update model zoo and exmaple readme

PaddleNLP/README.md

@@ -81,7 +81,7 @@ gpt2 = GPT2ForPretraining.from_pretrained('gpt2-base-cn')
 ## 模型库及其应用
 
 PaddleNLP模型库整体介绍请参考文档[PaddleNLP Model Zoo](./docs/model_zoo.md).
-模型应用场景介绍请参考[examples](./examples/README.md):
+模型应用场景介绍请参考[PaddleNLP Examples](./examples/README.md):
 
 - [词向量](./examples/word_embedding/README.md)
 - [词法分析](./examples/lexical_analysis/README.md)

PaddleNLP/docs/model_zoo.md

@@ -23,17 +23,17 @@ PaddleNLP提供了丰富的模型结构，包含经典的RNN类模型结构，
 
 | 模型    |  简介   |
 | ------ | ------ |
-| [Transformer](../examples/lexical_analysis) | BiGRU-CRF是一个经典的词法分析模型，可用于中文分词、词性标注和命名实体识别等任务。     |
-| [Transformer-XL](../examples/language_model/transformer-xl/) | 最基础的序列特征提取模型，对序列内所有词向量进行线性求和或取平均的操作。     |
+| [Transformer](../examples/machine_translation/transformer/) | [Attention Is All You Need](https://arxiv.org/abs/1706.03762)     |
+| [Transformer-XL](../examples/language_model/transformer-xl/) | [Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context](https://arxiv.org/abs/1901.02860)     |
 | [BERT](../examples/language_model/bert/) |[BERT(Bidirectional Encoder Representation from Transformers)](./examples/language_model/bert)      |
 | [ERNIE](../examples/text_classification/rnn) | [ERNIE: Enhanced Representation through Knowledge Integration](https://arxiv.org/abs/1904.09223)   |
-| [ERNIE-Tiny](../examples/language_model/gpt2) | 百度自研的小型化ERNIE网络结构，采用浅层Transformer，加宽隐层参数，中文subword粒度词表结合蒸馏的方法使模型相比SOTA Before BERT 提升8.35%， 速度提升4.3倍。 |
-| [ERNIE-GEN](../examples/language_model/gpt2) | [ERNIE-GEN: An Enhanced Multi-Flow Pre-training and Fine-tuning Framework for Natural Language Generation](https://arxiv.org/abs/2001.11314) ERNIE-GEN是百度发布的生成式预训练模型，通过Global-Attention的方式解决训练和预测曝光偏差的问题，同时使用Multi-Flow Attention机制来分别进行Global和Context信息的交互，同时通过片段生成的方式来增加语义相关性。    |
+| [ERNIE-Tiny](../examples/text_classification/rnn) | 百度自研的小型化ERNIE网络结构，采用浅层Transformer，加宽隐层参数，中文subword粒度词表结合蒸馏的方法使模型相比SOTA Before BERT 提升8.35%， 速度提升4.3倍。 |
+| [ERNIE-GEN](../examples/text_generation/ernie-gen) | [ERNIE-GEN: An Enhanced Multi-Flow Pre-training and Fine-tuning Framework for Natural Language Generation](https://arxiv.org/abs/2001.11314) ERNIE-GEN是百度发布的生成式预训练模型，通过Global-Attention的方式解决训练和预测曝光偏差的问题，同时使用Multi-Flow Attention机制来分别进行Global和Context信息的交互，同时通过片段生成的方式来增加语义相关性。    |
 | [ERNIESage](../examples/text_graph/erniesage)| ERNIESage(ERNIE SAmple aggreGatE) 通过Graph(图)来构建自身节点和邻居节点的连接关系，将自身节点和邻居节点的关系构建成一个关联样本输入到ERNIE中，ERNIE作为聚合函数 (Aggregators) 来表征自身节点和邻居节点的语义关系，最终强化图中节点的语义表示。|
-| [GPT-2](../examples/language_model/gpt2) | 单/双向GRU序列特征提取器，是变种的LSTM结构，计算量相比LSTM较少。    |
+| [GPT-2](../examples/language_model/gpt2) |[Language Models are Unsupervised Multitask Learners](https://d4mucfpksywv.cloudfront.net/better-language-models/language-models.pdf)   |
 | [ELECTRA](../examples/language_model/electra/) | [ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators](https://arxiv.org/abs/2003.10555)   |
 | [RoBERTa](../examples/text_classification/rnn) | [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://arxiv.org/abs/1907.11692)   |
-| [PLATO-2](../examples/dialogue/plato-2) | 百度自研领先的开放域对话预训练模型。[PLATO-2: Towards Building an Open-Domain Chatbot via Curriculum Learning](https://arxiv.org/abs/2006.16779) |
+| [PLATO-2](../examples/dialogue/plato-2) | 百度自研领先的开放域对话预训练模型 [PLATO-2: Towards Building an Open-Domain Chatbot via Curriculum Learning](https://arxiv.org/abs/2006.16779) |
 | [SentenceBERT](../examples/text_matching/sentence_transformers)| [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://arxiv.org/abs/1908.10084) |