adjust azureml-examples links (deepspeedai#1015)

lostmygithubaccount · jeffra · web-flow · commit 6924d840ac00 · 2021-06-08T09:33:26.000-07:00
Co-authored-by: Jeff Rasley &lt;jerasley@microsoft.com&gt;
diff --git a/docs/_tutorials/azure.md b/docs/_tutorials/azure.md
@@ -10,7 +10,7 @@ benefit all your large model training jobs.
 
 If you don't already have an Azure account please see more details here: [https://azure.microsoft.com/](https://azure.microsoft.com/).
 
-To use DeepSpeed on [Azure ML](https://azure.microsoft.com/en-us/services/machine-learning/), please take a look at easy-to-use examples for Transformers and CIFAR training from [AzureML Examples GitHub](https://github.com/Azure/azureml-examples/tree/main/workflows/train/deepspeed).
+To use DeepSpeed on [Azure ML](https://azure.microsoft.com/en-us/services/machine-learning/), please take a look at easy-to-use examples for Transformers and CIFAR training from [AzureML Examples GitHub](https://github.com/Azure/azureml-examples/tree/main/python-sdk/workflows/train/deepspeed).
 
 To help with launching Azure instances we suggest using the [Azure
 CLI](https://docs.microsoft.com/en-us/cli/azure/?view=azure-cli-latest). We have created
diff --git a/docs/_tutorials/getting-started.md b/docs/_tutorials/getting-started.md
@@ -9,7 +9,7 @@ date: 2020-05-15
 
 * Installing is as simple as `pip install deepspeed`, [see more details](/tutorials/advanced-install/).
 * Please see our [Azure tutorial](/tutorials/azure/) to get started with DeepSpeed on Azure!
-* To get started with DeepSpeed on AzureML, please see the [AzureML Examples GitHub](https://github.com/Azure/azureml-examples/tree/main/workflows/train/deepspeed)
+* To get started with DeepSpeed on AzureML, please see the [AzureML Examples GitHub](https://github.com/Azure/azureml-examples/tree/main/python-sdk/workflows/train/deepspeed)
 * If you're not on Azure, we recommend using our docker image via `docker pull deepspeed/deepspeed:latest` which contains a pre-installed version of DeepSpeed and all the necessary dependencies.
 * DeepSpeed has direct integrations with [HuggingFace Transformers](https://github.com/huggingface/transformers) and [PyTorch Lightning](https://github.com/PyTorchLightning/pytorch-lightning). HuggingFace Transformers users can now easily accelerate their models with DeepSpeed through a simple ``--deepspeed`` flag + config file [See more details](https://huggingface.co/transformers/main_classes/trainer.html#deepspeed). PyTorch Lightning provides easy access to DeepSpeed through the Lightning Trainer [See more details](https://pytorch-lightning.readthedocs.io/en/stable/advanced/multi_gpu.html?highlight=deepspeed#deepspeed).
 
diff --git a/docs/index.md b/docs/index.md
@@ -34,7 +34,7 @@ information [here](https://innovation.microsoft.com/en-us/exploring-ai-at-scale)
 * [2021/04/20] [1-bit LAMB: up to 4.6x less communication and 2.8x faster training, together with LAMB's convergence speed at large batch sizes](https://www.deepspeed.ai/tutorials/onebit-lamb/)
 * [2021/04/19] [ZeRO-Infinity unlocks unprecedented model scale for deep learning training](https://www.microsoft.com/en-us/research/blog/zero-infinity-and-deepspeed-unlocking-unprecedented-model-scale-for-deep-learning-training/)
   * [Tutorial on how to use different stages of ZeRO](https://www.deepspeed.ai/tutorials/zero/)
-* [2021/04/02] [[DeepSpeed on AzureML] Transformers and CIFAR examples are now available on AzureML GitHub](https://github.com/Azure/azureml-examples/tree/main/workflows/train/deepspeed)
+* [2021/04/02] [[DeepSpeed on AzureML] Transformers and CIFAR examples are now available on AzureML GitHub](https://github.com/Azure/azureml-examples/tree/main/python-sdk/workflows/train/deepspeed)
 * [2021/03/30] [[PyTorch Lightning Blog] Accessible Multi-Billion Parameter Model Training with PyTorch Lightning + DeepSpeed](https://medium.com/pytorch-lightning/accessible-multi-billion-parameter-model-training-with-pytorch-lightning-deepspeed-c9333ac3bb59)
 * [2021/03/16] [1-bit Adam v2: NCCL-based implementation and more](https://www.deepspeed.ai/tutorials/onebit-adam/)
 * [2021/03/08] [ZeRO-3 Offload: Scale your models to trillion parameters without code changes while leveraging both CPUs & GPUs](https://www.deepspeed.ai/news/2021/03/07/zero3-offload.html)
