Xplique (pronounced \ɛks.plik\) is a Python toolkit dedicated to explainability, currently based on Tensorflow. The goal of this library is to gather the state of the art of Explainable AI to help you understand your complex neural network models. The library is composed of several modules, the Attributions Methods module implements various methods (e.g Saliency, Grad-CAM, Integrated-Gradients...), with explanations, examples and links to official papers. The Feature Visualization module allows to see how neural networks build their understanding of images by finding inputs that maximize neurons, channels, layers or compositions of these elements. The Concepts module allows you to extract human concepts from a model and to test their usefulness with respect to a class.