Texar-PyTorch provides modular components for composing machine learning models, especially for natural language processing and text generation tasks. It integrates TensorFlow design patterns into PyTorch, offering highly customizable layers, modules, and functionalities for model building and experimentation. The toolkit supports popular models like BERT, GPT-2, RoBERTa, and XLNet, targeting researchers and practitioners for fast prototyping.