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‎.gitignore‎

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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.nox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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.hypothesis/
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.pytest_cache/
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# Translations
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*.mo
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*.pot
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# Django stuff:
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*.log
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local_settings.py
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db.sqlite3
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# Flask stuff:
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instance/
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.webassets-cache
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# Scrapy stuff:
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.scrapy
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# Sphinx documentation
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docs/_build/
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# PyBuilder
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target/
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# Jupyter Notebook
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.ipynb_checkpoints
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# IPython
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profile_default/
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ipython_config.py
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# pyenv
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.python-version
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# celery beat schedule file
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celerybeat-schedule
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# SageMath parsed files
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*.sage.py
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# Environments
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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# Spyder project settings
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.spyderproject
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.spyproject
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# Rope project settings
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.ropeproject
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# mkdocs documentation
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/site
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# mypy
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.mypy_cache/
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.dmypy.json
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dmypy.json
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# Pyre type checker
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.pyre/
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# pycharm
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.DS_Store
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.idea/
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FETCH_HEAD
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# vscode
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.vscode

‎.pre-commit-config.yaml‎

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- repo: https://github.com/PaddlePaddle/mirrors-yapf.git
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sha: 0d79c0c469bab64f7229c9aca2b1186ef47f0e37
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hooks:
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- id: yapf
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files: \.py$
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- repo: https://github.com/pre-commit/pre-commit-hooks
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sha: a11d9314b22d8f8c7556443875b731ef05965464
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hooks:
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- id: check-merge-conflict
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- id: check-symlinks
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- id: detect-private-key
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files: (?!.*paddle)^.*$
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- id: end-of-file-fixer
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files: \.md$
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- id: trailing-whitespace
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files: \.md$
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- repo: https://github.com/Lucas-C/pre-commit-hooks
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sha: v1.0.1
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hooks:
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- id: forbid-crlf
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files: \.md$
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- id: remove-crlf
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files: \.md$
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- id: forbid-tabs
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files: \.md$
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- id: remove-tabs
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files: \.md$
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- repo: local
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hooks:
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- id: clang-format
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name: clang-format
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description: Format files with ClangFormat
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entry: bash .clang_format.hook -i
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language: system
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files: \.(c|cc|cxx|cpp|cu|h|hpp|hxx|cuh|proto)$

‎.style.yapf‎

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[style]
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based_on_style = pep8
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column_limit = 80

‎LICENSE‎

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Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved
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Apache License
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Version 2.0, January 2004
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http://www.apache.org/licenses/
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same "printed page" as the copyright notice for easier
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identification within third-party archives.
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Copyright [yyyy] [name of copyright owner]
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Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.

‎README.md‎

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# PaddleNLP
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简体中文 | [English](./README_en.md)
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<p align="center">
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<img src="./docs/imgs/paddlenlp.png" width="520" height ="100" />
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</p>
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------------------------------------------------------------------------------------------
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![License](https://img.shields.io/badge/license-Apache%202-red.svg)
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![python version](https://img.shields.io/badge/python-3.6+-orange.svg)
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![support os](https://img.shields.io/badge/os-linux%2C%20win%2C%20mac-yellow.svg)
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## 简介
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PaddleNLP 2.0拥有丰富的模型库、简洁易用的API与高性能的分布式训练的能力，旨在为飞桨开发者提升文本建模效率，并提供基于PaddlePaddle 2.0的NLP领域最佳实践。
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## 特性
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- **丰富的模型库**
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- 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，更多详细介绍请查看[PaddleNLP模型库](./docs/model_zoo.md)。
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- **简洁易用的API**
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- 深度兼容飞桨2.0的高层API体系，提供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量，提升文本建模开发效率。
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- **高性能分布式训练**
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- 通过深度优化的混合精度训练策略与Fleet分布式训练API，可充分利用GPU集群资源，高效完成大规模预训练模型的分布式训练。
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## 安装
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### 环境依赖
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- python >= 3.6
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- paddlepaddle >= 2.0.0
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```
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pip install paddlenlp==2.0.0rc
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```
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## 快速开始
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### 数据集快速加载
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```python
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from paddlenlp.datasets import ChnSentiCorp
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train_ds, dev_ds, test_ds = ChnSentiCorp.get_datasets(['train', 'dev', 'test'])
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```
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可参考[Dataset文档](./docs/datasets.md)查看更多数据集。
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### 一键加载中文词向量
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```python
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from paddlenlp.embeddings import TokenEmbedding
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wordemb = TokenEmbedding("w2v.baidu_encyclopedia.target.word-word.dim300")
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print(wordemb.cosine_sim("国王", "王后"))
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>>> 0.63395125
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wordemb.cosine_sim("艺术", "火车")
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>>> 0.14792643
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```
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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)。
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### 一键加载高质量中文预训练模型
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```python
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from paddlenlp.transformers import ErnieModel, BertModel, RobertaModel, ElectraModel, GPT2ForPretraining
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ernie = ErnieModel.from_pretrained('ernie-1.0')
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bert = BertModel.from_pretrained('bert-wwm-chinese')
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roberta = RobertaModel.from_pretrained('roberta-wwm-ext')
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electra = ElectraModel.from_pretrained('chinese-electra-small')
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gpt2 = GPT2ForPretraining.from_pretrained('gpt2-base-cn')
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```
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请参考 [Pretrained-Models](./docs/transformers.md)查看目前支持的预训练模型。
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## 模型库及其应用
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PaddleNLP模型库整体介绍请参考文档[PaddleNLP Model Zoo](./docs/model_zoo.md).
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模型应用场景介绍请参考[PaddleNLP Examples](./examples/README.md)。
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- [词向量](./examples/word_embedding/README.md)
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- [词法分析](./examples/lexical_analysis/README.md)
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- [语言模型](./examples/language_model)
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- [文本分类](./examples/text_classification/README.md)
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- [文本生成](./examples/text_generation/README.md)
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- [语义匹配](./examples/text_matching/README.md)
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- [命名实体识别](./examples/named_entity_recognition/README.md)
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- [文本图学习](./examples/text_graph/erniesage/README.md)
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- [通用对话](./examples/dialogue)
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- [机器翻译](./examples/machine_translation)
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- [阅读理解](./examples/machine_reading_comprehension)
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## 进阶应用
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- [模型压缩](./examples/model_compression/)
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## API 使用文档
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- [Transformer API](./docs/transformers.md)
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* 基于Transformer结构相关的预训练模型API，包含ERNIE, BERT, RoBERTa, Electra等主流经典结构和下游任务。
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- [Data API](./docs/data.md)
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* 文本数据处理Pipeline的相关API说明。
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- [Dataset API](./docs/datasets.md)
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* 数据集相关API，包含自定义数据集，数据集贡献与数据集快速加载等功能说明。
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- [Embedding API](./docs/embeddings.md)
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* 词向量相关API，支持一键快速加载包预训练的中文词向量，VisulDL高维可视化等功能说明。
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- [Metrics API](./docs/metrics.md)
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* 针对NLP场景的评估指标说明，与飞桨2.0框架高层API兼容。
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## 交互式Notebook教程
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- [使用Seq2Vec模块进行句子情感分类](https://aistudio.baidu.com/aistudio/projectdetail/1283423)
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- [如何通过预训练模型Fine-tune下游任务](https://aistudio.baidu.com/aistudio/projectdetail/1294333)
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- [使用BiGRU-CRF模型完成快递单信息抽取](https://aistudio.baidu.com/aistudio/projectdetail/1317771)
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- [使用预训练模型ERNIE优化快递单信息抽取](https://aistudio.baidu.com/aistudio/projectdetail/1329361)
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- [使用Seq2Seq模型完成自动对联](https://aistudio.baidu.com/aistudio/projectdetail/1321118)
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- [使用预训练模型ERNIE-GEN实现智能写诗](https://aistudio.baidu.com/aistudio/projectdetail/1339888)
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- [使用TCN网络完成新冠疫情病例数预测](https://aistudio.baidu.com/aistudio/projectdetail/1290873)
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更多教程参见[PaddleNLP on AI Studio](https://aistudio.baidu.com/aistudio/personalcenter/thirdview/574995)。
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## 社区贡献与技术交流
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- 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。
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- 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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<div align="center">
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<img src="./docs/imgs/qq.png" width="200" height="200" />
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</div>
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## License
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PaddleNLP遵循[Apache-2.0开源协议](./LICENSE)。

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