This package provides a PyTorch implementation of linear-chain conditional random fields (CRF), a class of structured prediction models commonly used in sequence labeling tasks such as named entity recognition and part-of-speech tagging. The implementation builds on the AllenNLP CRF module and extends PyTorch’s neural network capabilities with a dedicated CRF layer. It is available as a standalone Python package for integration into PyTorch-based machine learning pipelines.