minor fix

Co-authored-by: Miyoung <[email protected]>

README.md

@@ -154,7 +154,7 @@ These examples provide and introduction to SageMaker Debugger which allows debug
 ### Amazon SageMaker Distributed Training
 
 These examples provide an introduction to SageMaker Distributed Training Libraries for data parallelism and model parallelism. The libraries are optimized for the SageMaker training environment, help adapt your distributed training jobs to SageMaker, and improve training speed and throughput.
-More examples for models such as BERT and YOLOv5 can be found in [distributed_training/](https://github.com/aws/amazon-sagemaker-examples/tree/main/training/distributed_training) . 
+More examples for models such as BERT and YOLOv5 can be found in [distributed_training/](https://github.com/aws/amazon-sagemaker-examples/tree/main/training/distributed_training).
 
 - [Train GPT-2 with Sharded Data Parallel](https://github.com/aws/amazon-sagemaker-examples/tree/main/training/distributed_training/pytorch/model_parallel/gpt2/smp-train-gpt-simple-sharded-data-parallel.ipynb) shows how to Train GPT-2 with near-linear scaling using Sharded Data Parallelism technique in SageMaker Model Parallelism Library.
 - [Train EleutherAI GPT-J with Model Parallel](https://github.com/aws/amazon-sagemaker-examples/blob/main/training/distributed_training/pytorch/model_parallel/gpt-j/11_train_gptj_smp_tensor_parallel_notebook.ipynb) shows how to train EleutherAI GPT-J with PyTorch and Tensor Parallelism technique in the SageMaker Model Parallelism Library.