The Berkeley Neural Parser implements self-attentive encoders for high-accuracy constituency parsing, based on ACL 2018 and 2018b research papers. It provides pre-trained models for 11 languages and supports custom model training. Users can integrate with spaCy or use the parser directly via PyTorch, with automatic GPU acceleration when available.