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Merge pull request #1795 from Azure/release_update/Release-153

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update samples from Release-153 as a part of  SDK release
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Harneet Virk
2022-08-09 15:39:30 -07:00
committed by GitHub
parent aed078aeab 6a38f4bec3
commit 7fb5dd3ef9
2 changed files with 3 additions and 3 deletions
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2
how-to-use-azureml/ml-frameworks/chainer/train-hyperparameter-tune-deploy-with-chainer/train-hyperparameter-tune-deploy-with-chainer.ipynb
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@@ -554,7 +554,7 @@
"cd = CondaDependencies.create()\n",
"cd.add_conda_package('numpy')\n",
"cd.add_pip_package('chainer==5.1.0')\n",
"cd.add_pip_package(\"azureml-defaults\")\n",
"cd.add_pip_package(\"azureml-defaults==1.43.0\")\n",
"cd.add_pip_package(\"azureml-opendatasets\")\n",
"cd.save_to_file(base_directory='./', conda_file_path='myenv.yml')\n",
"\n",

4
how-to-use-azureml/ml-frameworks/pytorch/train-hyperparameter-tune-deploy-with-pytorch/train-hyperparameter-tune-deploy-with-pytorch.ipynb
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@@ -264,7 +264,7 @@
"- python=3.6.2\n",
"- pip=21.3.1\n",
"- pip:\n",
" - azureml-defaults\n",
" - azureml-defaults==1.43.0\n",
" - torch==1.6.0\n",
" - torchvision==0.7.0\n",
" - future==0.17.1\n",
@@ -539,7 +539,7 @@
"metadata": {},
"source": [
"## Deploy model as web service\n",
"Once you have your trained model, you can deploy the model on Azure. In this tutorial, we will deploy the model as a web service in [Azure Container Instances](https://docs.microsoft.com/en-us/azure/container-instances/) (ACI). For more information on deploying models using Azure ML, refer [here](https://docs.microsoft.com/azure/machine-learning/service/how-to-deploy-and-where)."
"Once you have your trained model, you can deploy the model on Azure. In this tutorial, we will deploy the model as a web service in [Azure Container Instances](https://docs.microsoft.com/en-us/azure/container-instances/) (ACI). For more information on deploying models using Azure ML, refer [here](https://docs.microsoft.com/en-us/azure/machine-learning/v1/how-to-deploy-and-where)."
]
},
{