Update version numbers

code/Sentiment analysis with Hugging Face and SageMaker.ipynb

@@ -26,17 +26,8 @@
    },
    "outputs": [],
    "source": [
-    "!pip -q install sagemaker \"transformers>=4.4.2\" \"datasets[s3]==1.5.0\" widgetsnbextension ipywidgets huggingface_hub --upgrade"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "!curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | bash\n",
-    "!apt-get install git-lfs"
+    "%%sh\n",
+    "pip -q install torch transformers datasets widgetsnbextension ipywidgets huggingface_hub sacremoses==0.0.49"
    ]
   },
   {
@@ -303,15 +294,15 @@
     "    entry_point='train.py',\n",
     "    hyperparameters=hyperparameters,\n",
     "    # Infrastructure\n",
-    "    transformers_version='4.6.1',\n",
-    "    pytorch_version='1.7.1',\n",
-    "    py_version='py36',\n",
+    "    transformers_version='4.10',\n",
+    "    pytorch_version='1.9',\n",
+    "    py_version='py38',\n",
     "    instance_type='ml.p3.2xlarge',  # 1 GPUs, $4.131/hour in eu-west-1\n",
     "    instance_count=1,\n",
     "    # Enable spot instances\n",
-    "    use_spot_instances=True,        # 70% discount is typical\n",
-    "    max_run = 3600,\n",
-    "    max_wait = 7200\n",
+    "    #use_spot_instances=True,        # 70% discount is typical\n",
+    "    #max_run = 3600,\n",
+    "    #max_wait = 7200\n",
     ")"
    ]
   },
@@ -535,11 +526,18 @@
     "huggingface_model = HuggingFaceModel(\n",
     "   env=hub,                                                \n",
     "   role=sagemaker.get_execution_role(),                                        \n",
-    "   transformers_version='4.6.1',                           \n",
-    "   pytorch_version='1.7.1',                                \n",
-    "   py_version='py36'                                      \n",
-    ")\n",
-    "\n",
+    "   transformers_version='4.10',                           \n",
+    "   pytorch_version='1.9',                                \n",
+    "   py_version='py38'                                      \n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "huggingface_predictor = huggingface_model.deploy(\n",
     "   initial_instance_count=1,\n",
     "   instance_type='ml.m5.xlarge'\n",
@@ -580,9 +578,9 @@
  "metadata": {
   "instance_type": "ml.m5.4xlarge",
   "kernelspec": {
-   "display_name": "Python 3 (PyTorch 1.6 Python 3.6 CPU Optimized)",
+   "display_name": "Python 3 (Data Science)",
    "language": "python",
-   "name": "python3__SAGEMAKER_INTERNAL__arn:aws:sagemaker:eu-west-1:470317259841:image/pytorch-1.6-cpu-py36-ubuntu16.04-v1"
+   "name": "python3__SAGEMAKER_INTERNAL__arn:aws:sagemaker:us-west-2:236514542706:image/datascience-1.0"
   },
   "language_info": {
    "codemirror_mode": {
@@ -594,7 +592,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.13"
+   "version": "3.7.10"
   }
  },
  "nbformat": 4,