lightNLP

Why we included this project

lightNLP is a compact PyTorch and torchtext framework for people who want to learn Chinese NLP by reading and running real model code. It covers a broad set of tasks, including named entity recognition, part-of-speech tagging, word segmentation, dependency parsing, relation extraction, sentence similarity, text classification, and word2vec-style embeddings, all behind the same train/test/predict interface. The author is upfront that this is a learning-oriented collection rather than a production service: it ships no pretrained models or tuned parameters, so the value is in studying and adapting the code, not deploying it as is. For developers coming from other fields, the bundled demos and the lightnlp-cookbook documentation make it easy to work through each task end to end and swap in your own data.