# PaddlePaddle

> An open-source deep learning platform developed by Baidu for industrial-grade AI development and deployment.

PaddlePaddle (Parallel Distributed Deep Learning) is an open-source deep learning framework developed by Baidu, designed for industrial-grade AI development and deployment. It provides a comprehensive ecosystem of tools, libraries, and development kits that enable developers to build, train, and deploy deep learning models across various domains including natural language processing, computer vision, speech recognition, and scientific computing.

The platform features a unified dynamic-static graph architecture that allows developers to program and debug in dynamic graph mode while deploying in static graph mode for optimal performance. PaddlePaddle supports large-scale distributed training with its universal heterogeneous parameter server architecture and end-to-end adaptive distributed training capabilities.

**Key Features:**

- **Unified Dynamic-Static Framework** - Industry-first framework supporting seamless transition between dynamic graph development and static graph deployment for maximum flexibility and performance
- **Large-Scale Model Training** - Advanced distributed training technologies including heterogeneous parameter server architecture for training massive deep learning models
- **Multi-Platform Deployment** - High-performance inference engine supporting deployment across edge devices, cloud platforms, and multiple hardware architectures
- **Comprehensive Development Kits** - Includes PaddleOCR for text recognition, PaddleNLP for language models, PaddleSpeech for speech processing, PaddleDetection for object detection, and PaddleMIX for multimodal models
- **PaddleX Low-Code Development** - Simplified development toolkit enabling rapid AI application development with minimal coding requirements
- **Multi-Hardware Support** - Optimized for various hardware platforms with software-hardware co-optimization for heterogeneous computing environments
- **Scientific Computing Support** - PaddleScience toolkit for AI-driven scientific computing applications including physics-informed neural networks
- **FastDeploy** - Model inference deployment tool for production-ready AI applications

To get started with PaddlePaddle, developers can install the framework locally using pip or conda, choose their preferred operating system and compute platform, and begin building models using the extensive documentation and tutorials available. The platform integrates with AI Studio, Baidu's AI learning and training community, providing access to pre-trained models, datasets, and collaborative development environments.

## Features
- Unified dynamic-static graph framework
- Large-scale distributed training
- Multi-platform deployment
- PaddleOCR text recognition
- PaddleNLP language model development
- PaddleSpeech speech recognition
- PaddleDetection object detection
- PaddleSeg image segmentation
- PaddleMIX multimodal models
- PaddleScience scientific computing
- PaddleX low-code development
- FastDeploy inference deployment
- Multi-hardware optimization
- PaddleHelix biological computing
- PaddleFormers transformer models
- ERNIEKit model fine-tuning

## Integrations
AI Studio, NVIDIA GPU, Multiple hardware platforms, Docker, Kubernetes

## Platforms
WINDOWS, MACOS, LINUX, API, DEVELOPER_SDK

## Pricing
Open Source

## Version
3.0

## Links
- Website: https://www.paddlepaddle.org.cn/en
- Documentation: https://www.paddlepaddle.org.cn/documentation/docs/en/guides/index_en.html
- Repository: https://github.com/PaddlePaddle/Paddle
- EveryDev.ai: https://www.everydev.ai/tools/paddlepaddle