This repository implements ALBERT (A Lite BERT), a parameter-efficient language model architecture, with multiple pre-trained Chinese models. It supports TensorFlow, PyTorch, and Keras frameworks and provides tools for fine-tuning on downstream NLP tasks including text classification and sentence pair classification. The project includes various model sizes from tiny to large variants trained on large-scale Chinese corpora.