\nASCII characters (bytes). In particular, it is not aware of UTF-8\nwhitespace. We advice the user to convert UTF-8 whitespace / word\nboundaries into one of the following symbols as appropiate.\n\n-  space\n-  tab\n-  vertical tab\n-  carriage return\n-  formfeed\n-  the null character\n\nThe newline character is used to delimit lines of text. In particular,\nthe EOS token is appended to a line of text if a newline character is\nencountered. The only exception is if the number of tokens exceeds the\nMAX\\_LINE\\_SIZE constant as defined in the `Dictionary\nheader <https://github.com/facebookresearch/fastText/blob/master/src/dictionary.h>`__.\nThis means if you have text that is not separate by newlines, such as\nthe `fil9 dataset <http://mattmahoney.net/dc/textdata>`__, it will be\nbroken into chunks with MAX\\_LINE\\_SIZE of tokens and the EOS token is\nnot appended.\n\nThe length of a token is the number of UTF-8 characters by considering\nthe `leading two bits of a\nbyte <https://en.wikipedia.org/wiki/UTF-8#Description>`__ to identify\n`subsequent bytes of a multi-byte\nsequence <https://github.com/facebookresearch/fastText/blob/master/src/dictionary.cc>`__.\nKnowing this is especially important when choosing the minimum and\nmaximum length of subwords. Further, the EOS token (as specified in the\n`Dictionary\nheader <https://github.com/facebookresearch/fastText/blob/master/src/dictionary.h>`__)\nis considered a character and will not be broken into subwords.",
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