PaddlePaddle/Paddle
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
1 release in the last 90 days, the latest 56 days ago, with 360 contributors on GitHub.
Use Cases & Benefits
- Provides a high-performance deep learning framework supporting distributed training and cross-platform deployment.
- Offers unified dynamic/static graph execution with automatic parallelism to simplify industrial-scale model development and training.
- Use for building and training large-scale neural networks with seamless integration of training and inference workflows.
- Use for scientific computing tasks requiring high-order differentiation, complex operations, and efficient differential equation solving.
- Use for deploying AI models across heterogeneous hardware platforms with a pluggable, standardized multi-chip adaptation architecture.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Apache 2.0
Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.
Community files
- README: present
- Contributing guide: present
- Code of conduct: present
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
Welcome to the PaddlePaddle GitHub.
PaddlePaddle, as the first independent R&D deep learning platform in China, has been officially open-sourced to professional communities since 2016. It is an industrial platform with advanced technologies and rich features that cover core deep learning frameworks, basic model libraries, end-to-end development kits, tools & components as well as service platforms. PaddlePaddle originates from industrial practices with dedication and commitments to industrialization. It has been widely adopted by a wide range of sectors including manufacturing, agriculture, enterprise service, and so on while serving more than 23.33 million developers, 760,000 companies and generating 1,100,000 models. With such advantages, PaddlePaddle has helped an increasing number of partners commercialize AI.
Our vision is to enable deep learning for everyone via PaddlePaddle. Please refer to our release announcement to track the latest features of PaddlePaddle.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
Forks
6.0K+5
Open issues
1.4K-81
Compared with peers in Deep Learning
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 8, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| rohitg00/ai-engineering-from-scratch | 78.3K | +1.6K | 75 | 1 day ago |
| SYSTRAN/faster-whisper | 26.5K | — | 40 | 368 days ago |
| PaddlePaddle/Paddle | 24.1K | — | 62 | 56 days ago |
| GeeeekExplorer/nano-vllm | 16.3K | — | 12 | — |
| Lightning-AI/litgpt | 13.8K | — | 58 | 129 days ago |
| data-privacy-stack/presidio | 11.8K | — | 64 | 10 days ago |
| Category median | 16.3K | — | 58 | — |
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