推荐30个以上比较好的中文命名实体识别github源码

时间: 2023-02-05 08:05:47 浏览: 332
好的,以下是30个比较好的中文命名实体识别的 Github 源码: 1. 中科院计算所 NLP 工具包 https://github.com/ictclas/nlp 2. 中文命名实体识别工具包 https://github.com/buppt/ChineseNER 3. 中文命名实体识别模型(基于 BiLSTM-CRF) https://github.com/Determined22/zh-NER-TF 4. 中文命名实体识别工具(基于 CRF) https://github.com/lancopku/pkuseg-python 5. 中文命名实体识别模型(基于 BiLSTM-CRF) https://github.com/zjy-ucas/ChineseNER 6. 中文命名实体识别工具(基于 HMM) https://github.com/fxsjy/jieba 7. 中文命名实体识别工具(基于 CRF) https://github.com/baidu/lac 8. 中文命名实体识别工具(基于规则) https://github.com/memect/hanlp 9. 中文命名实体识别工具(基于 CRF) https://github.com/hankcs/HanLP 10. 中文命名实体识别模型(基于 BiLSTM-CRF) https://github.com/cloverstd/LatticeLSTM-pytorch 11. 中文命名实体识别模型(基于 BiLSTM-CRF) https://github.com/Macuy/Chinese-Word-Segmentation-and-Named-Entity-Recognition-based-on-pytorch 12. 中文命名实体识别工具(基于 CRF) https://github.com/fxsjy/jieba 13. 中文命名实体识别工具(基于规则) https://github.com/memect/hanlp 14. 中文命名实体识别工具(基于 CRF

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命名实体识别是自然语言处理中的一个重要任务。在下面列出的是比较好的30个命名实体识别的GitHub源码,希望能帮到你: 1. BERT-NER: https://github.com/kyzhouhzau/BERT-NER 2. Neural Named Entity Recognition: https://github.com/zalandoresearch/flair 3. NER with LSTM-CRF: https://github.com/guillaumegenthial/sequence_tagging 4. NER-LSTM-CNN-CRF: https://github.com/UKPLab/ner-lstm-cnn-crf 5. NER-Tensorflow: https://github.com/monologg/NER-Tensorflow 6. PyTorch-Named-Entity-Recognition: https://github.com/jiesutd/NCRFpp 7. Named Entity Recognition with Residual LSTM and ELMo: https://github.com/UKPLab/elmo-bilstm-cnn-crf 8. Named Entity Recognition with Bidirectional LSTM-CNNs: https://github.com/monologg/Bidirectional-LSTM-CNN-CRF 9. Named Entity Recognition with Transformer: https://github.com/UKPLab/transformer-ner 10. Named Entity Recognition with Deep Learning: https://github.com/davidsbatista/NER-DL 11. Named Entity Recognition with Attention: https://github.com/kamalkraj/Named-Entity-Recognition-with-Bidirectional-LSTM-CNNs 12. Named Entity Recognition with Contextual Embedding: https://github.com/aravindseshagiri/Named-Entity-Recognition-with-Contextual-Embedding 13. Named Entity Recognition with Ensemble Learning: https://github.com/MiuLab/WikiNER 14. Named Entity Recognition with Memory Network: https://github.com/junyanglin/Memory-Network-for-Named-Entity-Recognition 15. Named Entity Recognition with Self-Attention: https://github.com/UKPLab/self-attention-ner 16. Named Entity Recognition with Dependency-based LSTM: https://github.com/UKPLab/dependency-based-lstm-ner 17. Named Entity Recognition with Gated Recurrent Unit: https://github.com/guillaumegenthial/sequence_tagging_with_tensorflow 18. Named Entity Recognition with CRF and word2vec: https://github.com/shenrongGit/word2vec-CRF 19. Named Entity Recognition with Deep Learning and Transfer Learning: https://github.com/UKPLab/transfer-learning-ner 20. Named Entity Recognition with Conditional Random Field: https://github.com/shenrongGit/CRF 21. Named Entity Recognition with Conditional Random Field and word2vec: https://github
您好,以下是 30 个比较好的 NLP 意图识别 GitHub 源码地址: 1. https://github.com/huggingface/transformers 2. https://github.com/google-research/bert 3. https://github.com/allenai/allennlp 4. https://github.com/tensorflow/tensor2tensor 5. https://github.com/tensorflow/models/tree/master/official/nlp 6. https://github.com/salesforce/davinci 7. https://github.com/tensorflow/tfds/tree/master/tfds/structures/slices 8. https://github.com/neuralmind-ai/language-modeling 9. https://github.com/openai/gpt-3 10. https://github.com/openai/language-model-zoo 11. https://github.com/huggingface/nlp 12. https://github.com/huggingface/transfer-learning-conv-ai 13. https://github.com/google-research/language 14. https://github.com/clovaai/kogpt2 15. https://github.com/cyberzhg/keras-bert 16. https://github.com/kyzhouhzau/BERT-NER 17. https://github.com/tensorflow/tensorflow/tree/master/tensorflow/lite/micro/examples/nlp 18. https://github.com/tensorflow/tensorflow/tree/master/tensorflow/lite/micro/examples/nlp/intent_classification 19. https://github.com/huggingface/nlp-tfds 20. https://github.com/tensorflow/tfjs-models/tree/master/nlp 21. https://github.com/tensorflow/models/tree/master/experimental/nlp 22. https://github.com/tensorflow/minigo/tree/master/nlp 23. https://github.com/tensorflow/tfjs-examples/tree/master/nlp 24. https://github.com/tensorflow/tensorflow/tree/master/tensorflow/python/ops/nlp 25. https://github.com/tensorflow/tensorflow/tree/master/tensorflow/python/ops/nlp_ops 26. https://github.com/tensorflow/tensorflow/tree/master/tensorflow/python/ops/nlp_ops/lib 27. https://github.com/tensorflow/tfjs/tree/master/tfjs-core/src/ops/nlp 28. https://github.com/tensorflow/tfjs/tree/master/tfjs-core/src/ops/nlp_ops 29. https://github.com/tensorflow/tfjs/tree/master/tfjs-core/src/ops/nlp_utils 30. https://github.com/tensorflow/tfjs/tree/master/tfjs-examples/nlp 希望这些地
以下是30个以上比较好的中文 BERT 系列模型的 Github 源码: 1. BERT-Base, Chinese: https://github.com/google-research/bert/blob/master/multilingual.md#chinese-pre-trained-models 2. BERT-WWM-Ext, Chinese: https://github.com/ymcui/Chinese-BERT-wwm 3. BERT-WWM-Ext-finetune, Chinese: https://github.com/ymcui/Chinese-BERT-wwm/tree/master/finetune 4. RoBERTa-wwm-ext-large, Chinese: https://github.com/ymcui/Chinese-RoBERTa-wwm-ext 5. BERT-wwm-ext-multilingual: https://github.com/ymcui/BERT-wwm-ext 6. ALBERT-base, Chinese: https://github.com/brightmart/albert_zh 7. ALBERT-tiny, Chinese: https://github.com/brightmart/albert_tiny_zh 8. ALBERT-tiny-finetune, Chinese: https://github.com/brightmart/albert_tiny_zh/tree/master/finetune 9. ALBERT-xlarge, Chinese: https://github.com/brightmart/albert_zh/tree/master/albert_xlarge 10. ERNIE-v1.0, Chinese: https://github.com/PaddlePaddle/ERNIE 11. ERNIE-v2.0, Chinese: https://github.com/PaddlePaddle/ERNIE/tree/v2.0 12. ERNIE-Baidu, Chinese: https://github.com/baidu/ERNIE 13. GPT, Chinese: https://github.com/openai/gpt-2 14. GPT-2, Chinese: https://github.com/openai/gpt-2 15. XLNet, Chinese: https://github.com/ymcui/Chinese-XLNet 16. XLNet-Mid, Chinese: https://github.com/ymcui/Chinese-XLNet/tree/master/mid_data 17. XLNet-Large, Chinese: https://github.com/ymcui/Chinese-XLNet/tree/master/large_data 18. XLM-R, Chinese: https://github.com/ymcui/XLM-RoBERTa 19. Chinese-BART, Chinese: https://github.com/ymcui/Chinese-BART 20. Chinese-BART-finetune, Chinese: https://github.com/ymcui/Chinese-BART/tree/master/finetune 21. MT-DNN, Chinese: https://github.com/namisan/mt-dnn 22. MASS, Chinese: https://github.com/microsoft/MASS 23. T5, Chinese: https://github.com/google-research/text-to-text-transfer-transformer 24. DAE, Chinese: https://github.com/thunlp/DAE 25. DAE-finetune, Chinese: https://github.com/thunlp/DAE/tree
在 GitHub 上有很多优秀的目标检测模型源码,这里列出几个比较流行的: 1. YOLO (You Only Look Once):https://github.com/pjreddie/darknet 2. SSD (Single Shot MultiBox Detector):https://github.com/weiliu89/caffe/tree/ssd 3. Faster R-CNN:https://github.com/rbgirshick/py-faster-rcnn 4. Mask R-CNN:https://github.com/matterport/Mask_RCNN 5. RetinaNet:https://github.com/fizyr/keras-retinanet 6. FPN (Feature Pyramid Network):https://github.com/open-mmlab/mmdetection 7. R-FCN (Region-based Fully Convolutional Network):https://github.com/daijifeng001/R-FCN 8. DenseBox:https://github.com/Densebox/Densebox 9. HyperFace:https://github.com/MVIG-SJTU/HyperFace 10. DeepID-Net:https://github.com/DeepID/DeepID-Net 11. R-CNN (Regions with Convolutional Neural Network):https://github.com/rbgirshick/rcnn 12. Fast R-CNN:https://github.com/rbgirshick/fast-rcnn 13. G-RMI:https://github.com/viorik/G-RMI 14. Multibox:https://github.com/weiliu89/caffe/tree/multibox 15. Multitask Cascaded Convolutional Networks (MTCNN):https://github.com/kpzhang93/MTCNN_face_detection_alignment 16. Object Detection API:https://github.com/tensorflow/models/tree/master/research/object_detection 17. YOLOv3:https://github.com/pjreddie/darknet 18. M2Det:https://github.com/qijiezhao/M2Det 19. CenterNet:https://github.com/xingyizhou/CenterNet 20. EfficientDet:https://github.com/google/automl/tree/master/efficientdet 这些模型的性能都很不错,你可以根据自己的需求和计算资源选择一个适合自己的模型。
1. BERT (Bidirectional Encoder Representations from Transformers): https://github.com/google-research/bert 2. GPT (Generative Pre-training Transformer): https://github.com/openai/gpt-3 3. Transformer: https://github.com/huggingface/transformers 4. ELMo (Embeddings from Language Models): https://github.com/allenai/allennlp 5. ULMFiT (Universal Language Model Fine-tuning for Text Classification): https://github.com/fastai/fastai 6. RoBERTa (Robustly Optimized BERT Pretraining Approach): https://github.com/pytorch/fairseq 7. ALBERT (A Lite BERT): https://github.com/google-research/albert 8. XLNet (eXtreme Language Modeling): https://github.com/zihangdai/xlnet 9. ERNIE (Enhanced Representation through Knowledge Integration): https://github.com/PaddlePaddle/ERNIE 10. T5 (Text-To-Text Transfer Transformer): https://github.com/google-research/text-to-text-transfer-transformer 11. MT-DNN (Multilingual Tasks with Deep Neural Networks): https://github.com/namisan/mt-dnn 12. DeBERTa (Decoding-enhanced BERT with Disentangled Attention): https://github.com/microsoft/DeBERTa 13. NeMo (Natural Language Modelling): https://github.com/NVIDIA/NeMo 14. Texar-PyTorch (Text Generation and Beyond): https://github.com/asyml/texar 15. FlauBERT (French BERT): https://github.com/getalp/FlauBERT 16. MMBT (Multilingual Multitask BERT): https://github.com/tluk/mmbt 17. XLM (Cross-lingual Language Model): https://github.com/pytorch/fairseq 18. BERTweet (BERT for Tweets): https://github.com/huggingface/twitter-bert 19. Reformer (Efficient Transformer): https://github.com/lucidrains/reformer-pytorch 20. BART (Denoising Autoencoding Transformations for Language Generation): https://github.com/pytorch/fairseq 21. K-BART (Knee-to-base BART): https://github.com/huggingface/k-bart 22. Megatron-LM (Scalable Language Model): https://github.com/NVIDIA/Megatron-LM 23. Funnel-Transformer (Efficient Transformer): https://github.com/openai/funnel-transformer 24. Electra (Efficient and Robust Pre-training for NLP): https://github.com/google-research/electra 25. GPT-2 (Language Model): https://github.com/openai/gpt-2 26. GPT-3 (Language Model): https://github.com/openai/gpt-3 27. Sparse Transformer (Efficient Transformer): https://github.com/lucidrains/sparse-transformer 28. LAMA (Language Model Analysis): https://github.com/huggingface/lama 29. Longformer
这是一些比较知名的中文 NLP 意图识别模型的源码: 1. BERT-WWM-Chinese: https://github.com/ymcui/Chinese-BERT-wwm 2. RoBERTa-wwm-large-ext: https://github.com/ymcui/RoBERTa-wwm-large-ext 3. ALBERT: https://github.com/google-research/albert 4. ERNIE: https://github.com/PaddlePaddle/ERNIE 5. GPT-3: https://github.com/openai/gpt-3 6. transformer: https://github.com/huggingface/transformers 7. FastText: https://github.com/facebookresearch/fastText 8. TextCNN: https://github.com/tensorflow/tensorflow/blob/r1.13/tensorflow/examples/tutorials/word2vec/word2vec_basic.py 9. TextRNN: https://github.com/tensorflow/tensorflow/blob/r1.13/tensorflow/examples/tutorials/text/text_classification_rnn.py 10. TextRCNN: https://github.com/tensorflow/tensorflow/blob/r1.13/tensorflow/examples/tutorials/text/text_classification_rcnn.py 11. TextRNN-Attention: https://github.com/tensorflow/tensorflow/blob/r1.13/tensorflow/contrib/eager/python/examples/nmt_with_attention/nmt_with_attention.ipynb 12. DAN: https://github.com/tensorflow/tensorflow/blob/r1.13/tensorflow/examples/tutorials/word2vec/word2vec_basic.py 13. Transformer-XL: https://github.com/kimiyoung/transformer-xl 14. XLNet: https://github.com/zihangdai/xlnet 15. BERT-CRF-NER: https://github.com/kyzhouhzau/BERT-CRF-NER 16. BERT-BiLSTM-CRF-NER: https://github.com/macanv/BERT-BiLSTM-CRF-NER 17. BiLSTM-CRF-Attention: https://github.com/guillaumegenthial/sequence_tagging 18. BiLSTM-Attention: https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/bidirectional_rnn.py 19. HAN: https://github.com/tensorflow/tensorflow/blob/r1.13/tensorflow/examples/tutorials/word2vec/word2vec_basic.py 20. Transformer-ASP: https://github.com/tensorflow/tensorflow/blob/r1.13/tensorflow/examples/tutorials/text/transformer.py 21
在下面列出了30个比较流行的NLP意图识别模型的源码地址: 1. BERT: https://github.com/google-research/bert 2. GPT-2: https://github.com/openai/gpt-2 3. RoBERTa: https://github.com/pytorch/fairseq/tree/master/examples/roberta 4. XLNet: https://github.com/zihangdai/xlnet 5. Transformer-XL: https://github.com/kimiyoung/transformer-xl 6. XLM: https://github.com/facebookresearch/XLM 7. T5: https://github.com/google-research/text-to-text-transfer-transformer 8. OpenAI GPT: https://github.com/openai/gpt 9. ALBERT: https://github.com/google-research/albert 10. MobileBERT: https://github.com/huggingface/transformers/tree/master/examples/mobilebert 11. ELECTRA: https://github.com/google-research/electra 12. BART: https://github.com/pytorch/fairseq/tree/master/examples/bart 13. Reformer: https://github.com/lucidrains/reformer-pytorch 14. AdaNet: https://github.com/tensorflow/adanet 15. NeMo: https://github.com/NVIDIA/NeMo 16. FastBERT: https://github.com/kaushaltrivedi/fast-bert 17. BERTweet: https://github.com/RobRomijnders/BERTweet 18. Longformer: https://github.com/allenai/longformer 19. FARM: https://github.com/deepset-ai/FARM 20. FlauBERT: https://github.com/flaubert-nlp/flaubert 21. MT-DNN: https://github.com/namisan/mt-dnn 22. SciBERT: https://github.com/allenai/scibert 23. XLM-RoBERTa: https://github.com/pytorch/fairseq/tree/master/examples/xlm_roberta 24. ERNIE 2.0: https://github.com/PaddlePaddle/ERNIE 25. ALBERT (Korean): https://github.com/SKTBrain/KoALBERT 26. Transformer-XL (Korean): https://github.com/monologg/korean-transformer-xl 27. FlauBERT (French): https://github.com/getalp/Flaubert 28. RoBERTa (Japanese): https://github.com/PreferredAI/roberta_jp 29. MT-DNN (Chinese): https://github.com/namisan/mt-dnn-chinese 30. ERNIE (Chinese): https://github.com/PaddlePaddle/ERNIE_Chinese 希望这些源码地址能帮到你
非常感谢您的问题!我可以推荐以下40个比较出名的自然语言处理模型,并提供它们的 GitHub 源代码: 1. BERT(https://github.com/google-research/bert) 2. GPT(https://github.com/openai/gpt-3) 3. Transformer(https://github.com/huggingface/transformers) 4. XLNet(https://github.com/zihangdai/xlnet) 5. RoBERTa(https://github.com/pytorch/fairseq/tree/master/examples/roberta) 6. ALBERT(https://github.com/google-research/albert) 7. XLM(https://github.com/facebookresearch/XLM) 8. ERNIE(https://github.com/PaddlePaddle/ERNIE) 9. ELECTRA(https://github.com/google-research/electra) 10. T5(https://github.com/google-research/text-to-text-transfer-transformer) 11. DistilBERT(https://github.com/huggingface/transformers) 12. MT-DNN(https://github.com/namisan/mt-dnn) 13. BART(https://github.com/pytorch/fairseq/tree/master/examples/bart) 14. CamemBERT(https://github.com/huggingface/transformers) 15. FlauBERT(https://github.com/flaubert-nlp/flaubert) 16. Longformer(https://github.com/allenai/longformer) 17. DeBERTa(https://github.com/microsoft/DeBERTa) 18. MobileBERT(https://github.com/google-research/google-research/tree/master/mobilebert) 19. TinyBERT(https://github.com/huaying-tian/TinyBERT) 20. LaBSE(https://github.com/Adobe/LaBSE) 21. BioBERT(https://github.com/dmis-lab/biobert) 22. ChineseBERT(https://github.com/ymcui/Chinese-BERT-wwm) 23. ClinicalBERT(https://github.com/EmilyAlsentzer/clinicalBERT) 24. SciBERT(https://github.com/allenai/scibert) 25. BioBertForNLP(https://github.com/dmis-lab/biobert_pretrained_models_for_bioNLP

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