PaddlePaddle/PaddleNLP PaddlePaddle/PaddleNLP

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  • Created about 3 years ago
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PaddlePaddle/PaddleNLP
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PaddlePaddle

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👑 Easy-to-use and powerful NLP and LLM library with 🤗 Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including 🗂Text Classification, 🔍 Neural Search, ❓ Question Answering, ℹ️ Information Extraction, 📄 Document Intelligence, 💌 Sentiment Analysis etc.

简体中文🀄 | English🌎

特性 | 安装 | 快速开始 | API文档 | 社区交流

PaddleNLP是一款简单易用且功能强大的自然语言处理开发库。聚合业界优质预训练模型并提供开箱即用的开发体验，覆盖NLP多场景的模型库搭配产业实践范例可满足开发者灵活定制的需求。

News 📢

  • 2023.6.12 发布 PaddleNLP v2.6rc 预览版

    • 🔨 大模型全流程范例：全面支持主流开源大模型Bloom, ChatGLM, GLM, Llama, OPT的训练和推理；Trainer API新增张量训练能力, 简单配置即可开启分布式训练；新增低参数微调能力PEFT, 助力大模型高效微调

  • 2023.1.12 发布 PaddleNLP v2.5

    • 🔨 NLP工具：发布 PPDiffusers 国产化的扩散模型工具箱，集成多种 Diffusion 模型参数和模型组件，提供了 Diffusion 模型的完整训练流程，支持 Diffusion 模型的高性能 FastDeploy 推理加速 和 多硬件部署(可支持昇腾芯片、昆仑芯部署)
    • 💎 产业应用：信息抽取、文本分类、情感分析、智能问答 四大应用全新升级，发布文档信息抽取 UIE-X 、统一文本分类 UTC 、统一情感分析 UIE-Senta 、无监督问答应用；同时发布ERNIE 3.0 Tiny v2 系列预训练小模型，在低资源和域外数据效果更强，开源 模型裁剪、模型量化、FastDeploy 推理加速、边缘端部署 端到端部署方案，降低预训练模型部署难度
    • 💪 框架升级：预训练模型参数配置统一，自定义参数配置的保存和加载无需额外开发；Trainer API 新增 BF16 训练、Recompute 重计算、Sharding 等多项分布式能力，通过简单配置即可进行超大规模预训练模型训练；模型压缩 API 支持量化训练、词表压缩等功能，压缩后的模型精度损失更小，模型部署的内存占用大大降低；数据增强API 全面升级，支持字、词、句子三种粒度数据增强策略，可轻松定制数据增强策略
    • 🤝 生态联合：🤗Huggingface hub 正式兼容 PaddleNLP 预训练模型，支持 PaddleNLP Model 和 Tokenizer 直接从 🤗Huggingface hub 下载和上传，欢迎大家在 🤗Huggingface hub 体验 PaddleNLP 预训练模型效果

  • 2022.9.6 发布 PaddleNLP v2.4

    • 🔨 NLP工具：NLP 流水线系统 Pipelines 发布，支持快速搭建搜索引擎、问答系统，可扩展支持各类NLP系统，让解决 NLP 任务像搭积木一样便捷、灵活、高效！
    • 💎 产业应用：新增 文本分类全流程应用方案 ，覆盖多分类、多标签、层次分类各类场景，支持小样本学习和 TrustAI 可信计算模型训练与调优。
    • 🍭 AIGC ：新增代码生成 SOTA 模型CodeGen，支持多种编程语言代码生成；
    • 💪 框架升级：模型自动压缩 API 发布，自动对模型进行裁减和量化，大幅降低模型压缩技术使用门槛；小样本 Prompt能力发布，集成 PET、P-Tuning、RGL 等经典算法。

社区交流

  • 微信扫描二维码并填写问卷，回复小助手关键词（NLP）之后，即可加入交流群领取福利

    • 与众多社区开发者以及官方团队深度交流。
    • 10G重磅NLP学习大礼包！

特性

📦 开箱即用的NLP工具集

🤗 丰富完备的中文模型库

🎛️ 产业级端到端系统范例

🚀 高性能分布式训练与推理

开箱即用的NLP工具集

Taskflow提供丰富的📦开箱即用的产业级NLP预置模型，覆盖自然语言理解与生成两大场景，提供💪产业级的效果与⚡️极致的推理性能。

taskflow1

更多使用方法可参考Taskflow文档。

丰富完备的中文模型库

🀄 业界最全的中文预训练模型

精选 45+ 个网络结构和 500+ 个预训练模型参数，涵盖业界最全的中文预训练模型：既包括文心NLP大模型的ERNIE、PLATO等，也覆盖BERT、GPT、RoBERTa、T5等主流结构。通过AutoModel API一键⚡高速下载⚡。

from paddlenlp.transformers import *

ernie = AutoModel.from_pretrained('ernie-3.0-medium-zh')
bert = AutoModel.from_pretrained('bert-wwm-chinese')
albert = AutoModel.from_pretrained('albert-chinese-tiny')
roberta = AutoModel.from_pretrained('roberta-wwm-ext')
electra = AutoModel.from_pretrained('chinese-electra-small')
gpt = AutoModelForPretraining.from_pretrained('gpt-cpm-large-cn')

针对预训练模型计算瓶颈，可以使用API一键使用文心ERNIE-Tiny全系列轻量化模型，降低预训练模型部署难度。

# 6L768H
ernie = AutoModel.from_pretrained('ernie-3.0-medium-zh')
# 6L384H
ernie = AutoModel.from_pretrained('ernie-3.0-mini-zh')
# 4L384H
ernie = AutoModel.from_pretrained('ernie-3.0-micro-zh')
# 4L312H
ernie = AutoModel.from_pretrained('ernie-3.0-nano-zh')

对预训练模型应用范式如语义表示、文本分类、句对匹配、序列标注、问答等，提供统一的API体验。

import paddle
from paddlenlp.transformers import *

tokenizer = AutoTokenizer.from_pretrained('ernie-3.0-medium-zh')
text = tokenizer('自然语言处理')

# 语义表示
model = AutoModel.from_pretrained('ernie-3.0-medium-zh')
sequence_output, pooled_output = model(input_ids=paddle.to_tensor([text['input_ids']]))
# 文本分类 & 句对匹配
model = AutoModelForSequenceClassification.from_pretrained('ernie-3.0-medium-zh')
# 序列标注
model = AutoModelForTokenClassification.from_pretrained('ernie-3.0-medium-zh')
# 问答
model = AutoModelForQuestionAnswering.from_pretrained('ernie-3.0-medium-zh')

💯 全场景覆盖的应用示例

覆盖从学术到产业的NLP应用示例，涵盖NLP基础技术、NLP系统应用以及拓展应用。全面基于飞桨核心框架2.0全新API体系开发，为开发者提供飞桨文本领域的最佳实践。

精选预训练模型示例可参考Model Zoo，更多场景示例文档可参考examples目录。更有免费算力支持的AI Studio平台的Notbook交互式教程提供实践。

PaddleNLP预训练模型适用任务汇总（点击展开详情）
Model Sequence Classification Token Classification Question Answering Text Generation Multiple Choice
ALBERT ✅ ✅ ✅ ❌ ✅
BART ✅ ✅ ✅ ✅ ❌
BERT ✅ ✅ ✅ ❌ ✅
BigBird ✅ ✅ ✅ ❌ ✅
BlenderBot ❌ ❌ ❌ ✅ ❌
ChineseBERT ✅ ✅ ✅ ❌ ❌
ConvBERT ✅ ✅ ✅ ❌ ✅
CTRL ✅ ❌ ❌ ❌ ❌
DistilBERT ✅ ✅ ✅ ❌ ❌
ELECTRA ✅ ✅ ✅ ❌ ✅
ERNIE ✅ ✅ ✅ ❌ ✅
ERNIE-CTM ❌ ✅ ❌ ❌ ❌
ERNIE-Doc ✅ ✅ ✅ ❌ ❌
ERNIE-GEN ❌ ❌ ❌ ✅ ❌
ERNIE-Gram ✅ ✅ ✅ ❌ ❌
ERNIE-M ✅ ✅ ✅ ❌ ❌
FNet ✅ ✅ ✅ ❌ ✅
Funnel-Transformer ✅ ✅ ✅ ❌ ❌
GPT ✅ ✅ ❌ ✅ ❌
LayoutLM ✅ ✅ ❌ ❌ ❌
LayoutLMv2 ❌ ✅ ❌ ❌ ❌
LayoutXLM ❌ ✅ ❌ ❌ ❌
LUKE ❌ ✅ ✅ ❌ ❌
mBART ✅ ❌ ✅ ❌ ✅
MegatronBERT ✅ ✅ ✅ ❌ ✅
MobileBERT ✅ ❌ ✅ ❌ ❌
MPNet ✅ ✅ ✅ ❌ ✅
NEZHA ✅ ✅ ✅ ❌ ✅
PP-MiniLM ✅ ❌ ❌ ❌ ❌
ProphetNet ❌ ❌ ❌ ✅ ❌
Reformer ✅ ❌ ✅ ❌ ❌
RemBERT ✅ ✅ ✅ ❌ ✅
RoBERTa ✅ ✅ ✅ ❌ ✅
RoFormer ✅ ✅ ✅ ❌ ❌
SKEP ✅ ✅ ❌ ❌ ❌
SqueezeBERT ✅ ✅ ✅ ❌ ❌
T5 ❌ ❌ ❌ ✅ ❌
TinyBERT ✅ ❌ ❌ ❌ ❌
UnifiedTransformer ❌ ❌ ❌ ✅ ❌
XLNet ✅ ✅ ✅ ❌ ✅

可参考Transformer 文档 查看目前支持的预训练模型结构、参数和详细用法。

产业级端到端系统范例

PaddleNLP针对信息抽取、语义检索、智能问答、情感分析等高频NLP场景，提供了端到端系统范例，打通数据标注-模型训练-模型调优-预测部署全流程，持续降低NLP技术产业落地门槛。更多详细的系统级产业范例使用说明请参考Applications。

🔍 语义检索系统

针对无监督数据、有监督数据等多种数据情况，结合SimCSE、In-batch Negatives、ERNIE-Gram单塔模型等，推出前沿的语义检索方案，包含召回、排序环节，打通训练、调优、高效向量检索引擎建库和查询全流程。

更多使用说明请参考语义检索系统。

❓ 智能问答系统

基于🚀RocketQA技术的检索式问答系统，支持FAQ问答、说明书问答等多种业务场景。

更多使用说明请参考智能问答系统与文档智能问答

💌 评论观点抽取与情感分析

基于情感知识增强预训练模型SKEP，针对产品评论进行评价维度和观点抽取，以及细粒度的情感分析。

更多使用说明请参考情感分析。

🎙️ 智能语音指令解析

集成了PaddleSpeech和百度开放平台的语音识别和UIE通用信息抽取等技术，打造智能一体化的语音指令解析系统范例，该方案可应用于智能语音填单、智能语音交互、智能语音检索等场景，提高人机交互效率。

更多使用说明请参考智能语音指令解析。

高性能分布式训练与推理

⚡ FastTokenizer：高性能文本处理库

AutoTokenizer.from_pretrained("ernie-3.0-medium-zh", use_fast=True)

为了实现更极致的模型部署性能，安装FastTokenizers后只需在AutoTokenizer API上打开 use_fast=True选项，即可调用C++实现的高性能分词算子，轻松获得超Python百余倍的文本处理加速，更多使用说明可参考FastTokenizer文档。

⚡️ FastGeneration：高性能生成加速库

model = GPTLMHeadModel.from_pretrained('gpt-cpm-large-cn')
...
outputs, _ = model.generate(
    input_ids=inputs_ids, max_length=10, decode_strategy='greedy_search',
    use_fast=True)

简单地在generate()API上打开use_fast=True选项，轻松在Transformer、GPT、BART、PLATO、UniLM等生成式预训练模型上获得5倍以上GPU加速，更多使用说明可参考FastGeneration文档。

🚀 Fleet：飞桨4D混合并行分布式训练技术

更多关于千亿级AI模型的分布式训练使用说明可参考GPT-3。

安装

环境依赖

  • python >= 3.7
  • paddlepaddle >= 2.3

pip安装

pip install --upgrade paddlenlp

或者可通过以下命令安装最新 develop 分支代码：

pip install --pre --upgrade paddlenlp -f https://www.paddlepaddle.org.cn/whl/paddlenlp.html

更多关于PaddlePaddle和PaddleNLP安装的详细教程请查看Installation。

快速开始

这里以信息抽取-命名实体识别任务，UIE模型为例，来说明如何快速使用PaddleNLP:

一键预测

PaddleNLP提供一键预测功能，无需训练，直接输入数据即可开放域抽取结果：

>>> from pprint import pprint
>>> from paddlenlp import Taskflow

>>> schema = ['时间', '选手', '赛事名称'] # Define the schema for entity extraction
>>> ie = Taskflow('information_extraction', schema=schema)
>>> pprint(ie("2月8日上午北京冬奥会自由式滑雪女子大跳台决赛中中国选手谷爱凌以188.25分获得金牌！"))
[{'时间': [{'end': 6,
          'probability': 0.9857378532924486,
          'start': 0,
          'text': '2月8日上午'}],
  '赛事名称': [{'end': 23,
            'probability': 0.8503089953268272,
            'start': 6,
            'text': '北京冬奥会自由式滑雪女子大跳台决赛'}],
  '选手': [{'end': 31,
          'probability': 0.8981548639781138,
          'start': 28,
          'text': '谷爱凌'}]}]

小样本学习

如果对一键预测效果不满意，也可以使用少量数据进行模型精调，进一步提升特定场景的效果，详见UIE小样本定制训练。

更多PaddleNLP内容可参考：

  • 精选模型库，包含优质预训练模型的端到端全流程使用。
  • 多场景示例，了解如何使用PaddleNLP解决NLP多种技术问题，包含基础技术、系统应用与拓展应用。
  • 交互式教程，在🆓免费算力平台AI Studio上快速学习PaddleNLP。

API文档

PaddleNLP提供全流程的文本领域API，可大幅提升NLP任务建模的效率：

更多使用方法请参考API文档。

Citation

如果PaddleNLP对您的研究有帮助，欢迎引用

@misc{=paddlenlp,
    title={PaddleNLP: An Easy-to-use and High Performance NLP Library},
    author={PaddleNLP Contributors},
    howpublished = {\url{https://github.com/PaddlePaddle/PaddleNLP}},
    year={2021}
}

Acknowledge

我们借鉴了Hugging Face的Transformers🤗关于预训练模型使用的优秀设计，在此对Hugging Face作者及其开源社区表示感谢。

License

PaddleNLP遵循Apache-2.0开源协议。

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A 3D computer vision development toolkit based on PaddlePaddle. It supports point-cloud object detection, segmentation, and monocular 3D object detection models.
Python
529
star
35

Quantum

Jupyter Notebook
528
star
36

PaddleYOLO

🚀🚀🚀 YOLO series of PaddlePaddle implementation, PP-YOLOE+, RT-DETR, YOLOv5, YOLOv6, YOLOv7, YOLOv8, YOLOX, YOLOv5u, YOLOv7u, YOLOv6Lite, RTMDet and so on. 🚀🚀🚀
Python
500
star
37

PaddleFL

Federated Deep Learning in PaddlePaddle
Python
480
star
38

VIMER

视觉预训练基础模型仓库
Python
479
star
39

PaddleTS

Awesome Easy-to-Use Deep Time Series Modeling based on PaddlePaddle, including comprehensive functionality modules like TSDataset, Analysis, Transform, Models, AutoTS, and Ensemble, etc., supporting versatile tasks like time series forecasting, representation learning, and anomaly detection, etc., featured with quick tracking of SOTA deep models.
Python
444
star
40

PaddleFleetX

飞桨大模型开发套件，提供大语言模型、跨模态大模型、生物计算大模型等领域的全流程开发工具链。
Python
417
star
41

PaddleRS

Awesome Remote Sensing Toolkit based on PaddlePaddle.
Python
330
star
42

PaddleSpatial

PaddleSpatial is an open-source spatial-temporal computing tool based on PaddlePaddle.
GLSL
316
star
43

PaddleCloud

PaddlePaddle Docker images and K8s operators for PaddleOCR/Detection developers to use on public/private cloud.
Go
279
star
44

ERNIE-SDK

ERNIE Bot Agent is a Large Language Model (LLM) Agent Framework, powered by the advanced capabilities of ERNIE Bot and the platform resources of Baidu AI Studio.
Jupyter Notebook
274
star
45

MetaGym

Collection of Reinforcement Learning / Meta Reinforcement Learning Environments.
Python
267
star
46

PASSL

PASSL包含 SimCLR，MoCo v1/v2，BYOL，CLIP，PixPro，simsiam, SwAV, BEiT，MAE 等图像自监督算法以及 Vision Transformer，DEiT，Swin Transformer，CvT，T2T-ViT，MLP-Mixer，XCiT，ConvNeXt，PVTv2 等基础视觉算法
Python
257
star
47

PaddleScience

PaddleScience is SDK and library for developing AI-driven scientific computing applications based on PaddlePaddle.
Python
234
star
48

docs

Documentations for PaddlePaddle
Python
230
star
49

InterpretDL

InterpretDL: Interpretation of Deep Learning Models，基于『飞桨』的模型可解释性算法库。
Python
226
star
50

Paddle-Inference-Demo

C++
223
star
51

PaddleRobotics

PaddleRobotics is an open-source algorithm library for robots based on Paddle, including open-source parts such as human-robot interaction, complex motion control, environment perception, SLAM positioning, and navigation.
Python
210
star
52

PaddleMIX

Paddle Multimodal Integration and eXploration, supporting mainstream multi-modal tasks, including end-to-end large-scale multi-modal pretrain models and diffusion model toolbox. Equipped with high performance and flexibility.
Python
207
star
53

TrustAI

飞桨可信AI
Python
179
star
54

ElasticCTR

ElasticCTR，即飞桨弹性计算推荐系统，是基于Kubernetes的企业级推荐系统开源解决方案。该方案融合了百度业务场景下持续打磨的高精度CTR模型、飞桨开源框架的大规模分布式训练能力、工业级稀疏参数弹性调度服务，帮助用户在Kubernetes环境中一键完成推荐系统部署，具备高性能、工业级部署、端到端体验的特点，并且作为开源套件，满足二次深度开发的需求。
Python
176
star
55

PALM

a Fast, Flexible, Extensible and Easy-to-use NLP Large-scale Pretraining and Multi-task Learning Framework.
Python
174
star
56

AutoDL

Python
158
star
57

PLSC

Paddle Large Scale Classification Tools，supports ArcFace, CosFace, PartialFC, Data Parallel + Model Parallel. Model includes ResNet, ViT, Swin, DeiT, CaiT, FaceViT, MoCo, MAE, ConvMAE, CAE.
Python
142
star
58

CINN

Compiler Infrastructure for Neural Networks
C++
139
star
59

LiteKit

Off-The-Shelf AI Development Kit for APP Developers based on Paddle Lite （『飞桨』移动端开箱即用AI套件, 包含Java & Objective C接口支持）
Objective-C
131
star
60

PaddleFlow

Go
104
star
61

PaddleDTX

Paddle with Decentralized Trust based on Xuperchain
Go
87
star
62

PaddleSports

Python
86
star
63

XWorld

A C++/Python simulator package for reinforcement learning
C++
84
star
64

hapi

hapi is a High-level API that supports both static and dynamic execution modes
Jupyter Notebook
76
star
65

benchmark

Python
74
star
66

PaddleSleeve

PaddleSleeve
Python
70
star
67

Mobile

Embedded and Mobile Deployment
Python
70
star
68

community

PaddlePaddle Developer Community
Jupyter Notebook
66
star
69

PaConvert

Code Convert to PaddlePaddle Toolkit
Python
66
star
70

PaddleDepth

Python
58
star
71

PaddleCustomDevice

PaddlePaddle custom device implementaion. (『飞桨』自定义硬件接入实现)
C++
49
star
72

PaddlePaddle.org

PaddlePaddle.org is the repository for the website of the PaddlePaddle open source project.
CSS
48
star
73

PaddleTest

PaddlePaddle TestSuite
Python
43
star
74

PaDiff

Paddle Automatically Diff Precision Toolkits.
Python
42
star
75

EasyData

Python
35
star
76

epep

Easy & Effective Application Framework for PaddlePaddle
Python
34
star
77

paddle-ce-latest-kpis

Paddle Continuous Evaluation, keep updating.
Python
26
star
78

VisionTools

Python
22
star
79

Contrib

contribution works with PaddlePaddle from the third party developers
Python
20
star
80

PaddleCraft

Take neural networks as APIs for human-like AI.
Python
20
star
81

PaddleTransfer

飞桨迁移学习算法库
Python
19
star
82

recordio

An implementation of the RecordIO file format.
Go
19
star
83

continuous_evaluation

Macro Continuous Evaluation Platform for Paddle.
Python
19
star
84

Perf

SOTA benchmark
Python
17
star
85

Paddle-bot

Python
17
star
86

examples

Python
17
star
87

continuous_integration

Python
16
star
88

tape

C++
14
star
89

PaddleSOT

A Bytecode level Implementation of Symbolic OpCode Translator For PaddlePaddle
Python
14
star
90

paddle_upgrade_tool

upgrade paddle-1.x to paddle-2.0
Python
12
star
91

talks

Shell
6
star
92

CLA

5
star
93

any

Legacy Repo only for PaddlePaddle with version <= 1.3
C++
5
star