Building a text classification model with TensorFlow Hub and Estimators

We often see transfer learning applied to computer vision models, but what about using it for text classification? Enter TensorFlow Hub, a library for enhancing your TF models with transfer learning. Transfer learning is the process of taking the weights and variables of a pre-existing model that has already been trained on lots of data and leveraging it for your own data and prediction task. One of the many benefits of transfer learning is that you don't need to provide as much of your own training data as you would if you were starting from scratch. But where do these pre-existing models come from?