《Improving Langugage Understanding by Generative Pre-Tranining》 —— GPT

时间 2021-01-13

标签 nlp论文学习繁體版

原文原文链接

目录《Improving Langugage Understanding by Generative Pre-Tranining》 1、GPT历史意义 2、无监督预训练——通过大量未标记语料学习网络的初始参数 3、Supervised Fine-Tuning 4、Task-specific input transformations 5、实验结果 5.1 模型结构 5.2 GPT模型在不同任务上

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3. 【论文笔记】Improving Language Understanding by Generative Pre-Training
4. 文献阅读笔记—Improving Language Understanding by Generative Pre-Training
5. 深度学习 -- > NLP -- >Improving Language Understanding by Generative Pre-Training
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1. GPT模型：Improving Language Understanding by Generative Pre-Training
2. Improving Language Understanding by Generative Pre-Training阅读笔记
3. 【论文笔记】Improving Language Understanding by Generative Pre-Training
4. 文献阅读笔记—Improving Language Understanding by Generative Pre-Training
5. 深度学习 -- > NLP -- >Improving Language Understanding by Generative Pre-Training
6. OpenAI-GPT（Generative Pre-Training）详解
7. OpenAI GPT解读
8. IMPROVING GENERATIVE ADVERSARIAL NETWORKS WITH DENOISING FEATURE MATCHING（Bingio-ICLR2017）
9. ELMO BERT GPT
10. GAN Dissection: Visualizing and Understanding Generative Adversarial Networks

>>更多相关文章<<