distributed-training

PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more

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）

Fast and flexible AutoML with learning guarantees.

A high performance and generic framework for distributed DNN training

FedML - The federated learning and analytics library enabling secure and collaborative machine learning on decentralized data anywhere at any scale. Supporting large-scale cross-silo federated learning, cross-device federated learning on smartphones/IoTs, and research simulation. MLOps and App Marketplace are also enabled (https://open.fedml.ai).

Fengshenbang-LM(封神榜大模型)是IDEA研究院认知计算与自然语言研究中心主导的大模型开源体系，成为中文AIGC和认知智能的基础设施。

SkyPilot is a framework for easily running machine learning workloads on any cloud through a unified interface.

Training and serving large-scale neural networks

Determined: Deep Learning Training Platform

Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world.

Library for Fast and Flexible Human Pose Estimation

DeepRec is a high-performance recommendation deep learning framework based on TensorFlow. It is hosted in incubation in LF AI & Data Foundation.

Resource-adaptive cluster scheduler for deep learning training.

LiBai(李白): A Toolbox for Large-Scale Distributed Parallel Training

Efficient Deep Learning Systems course materials (HSE, YSDA)

Fast and Adaptive Distributed Machine Learning for TensorFlow, PyTorch and MindSpore.

A full pipeline AutoML tool for tabular data

HandyRL is a handy and simple framework based on Python and PyTorch for distributed reinforcement learning that is applicable to your own environments.

Distributed Deep Learning on AWS Using CloudFormation (CFN), MXNet and TensorFlow

YOLO3D: End-to-end real-time 3D Oriented Object Bounding Box Detection from LiDAR Point Cloud (ECCV 2018)