We use existing machine learning neural style transfer model, differential rasterizer, for colored font design. The input of the proposed system is an existing TrueType font and the output is an neural style transferred OpenType-SVG color font. Each character glyph contains a series of vector graphics path elements. A neural style transferred glyph consists of dozens of random Bézier curves initially distributed among the glyph space, gradually converging to glyph stokes of a given character. In contract, the process of designing a font manually requires specialized skills for designers. They use mouse cursor to adjust strokes and glyph kerning for each character. It require hours to achieve a specific style. A Chinese font contains thousands of characters. Neural style transfer techniques can be used to speed up the process for designing decorative fonts. In addition, we add different colors to the curves in a an neural style transfer character for visual appealing. In order to support colors in a font, we choose OpenType-SVG format, allowing displaying colors in software like Illustrator or Inkscape. We open-source our code at https://github.com/su8691/ribbon.