Python-用BERT进行序列标记和文本分类的模板代码

[{"title":"（ 89 个子文件 2.47MB ） Python-用BERT进行序列标记和文本分类的模板代码","children":[{"title":"BERT-for-Sequence-Labeling-and-Text-Classification-master","children":[{"title":"bert","children":[{"title":"run_squad.py <span style='color:#111;'> 45.44KB </span>","children":null,"spread":false},{"title":"multilingual.md <span style='color:#111;'> 11.03KB </span>","children":null,"spread":false},{"title":"tokenization.py <span style='color:#111;'> 11.97KB </span>","children":null,"spread":false},{"title":"run_classifier.py <span style='color:#111;'> 33.97KB </span>","children":null,"spread":false},{"title":"run_pretraining.py <span style='color:#111;'> 18.23KB </span>","children":null,"spread":false},{"title":"create_pretraining_data.py <span style='color:#111;'> 14.88KB </span>","children":null,"spread":false},{"title":"modeling.py <span style='color:#111;'> 37.03KB </span>","children":null,"spread":false},{"title":"tokenization_test.py <span style='color:#111;'> 4.42KB </span>","children":null,"spread":false},{"title":"requirements.txt <span style='color:#111;'> 110B </span>","children":null,"spread":false},{"title":"extract_features.py <span style='color:#111;'> 13.57KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 616B </span>","children":null,"spread":false},{"title":"optimization_test.py <span style='color:#111;'> 1.68KB </span>","children":null,"spread":false},{"title":"optimization.py <span style='color:#111;'> 6.11KB </span>","children":null,"spread":false},{"title":"modeling_test.py <span style='color:#111;'> 8.98KB </span>","children":null,"spread":false},{"title":"CONTRIBUTING.md <span style='color:#111;'> 1.29KB </span>","children":null,"spread":false},{"title":"sample_text.txt <span style='color:#111;'> 4.29KB </span>","children":null,"spread":false},{"title":"LICENSE <span style='color:#111;'> 11.09KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 41.77KB </span>","children":null,"spread":false},{"title":"run_classifier_with_tfhub.py <span style='color:#111;'> 9.33KB </span>","children":null,"spread":false},{"title":"predicting_movie_reviews_with_bert_on_tf_hub.ipynb <span style='color:#111;'> 64.93KB </span>","children":null,"spread":false},{"title":".gitignore <span style='color:#111;'> 1.33KB </span>","children":null,"spread":false}],"spread":false},{"title":"pretrained_model","children":[{"title":"uncased_L-12_H-768_A-12","children":[{"title":"bert_config.json <span style='color:#111;'> 313B </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"run_sequence_labeling.py <span style='color:#111;'> 33.62KB </span>","children":null,"spread":false},{"title":"Usage example 使用方法示例.ipynb <span style='color:#111;'> 10.58KB </span>","children":null,"spread":false},{"title":"output","children":[{"title":"atis_join_task_epoch10_test1399ckpt","children":[{"title":"intent_prediction_test_results.txt <span style='color:#111;'> 11.31KB </span>","children":null,"spread":false},{"title":"slot_filling_test_results.txt <span style='color:#111;'> 94.98KB </span>","children":null,"spread":false}],"spread":true},{"title":"conll2003ner_epoch3_test653ckpt","children":[{"title":".ipynb_checkpoints","children":[{"title":"slot_filling_test_results-checkpoint.txt <span style='color:#111;'> 250.65KB </span>","children":null,"spread":false}],"spread":true},{"title":"predict.tf_record <span style='color:#111;'> 1005.00KB </span>","children":null,"spread":false},{"title":"label2id.pkl <span style='color:#111;'> 200B </span>","children":null,"spread":false},{"title":"model_score_log.txt <span style='color:#111;'> 1.39KB </span>","children":null,"spread":false},{"title":"token_test.txt <span style='color:#111;'> 253.09KB </span>","children":null,"spread":false},{"title":"slot_filling_test_results.txt <span style='color:#111;'> 250.65KB </span>","children":null,"spread":false}],"spread":true},{"title":"snips_join_task_epoch10_test4088ckpt","children":[{"title":"predict.tf_record <span style='color:#111;'> 466.05KB </span>","children":null,"spread":false},{"title":"log.txt <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"intent_prediction_test_results.txt <span style='color:#111;'> 9.86KB </span>","children":null,"spread":false},{"title":"intent_label2id.pkl <span style='color:#111;'> 163B </span>","children":null,"spread":false},{"title":"slot_filling_test_results.txt <span style='color:#111;'> 67.48KB </span>","children":null,"spread":false},{"title":"slot_label2id.pkl <span style='color:#111;'> 1.61KB </span>","children":null,"spread":false}],"spread":true},{"title":"score_summarization.py <span style='color:#111;'> 868B </span>","children":null,"spread":false}],"spread":true},{"title":"run_slot_intent_join_task_LSTM.py <span style='color:#111;'> 45.50KB </span>","children":null,"spread":false},{"title":"LICENSE <span style='color:#111;'> 11.09KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 5.46KB </span>","children":null,"spread":false},{"title":"data","children":[{"title":"snips_Intent_Detection_and_Slot_Filling","children":[{"title":"train","children":[{"title":"seq.in <span style='color:#111;'> 602.62KB </span>","children":null,"spread":false},{"title":"seq.out <span style='color:#111;'> 928.64KB </span>","children":null,"spread":false},{"title":"label <span style='color:#111;'> 180.21KB </span>","children":null,"spread":false}],"spread":true},{"title":"valid","children":[{"title":"seq.in <span style='color:#111;'> 32.84KB </span>","children":null,"spread":false},{"title":"seq.out <span style='color:#111;'> 49.44KB </span>","children":null,"spread":false},{"title":"label <span style='color:#111;'> 9.67KB </span>","children":null,"spread":false}],"spread":true},{"title":"test","children":[{"title":"seq.in <span style='color:#111;'> 32.34KB </span>","children":null,"spread":false},{"title":"seq.out <span style='color:#111;'> 49.72KB </span>","children":null,"spread":false},{"title":"label <span style='color:#111;'> 9.88KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"atis_Intent_Detection_and_Slot_Filling","children":[{"title":"train","children":[{"title":"check_train_raw_data.py <span style='color:#111;'> 173B </span>","children":null,"spread":false},{"title":"seq.in <span style='color:#111;'> 283.05KB </span>","children":null,"spread":false},{"title":"seq.out <span style='color:#111;'> 405.82KB </span>","children":null,"spread":false},{"title":"label <span style='color:#111;'> 56.48KB </span>","children":null,"spread":false}],"spread":true},{"title":"valid","children":[{"title":"seq.in <span style='color:#111;'> 31.99KB </span>","children":null,"spread":false},{"title":"seq.out <span style='color:#111;'> 46.64KB </span>","children":null,"spread":false},{"title":"label <span style='color:#111;'> 6.37KB </span>","children":null,"spread":false}],"spread":true},{"title":"test","children":[{"title":"seq.in <span style='color:#111;'> 50.90KB </span>","children":null,"spread":false},{"title":"seq.out <span style='color:#111;'> 79.33KB </span>","children":null,"spread":false},{"title":"label <span style='color:#111;'> 11.36KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"CoNLL2003_NER","children":[{"title":"train","children":[{"title":"seq.in <span style='color:#111;'> 1.04MB </span>","children":null,"spread":false},{"title":"seq.out <span style='color:#111;'> 535.10KB </span>","children":null,"spread":false}],"spread":true},{"title":"test.txt <span style='color:#111;'> 730.56KB </span>","children":null,"spread":false},{"title":"train.txt <span style='color:#111;'> 3.13MB </span>","children":null,"spread":false},{"title":"conll03_raw_data_to_stand_file.py <span style='color:#111;'> 1.55KB </span>","children":null,"spread":false},{"title":"valid","children":[{"title":"seq.in <span style='color:#111;'> 269.07KB </span>","children":null,"spread":false},{"title":"seq.out <span style='color:#111;'> 135.14KB </span>","children":null,"spread":false}],"spread":false},{"title":"test","children":[{"title":"seq.in <span style='color:#111;'> 240.77KB </span>","children":null,"spread":false},{"title":"seq.out <span style='color:#111;'> 123.28KB </span>","children":null,"spread":false}],"spread":false},{"title":"dev.txt <span style='color:#111;'> 808.05KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"calculate_model_score.py <span style='color:#111;'> 25.48KB </span>","children":null,"spread":false},{"title":"calculating_model_score","children":[{"title":"tf_metrics.py <span style='color:#111;'> 8.00KB </span>","children":null,"spread":false},{"title":"calculate_atis_intent.py <span style='color:#111;'> 1.37KB </span>","children":null,"spread":false},{"title":"calculate_snips_slot.py <span style='color:#111;'> 5.26KB </span>","children":null,"spread":false},{"title":"sklearn_metrics_function.py <span style='color:#111;'> 2.12KB </span>","children":null,"spread":false},{"title":"snips_sequence_labeling_and_text_classification_test7","children":[{"title":"log.txt <span style='color:#111;'> 12.56KB </span>","children":null,"spread":false},{"title":"model_score_log.txt <span style='color:#111;'> 20.66KB </span>","children":null,"spread":false},{"title":"intent_prediction_test_results.txt <span style='color:#111;'> 9.85KB </span>","children":null,"spread":false},{"title":"slot_filling_test_results.txt <span style='color:#111;'> 67.39KB </span>","children":null,"spread":false}],"spread":false},{"title":"calculate_snpis_intent.py <span style='color:#111;'> 858B </span>","children":null,"spread":false},{"title":"snips_join_task_epoch10_test4088ckpt","children":[{"title":"intent_prediction_test_results.txt <span style='color:#111;'> 9.86KB </span>","children":null,"spread":false},{"title":"slot_filling_test_results.txt <span style='color:#111;'> 67.48KB </span>","children":null,"spread":false}],"spread":false},{"title":"calculate_snips_intent_and_slot_new.py <span style='color:#111;'> 6.12KB </span>","children":null,"spread":false},{"title":"calculate_snips_intent_and_slot.py <span style='color:#111;'> 6.66KB </span>","children":null,"spread":false},{"title":"calculate_model_score.py <span style='color:#111;'> 11.92KB </span>","children":null,"spread":false},{"title":"calculate_atis_slot.py <span style='color:#111;'> 9.92KB </span>","children":null,"spread":false}],"spread":false},{"title":"run_sequence_labeling_and_text_classification.py <span style='color:#111;'> 44.95KB </span>","children":null,"spread":false},{"title":"run_text_classification.py <span style='color:#111;'> 40.20KB </span>","children":null,"spread":false}],"spread":false}],"spread":true}]