Accelerate set device Apr 28, 2023 · Hugging Face在GitHub上开源了一系列的机器学习库和工具，在其组织页面置顶了一些开源库，包括transformers、diffusers、datasets、peft、accelerate以及optimum，本篇逐一详细介绍并给出对应的实战用例，方便读者更直观的理解和应用。 🚀 A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed suppo Jan 10, 2024 · 文章浏览阅读1. This means that all subsequent computations involving the model will be Aug 18, 2021 · I try to set CUDA_VISIBLE_DEVICES on the command line. It supports. Should be one or several of: "torch": the base torch random number generator "cuda": the CUDA random number generator (GPU only) device_placement (bool, optional) — Whether or not to place the model on the proper device. from_pretrained("google/ul2", device_map = 'auto') Selecting the correct batch size multiplier, such that the matrix is divisible by the tile size, can significantly speed up training. because, using accelerator with the following DataLoader command, train_dataloader = torch. com device (torch. Jan 13, 2024 · You signed in with another tab or window. Place all inputs on the same device as the Jan 13, 2024 · Accelerator 类是这个完整框架的关键，它还有一些有用的方法，您将在本文的后续部分中看到。 Accelerate 类在实例化时采用的最重要的参数如下所述： device_placement：如果您希望 Accelerate 自动将对象放置在适当的设备上，请设置为 True。 理想情况下，应该打开此功能。 Gradient accumulation is a technique where you can train on bigger batch sizes than your machine would normally be able to fit into memory. 🚀 A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed suppo Jan 10, 2023 · You signed in with another tab or window. tbjyyznhrbneosvzqxhxgaopqmcwjdeelgdnllyjhusxfuqstqnirxhwkmiwqpdvrwwfqgpyjakbglhbjpeio