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Automatic device placement with Accelerator

Your conversational AI model needs to train on a massive dataset, so you've decided to move the model to a GPU. You're leveraging Accelerator for automatic device placement. Note this exercise actually runs on the CPU, but the code remains the same for running on the GPU.

A BERT-based model has been preloaded as model.

本练习是课程的一部分

Efficient AI Model Training with PyTorch

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练习说明

  • Declare an accelerator object by instantiating the appropriate class.
  • Use the accelerator object to prepare the model for distributed training with GPU.

交互式实操练习

通过完成这段示例代码来试试这个练习。

from accelerate import Accelerator

# Declare an accelerator object
accelerator = ____()

# Prepare the model for distributed training
model = accelerator.____(model)

print(accelerator.device)
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