5 дней назад · DeepSpeed model training is accomplished using the DeepSpeed engine. The engine can wrap any arbitrary model of type torch.nn.module and has a minimal set of ...

It is an easy-to-use deep learning optimization software suite that powers unprecedented scale and speed for both training and inference.

DeepSpeed is a deep learning training optimization library, providing the means to train massive billion parameter models at scale.

DeepSpeed is a PyTorch optimization library that makes distributed training memory-efficient and fast. At its core is the Zero Redundancy Optimizer (ZeRO).

PyTorch Profiler is an open-source tool that enables accurate and efficient performance analysis and troubleshooting for large-scale deep learning models.

13 нояб. 2023 г. · I am looking into running DeepSpeed with torch.compile and facing multiple issues with respect to tracing the hooks.

31 окт. 2024 г. · This article describes how to perform distributed training on PyTorch ML models using the DeepSpeed distributor.

18 июн. 2023 г. · This page explores the techniques used to distribute neural network training across multiple GPUs, and examines the various distributed training optimizations.

deepspeed. Functions ... Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated state_dict file that can be loaded with torch.

DeepSpeed, powered by Zero Redundancy Optimizer (ZeRO), is an optimization library for training and fitting very large models onto a GPU.