fixed links

Author: zbyosufzai

notebooks/GenAI/Pubmed_RAG_chatbot.ipynb

@@ -316,7 +316,7 @@
    "source": [
     "Now we can make our index, this can take up to 30min to 1hr. \n",
     "\n",
-    "Please note that the dimensions depend on what text embedding model you are using for this tutorial we are using **Vertex AI's embedding model** which uses 768 dimensions. If you chose to change your model choose a embedding model that is compatible with it or you can use Tensorflow's Universal Sentence Encoder. For more information see [here](https://python.langchain.com/docs/integrations/vectorstores/matchingengine#using-tensorflow-universal-sentence-encoder-as-an-embedder)."
+    "Please note that the dimensions depend on what text embedding model you are using for this tutorial we are using **Vertex AI's embedding model** which uses 768 dimensions. If you choose to change your model, choose an embedding model that is compatible with it."
    ]
   },
   {
@@ -355,7 +355,7 @@
    "id": "9b3aa4a2-1145-475a-bd04-33bf69551751",
    "metadata": {},
    "source": [
-    "We will create a public endpoint for our vector store, you can also create a private one by setting up a VPC and specifying the VPC id for the params 'network'. Documentation for creating a VPC can be found [here](https://python.langchain.com/docs/integrations/vectorstores/matchingengine#imports-constants-and-configs)."
+    "We will create a public endpoint for our vector store, you can also create a private one by setting up a VPC and specifying the VPC id for the params 'network'."
    ]
   },
   {