from accelerate import Accelerator

The `accelerate` package is a Python library developed by Hugging Face that provides an easy-to-use API for distributed training and inference of deep learning models. The `Accelerator` class in this package is a wrapper around PyTorch or TensorFlow distributed training backends, which provides a unified interface for training models on multi-GPU and multi-node environments.

To use the `Accelerator` class, you first need to install the `accelerate` package by running `pip install accelerate`. Then, in your Python script, you can import the package and create an instance of the `Accelerator` class as follows:

from accelerate import Accelerator

accelerator = Accelerator()

This will automatically detect the available GPUs and configure the distributed training backend based on the number of GPUs and nodes. You can then use the `accelerator` instance to wrap your PyTorch or TensorFlow model and data loaders, and call the training and evaluation methods as usual. The `Accelerator` class will take care of parallelizing the computations across the available devices and nodes.