基于GOOGLE T5中文生成式模型的摘要生成/指代消解,支持batch批量生成,多进程. Contribute to SunnyGJing/t5-pegasus-chinese development by creating an account on GitHub.
At present, the best text summarization model for Chinese is the T5 PEGASUS model, but there are few researches on this model. In this study, the Chinese word segmentation of the T5 PEGASUS model is improved, and the Pkuseg word segmentation method, which is more...
该算法将实体特征融入T5-Pegasus摘要模型中,使模型能够学习新闻中不同词语之间的实体相关性,从而提高摘要的准确性。实验结果表明,与传统的T5-Pegasus模型相比,该模型生成的摘要在ROUGE-1、ROUGE-2和ROUGE-L指标上均有提升,有效提高了事实准确性,生成了更好的文本摘要。 关键词:中文新闻;生成式文本摘要;命名实体识别...
Star Here is 1 public repository matching this topic... Star5 Transformer based abstractive summarization models: mT5, T5 Pegasus, GPT-2 are implemented for Chinese text summarization. pytorchtext-summarizationgpt-2t5t5-pegasus UpdatedMar 21, 2022 ...
https://github.com/renmada/t5-pegasus-pytorchgithub.com/renmada/t5-pegasus-pytorch 因此我们使用这个中文预训练参数即可。 简单使用 那么如何方便的在bert_seq2seq框架中调用t5模型呢? # 加载自己t5代码 from bert_seq2seq.t5_ch import T5Model vocab_path = "./state_dict/t5-chinese/vocab.txt" ...
模型结果文件及相应的日志等信息会自动保存在./models/local_train/pegasus-hp/checkpoint-500 我们可以直接用这个产生的模型文件进行本地推理。注意这里的模型文件地址的指定为你刚刚训练产生的。 AI检测代码解析 import pandas as pd df=pd.read_csv('./data/hp/summary/news_summary_cleaned_small_test.csv') ...
Construct a Pegasus tokenizer. Based on WordPiece.This tokenizer inherits from [`PreTrainedTokenizer`] which contains most of the main methods. Users should refer to this superclass for more information regarding those methods.Args: vocab_file (`str`): ...
natural-language-processingmodel-zoopytorchclassificationbartchinesegptpegasusnercluealbertbertfine-tuningrobertaelmopre-traininggpt-2t5unilmxlm-roberta UpdatedAug 4, 2024 Python shibing624/textgen Star957 Code Issues Pull requests TextGen: Implementation of Text Generation models, include LLaMA, BLOOM, GPT...
nlptransformerscolabbarttransfer-learningpegasussequence-modelsabstractive-summarizationhuggingfacet5-model UpdatedFeb 18, 2021 Python gsarti/it5 Star30 Code Issues Pull requests Materials for "IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation" 🇮🇹 ...
bert_seq2seq的DDP(分布式训练)版本。 此项目是对bert_seq2seq项目的重构并且很好的支持pytorch的DDP多卡训练。examples里面是各种训练例子,data中是样例数据。 本项目可以轻松调用不同种类transformer结构的模型(Bert、Roberta、T5、Nezha、Bart等)针对不同的任务(生成、序列标注、文本分类、关系抽取、命名实体识别等)进...