In this entry, I am going to talk about deep learning models exposure and serving via Tensorflow, while showcasing my setup for a flexible and practical text generation solution.

With text generation I intend the automated task of generating new semantically valid pieces of text of variable length, given an optional seed string. The idea is to be able to avail of different models for different use-cases (Q&A, chatbot-utilities, simplification, next word(s) suggestion) also based on different type of content (e.g. narrative, scientific, code), sources or authors.

Check out the article on Medium.