Inference with state-of-the-art models (pre-trained by LD-Net / AutoNER / VanillaNER / ...)
$ git clone https://github.com/LiyuanLucasLiu/LightNER.gitKashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.
Empower Sequence Labeling with Task-Aware Language Model
The BiLSTM-CRF model implementation in Tensorflow, for sequence labeling tasks.
Learning Named Entity Tagger from Domain-Specific Dictionary
a Deep Learning Framework for Text https://delft.readthedocs.io/
Macadam是一个以Tensorflow(Keras)和bert4keras为基础，专注于文本分类、序列标注和关系抽取的自然语言处理工具包。支持RANDOM、WORD2VEC、FASTTEXT、BERT、ALBERT、ROBERTA、NEZHA、XLNET、ELECTRA、GPT-2等EMBEDDING嵌入; 支持FineTune、FastText、TextCNN、CharCNN、BiRNN、RCNN、DCNN、CRNN、DeepMoji、SelfAttention、HAN、Capsule等文本分类算法; 支持CRF、Bi-LSTM-CRF、CNN-LSTM、DGCNN、Bi-LSTM-LAN、Lattice-LSTM-Batch、MRC等序列标注算法。
Data from GitHub · snapshot Sep 24, 2026