PaddleNLP is a development library and toolkit for training, fine-tuning, and deploying large and small language models using the PaddlePaddle framework. It provides a comprehensive suite for the entire natural language processing lifecycle, from model development to high-performance inference.
The project features a standardized model zoo for loading and managing pre-trained models and tokenizers through a unified interface. It distinguishes itself with a specialized model compression framework that reduces memory footprints via weight precision conversion and lossless size optimization, alongside an inference engine that utilizes operator fusion and backend-agnostic execution to increase token generation speed.
The library covers a broad range of capabilities including distributed parallel training, parameter-efficient fine-tuning, and model weight merging. It also supports a full natural language processing pipeline for tasks such as text generation and zero-shot structured information extraction.