spell correct (#360)

Author: aimlnerd

tutorials/34_Extractive_QA_Pipeline.ipynb

@@ -565,7 +565,7 @@
     "\n",
     "Your extractive QA pipeline will consist of three components: an embedder, retriever, and reader.\n",
     "\n",
-    "- The `SentenceTransformersTextEmbedder` turns a query into a vector, usaing the same embedding model defined above.\n",
+    "- The `SentenceTransformersTextEmbedder` turns a query into a vector, using the same embedding model defined above.\n",
     "\n",
     "- Vector search allows the retriever to efficiently return relevant documents from the document store. Retrievers are tightly coupled with document stores; thus, you'll use an `InMemoryEmbeddingRetriever`to go with the `InMemoryDocumentStore`.\n",
     "\n",