PaddleFormers is an easy-to-use library of pre-trained large language model zoo based on PaddlePaddle.

High-performance Inference and Deployment Toolkit for LLMs and VLMs based on PaddlePaddle

NLP Core Library and Model Zoo based on PaddlePaddle 2.0

DeepEP: an efficient expert-parallel communication library

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）

Simple, safe way to store and distribute tensors

Ongoing research training transformer language models at scale, including: BERT & GPT-2

Paddle Distributed Training Examples. 飞桨分布式训练示例 Resnet Bert GPT MOE DataParallel ModelParallel PipelineParallel HybridParallel AutoParallel Zero Sharding Recompute GradientMerge Offload AMP DGC Loc…

Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image …

The implementation of DeBERTa

Documentations for PaddlePaddle

Paddle Graph Learning (PGL) is an efficient and flexible graph learning framework based on PaddlePaddle

Pre-trained and Reproduced Deep Learning Models （『飞桨』官方模型库，包含多种学术前沿和工业场景验证的深度学习模型）

Code for the paper "Language Models are Unsupervised Multitask Learners"

PaddlePaddle Entire Process Development Toolkit（『飞桨』深度学习全流程开发工具）

Python package built to ease deep learning on graph, on top of existing DL frameworks.

An open source benchmark for graph machine learning in Pytorch https://ogb.stanford.edu