From b28b862f630de939c6d2ed66b42ff74e95059a26 Mon Sep 17 00:00:00 2001 From: Zeyu Chen Date: Thu, 17 Dec 2020 21:39:00 +0800 Subject: [PATCH] Update README.md --- PaddleNLP/README.md | 115 ++++++++++++++++++++++++++------------------ 1 file changed, 68 insertions(+), 47 deletions(-) diff --git a/PaddleNLP/README.md b/PaddleNLP/README.md index e3ce07f8..580a03b2 100644 --- a/PaddleNLP/README.md +++ b/PaddleNLP/README.md @@ -1,55 +1,60 @@ 简体中文 | [English](./README_en.md) -# PaddleNLP +

+ +

+ + +PaddleNLP旨在帮助开发者提高文本建模的效率，通过丰富的模型库、简洁易用的API，提供飞桨2.0的最佳实践并加速NLP领域应用产业落地效率。 ![License](https://img.shields.io/badge/license-Apache%202-red.svg) ![python version](https://img.shields.io/badge/python-3.6+-orange.svg) ![support os](https://img.shields.io/badge/os-linux%2C%20win%2C%20mac-yellow.svg) -## Introduction -PaddleNLP aims to accelerate NLP applications through powerful model zoo, easy-to-use API with detailed tutorials, It's also the NLP best practice for PaddlePaddle 2.0 API system. +# 特性 + +- **丰富的模型库** + + - 涵盖了NLP主流应用相关的前沿模型，包括中文词向量、预训练模型、词法分析、文本分类、文本匹配、文本生成、机器翻译、通用对话、问答系统等。 + +- **简洁易用的API** -**This project is still UNDER ACTIVE DEVELOPMENT.** + - 深度兼容飞桨2.0的高层API体系，提供更多可复用的文本建模模块，可大幅度减少数据处理、组网、训练环节的代码开发，提高开发效率。 -## Features +- **高性能分布式训练** -* **Rich and Powerful Model Zoo** - - Our Model Zoo covers mainstream NLP applications, including Lexical Analysis, Syntactic Parsing, Machine Translation, Text Classification, Text Generation, Text Matching, General Dialogue and Question Answering etc. -* **Easy-to-use API** - - The API is fully integrated with PaddlePaddle high-level API system. It minimizes the number of user actions required for common use cases like data loading, text pre-processing, training and evaluation. which enables you to deal with text problems more productively. -* **High Performance and Large-scale Training** - - We provide a highly optimized ditributed training implementation for BERT with Fleet API, it can fully utilize GPU clusters for large-scale model pre-training. Please refer to our [benchmark](./benchmark/bert) for more information. -* **Detailed Tutorials and Industrial Practices** - - We offers detailed and interactable notebook tutorials to show you the best practices of PaddlePaddle 2.0. + - 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。 -## Installation -### Prerequisites + +# 安装 -* python >= 3.6 -* paddlepaddle >= 2.0.0-rc1 +## 环境依赖 + +- python >= 3.6 +- paddlepaddle >= 2.0.0-rc1 ``` -pip install paddlenlp>=2.0.0a +pip install paddlenlp==2.0.0b ``` -## Quick Start -### Quick Dataset Loading +# 快速开始 + +## 数据集快速加载 ```python from paddlenlp.datasets import ChnSentiCrop -train_ds, test_ds = ChnSentiCorp.get_datasets(['train','test']) +train_dataset, dev_dataset, test_dataset= ChnSentiCorp.get_datasets(['train', 'dev', 'test']) ``` -For more Dataset API usage, please refer to [Dataset API](./docs/datasets.md). +可参考[Dataset文档](./docs/datasets.md)查看更多数据集。 -### Chinese Text Emebdding Loading +## 一键加载中文词向量 ```python - from paddlenlp.embeddings import TokenEmbedding wordemb = TokenEmbedding("w2v.baidu_encyclopedia.target.word-word.dim300") @@ -59,9 +64,9 @@ wordemb.cosine_sim("艺术", "火车") >>> 0.14792643 ``` -For more token embedding usage, please refer to [examples/word_embedding](./example/../examples/word_embedding/README.md). +内置50+中文词向量，更多使用方法请参考 [Embedding文档](./examples/word_embedding/README.md)。 -### One-Line Classical Model Building +## 一键加载经典模型 ```python from paddlenlp.models import Ernie, Senta, SimNet @@ -71,49 +76,65 @@ ernie = Ernie("ernie-1.0", num_classes=2, task="seq-cls") senta = Senta(network="bow", vocab_size=1024, num_classes=2) simnet = SimNet(network="gru", vocab_size=1024, num_classes=2) - ``` -### Rich Chinsese Pre-trained Models +更多使用方法请参考[Models API](./docs/models.md)。 + +## 一键加载高质量中文预训练模型 ```python from paddlenlp.transformers import ErnieModel, BertModel, RobertaModel, ElectraModel ernie = ErnieModel.from_pretrained('ernie-1.0') + bert = BertModel.from_pretrained('bert-wwm-chinese') + roberta = RobertaModel.from_pretrained('roberta-wwm-ext') + electra = ElectraModel.from_pretrained('chinese-electra-small') ``` -For more pretrained model selection, please refer to [Pretrained-Models](./docs/transformers.md) +请参考 [Pretrained-Models](./docs/transformers.md)查看目前支持的预训练模型。 + + + +# API 使用文档 + +- [Transformer API](./docs/transformers.md) + +- [Dataset API](./docs/datasets.md) + +- [Embedding API](./docs/embeddings.md) -## API Usage +- [Metrics API](./docs/embeddings.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) +- [Models API](./docs/models.md) -## 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) +# 可交互式Notebook教程 -* [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. +- [使用seq2vec模块进行句子情感分类](https://aistudio.baidu.com/aistudio/projectdetail/1283423) +- [如何将预训练模型Fine-tune下游任务](https://aistudio.baidu.com/aistudio/projectdetail/1294333) +- [使用Bi-GRU+CRF完成快递单信息抽取](https://aistudio.baidu.com/aistudio/projectdetail/1317771) +- [使用预训练模型ERNIE优化快递单信息抽取](https://aistudio.baidu.com/aistudio/projectdetail/1329361) +- [使用Seq2Seq模型完成自动对联模型](https://aistudio.baidu.com/aistudio/projectdetail/1321118) +- [使用预训练模型ERNIE-GEN实现智能写诗](https://aistudio.baidu.com/aistudio/projectdetail/1339888) +- [使用TCN网络完成新冠疫情病例数预测](https://aistudio.baidu.com/aistudio/projectdetail/1290873) -* [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. +更多教程参见[PaddleNLP on AI Studio](https://aistudio.baidu.com/aistudio/personalcenter/thirdview/574995)。 -* [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. -* [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. +# 社区贡献与技术交流 +- 欢迎您加入PaddleNLP的SIG社区，贡献优秀的模型实现、公开数据集、教程与案例、外围小工具。 +- 现在就加入我们的QQ技术交流群，一起交流NLP技术！⬇️ -## Community +
+ +
-* SIG for Pretrained Model Contribution -* SIG for Dataset Integration -* SIG for Tutorial Writing -## License +# License -PaddleNLP is provided under the [Apache-2.0 License](./LICENSE). +PaddleNLP遵循[Apache-2.0开源协议](./LICENSE)。 -- GitLab