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    "info": {
        "author": "Adrian Viehweger",
        "author_email": "adrian.viehweger@googlemail.com",
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            "License :: OSI Approved :: MIT License",
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        "description": "## nanotext\n\nName inspired by [`fastText`](https://fasttext.cc/).\n\nRun tests: \n\n\n```bash\ncd .../nanotext/\npytest  # or python setup.py test\n```\n\n\n```\nTODO: turn embedding in gensim fmt into something similar to glove (bin?)\nwould then be easier to train/ unfreeze and then save again, to be loaded w/ some model eg for PUL prediction\n\nhttps://github.com/plasticityai/magnitude\n\nnanotext compute\n\ntakes annotation (load domains) and our model and computes vector\n\nnanotext train corpus model\n\nnanotext compare ...\n\nnanotext search ...\n\nnanotext taxonomy (calculate a gtdb based taxonomy and get closest functional genome and use that or distance)\n\nlike sourmash really\n\n\n\ncheck sourmash publication\n\nnanotext predict model=medium\nnanotext predict model=pul\n```\n\n",
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        "summary": "Domains as words, genomes as documents.",
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