Deep Learning & Natural Language Processing: Transformers

From Key

Generate a template with keywords for a new document that is within the domain of existing documents that have been processed, but is not identical to any of them.

Editors can generate frameworks for potential new articles and then have the system rank them for interest before choosing whether or not to assign them.

For example, the system might provide an outline and some major topic points. The key can have specified parameters for semantics, style, or audience.

A second similar but more sophisticated use case I use the same radio buttons but in the output presentation window actually show word level changes to the input document it will bring your closer bring it closer in line to being more likable by the desired demographics. That's in the second case we move from a simple categorization which parts of this document are more likely to reverberate with takeout demographics to the beginnings of a content generation model

Similarly, our radio buttons could correspond to content categories such as “horror movies,” “consumer electronics,” “vegetarian recipes.” In the same manner, the output dined could display the same input with those text passages that score high in the selected categories highlighted in the appropriate color.