LM-LSTM-CRF documentation

Check Our New NER Toolkit🚀🚀🚀

  • Inference:
    • LightNER: inference w. models pre-trained / trained w. any following tools, efficiently.
  • Training:
    • LD-Net: train NER models w. efficient contextualized representations.
    • VanillaNER: train vanilla NER models w. pre-trained embedding.
  • Distant Training:
    • AutoNER: train NER models w.o. line-by-line annotations and get competitive performance.

This project provides high-performance character-aware sequence labeling tools, including [Training](#usage), [Evaluation](#evaluation) and [Prediction](#prediction).

Details about LM-LSTM-CRF can be accessed here, and the implementation is based on the PyTorch library.

Indices and tables