dev(narugo): update docs

        - ``embedding``: a 1-dim embedding of image, recommended for index building after L2 normalization

        - ``prediction``: a 1-dim prediction result of image

        You can extract embedding of the given image with the follwing code

        >>> from imgutils.tagging import get_wd14_tags

        >>>

        >>> embedding = get_wd14_tags('skadi.jpg', fmt='embdding')

        >>> embedding.shape

        (1024, )

        This embedding is valuable for constructing indices that enable rapid querying of images based on

        visual features within large-scale datasets.

    Example:

        Here are some images for example

        .. image:: tagging_demo.plot.py.svg

           :align: center

        >>> import os

        >>> from imgutils.tagging import get_wd14_tags

        >>>

        >>> rating, features, chars = get_wd14_tags('skadi.jpg')