I understand that you want to be sure, but no need to worry. The trainer will probably simply trigger DataPrallel (non-distributed).

  

      github.com
  

  
    huggingface/transformers/blob/143738214cb83e471f3a43652617c8881370342c/src/transformers/trainer.py#L940-L942 1



      
      
          # Multi-gpu training (should be after apex fp16 initialization)
          if self.args.n_gpu > 1:
              model = nn.DataParallel(model)
      
    
  


  

  
    
    
  

  


This uses two GPUs, but non-distributed. This is less performant than using DistributedDataParallel but is still significantly faster than a single GPU. What it does is dividing the work over two (or more) GPUs by dividing the given batch size over the different devices. In the back pass the gradients are then summed.