Keras-text is a text classification library that implements various state-of-the-art neural network models with a clean and extendable interface. It provides tokenizers for words, characters, and sentences, a dataset abstraction for managing training/test splits, and model factories for building classification architectures including YoonKimCNN and attention-based models. The library builds on top of Keras, TensorFlow, and Theano backends.