sm-distributed-training-step-by-step

Making large AI models cheaper, faster and more accessible

Learn how to design, develop, deploy and iterate on production-grade ML applications.

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

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）

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。

FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, TensorOpera AI (https://TensorOpera.ai) is your generative AI platform at scale.

A high performance and generic framework for distributed DNN training

Fast and flexible AutoML with learning guarantees.

Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.

Training and serving large-scale neural networks with auto parallelization.