提交 9d96c205 编写于 作者: Z Zeyu Chen

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简体中文 | [English](./README_en.md) 简体中文 | [English](./README_en.md)
<p align="center"> <p align="center">
<img src="https://paddlenlp.bj.bcebos.com/images/paddlenlp.png" width="520" height ="100" align="middle" /> <img src="./docs/imgs/paddlenlp.png" width="520" height ="100" />
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...@@ -27,7 +27,7 @@ PaddleNLP旨在帮助开发者提高文本建模的效率,通过丰富的模 ...@@ -27,7 +27,7 @@ PaddleNLP旨在帮助开发者提高文本建模的效率,通过丰富的模
- 通过高度优化的Transformer网络实现,结合混合精度与Fleet分布式训练API,可充分利用GPU集群资源,高效完成预训练模型的分布式训练。 - 通过高度优化的Transformer网络实现,结合混合精度与Fleet分布式训练API,可充分利用GPU集群资源,高效完成预训练模型的分布式训练。
# 安装 # 安装
## 环境依赖 ## 环境依赖
...@@ -36,7 +36,7 @@ PaddleNLP旨在帮助开发者提高文本建模的效率,通过丰富的模 ...@@ -36,7 +36,7 @@ PaddleNLP旨在帮助开发者提高文本建模的效率,通过丰富的模
- paddlepaddle >= 2.0.0-rc1 - paddlepaddle >= 2.0.0-rc1
``` ```
pip install paddlenlp==2.0.0b pip install paddlenlp==2.0.0b
``` ```
...@@ -110,7 +110,7 @@ electra = ElectraModel.from_pretrained('chinese-electra-small') ...@@ -110,7 +110,7 @@ electra = ElectraModel.from_pretrained('chinese-electra-small')
- [Models API](./docs/models.md) - [Models API](./docs/models.md)
# 可交互式Notebook教程 # 可交互式Notebook教程
...@@ -131,7 +131,7 @@ electra = ElectraModel.from_pretrained('chinese-electra-small') ...@@ -131,7 +131,7 @@ electra = ElectraModel.from_pretrained('chinese-electra-small')
- 现在就加入PaddleNLP的QQ技术交流群,一起交流NLP技术吧!⬇️ - 现在就加入PaddleNLP的QQ技术交流群,一起交流NLP技术吧!⬇️
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<img src="https://paddlenlp.bj.bcebos.com/images/qq.png" width="200" height="200" /> <img src="./docs/imgs/qq.png" width="200" height="200" />
</div> </div>
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English | [简体中文] (./README.md) English | [简体中文] (./README.md)
<p align="center">
<img src="./docs/imgs/paddlenlp.png" width="520" height ="100" />
</p>
# PaddleNLP # PaddleNLP
![License](https://img.shields.io/badge/license-Apache%202-red.svg) ![License](https://img.shields.io/badge/license-Apache%202-red.svg)
...@@ -81,33 +85,34 @@ For more pretrained model selection, please refer to [PretrainedModels](./paddle ...@@ -81,33 +85,34 @@ For more pretrained model selection, please refer to [PretrainedModels](./paddle
## API Usage ## API Usage
* [Transformer API](./docs/transformers.md)
* [Dataset API](./docs/datasets.md)
* [Embedding API](./docs/embeddings.md)
* [Metrics API](./docs/embeddings.md)
* [Models API](./docs/models.md)
- [Transformer API](./docs/transformers.md)
- [Dataset API](./docs/datasets.md)
- [Embedding API](./docs/embeddings.md)
- [Metrics API](./docs/embeddings.md)
- [Models API](./docs/models.md)
## Tutorials ## Tutorials
Please refer to our official AI Studio account for more interactive tutorials: [PaddleNLP on AI Studio](https://aistudio.baidu.com/aistudio/personalcenter/thirdview/574995) Please refer to our official AI Studio account for more interactive tutorials: [PaddleNLP on AI Studio](https://aistudio.baidu.com/aistudio/personalcenter/thirdview/574995)
* [paddlenlp.seq2vec是什么? 瞧瞧它怎么完成情感分析教程](https://aistudio.baidu.com/aistudio/projectdetail/1294333) shows how to use lstm to do sentiment analysis. * [What's Seq2Vec?](https://aistudio.baidu.com/aistudio/projectdetail/1294333) shows how to use LSTM to do sentiment analysis.
* [使用PaddleNLP语义预训练模型ERNIE优化情感分析教程](https://aistudio.baidu.com/aistudio/projectdetail/1283423) shows how to exploit the pretrained ERNIE to make sentiment analysis better. * [Sentiment Analysis with ERNIE](https://aistudio.baidu.com/aistudio/projectdetail/1283423) shows how to exploit the pretrained ERNIE to make sentiment analysis better.
* [基于Bi-GRU+CRF的快递单信息抽取](https://aistudio.baidu.com/aistudio/projectdetail/1317771) shows how to make use of bigru and crf to do information extraction. * [Waybill Information Extraction with BiGRU-CRF Model](https://aistudio.baidu.com/aistudio/projectdetail/1317771) shows how to make use of bigru and crf to do information extraction.
* [使用PaddleNLP预训练模型ERNIE优化快递单信息抽取](https://aistudio.baidu.com/aistudio/projectdetail/1329361) shows how to exploit the pretrained ERNIE to do information extraction better. * [Waybill Information Extraction with ERNIE](https://aistudio.baidu.com/aistudio/projectdetail/1329361) shows how to exploit the pretrained ERNIE to do information extraction better.
## Community ## Community
* SIG for Pretrained Model Contribution Join our QQ Technical Group to
* SIG for Dataset Integration
* SIG for Tutorial Writing
## License ## License
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