fixes broken link to QA notebook

ted-at-openai · ted-at-openai · commit e383e243c207 · 2022-10-24T16:31:33.000-07:00
diff --git a/examples/Question_answering_using_embeddings.ipynb b/examples/Question_answering_using_embeddings.ipynb
@@ -195,7 +195,7 @@
     "\n",
     "We plan to use document embeddings to fetch the most relevant part of parts of our document library and insert them into the prompt that we provide to GPT-3. We therefore need to break up the document library into \"sections\" of context, which can be searched and retrieved separately. \n",
     "\n",
-    "Sections should be large enough to contain enough information to answer a question; but small enough to fit one or several into the GPT-3 prompt. We find that approximately a paragraph of text is usually a good length, but you should experiment for your particular use case. In this example, Wikipedia articles are already grouped into semantically related headers, so we will use these to define our sections. This preprocessing has already been done in [this notebook](examples/fine-tuned_qa/olympics-1-collect-data.ipynb), so we will load the results and use them."
+    "Sections should be large enough to contain enough information to answer a question; but small enough to fit one or several into the GPT-3 prompt. We find that approximately a paragraph of text is usually a good length, but you should experiment for your particular use case. In this example, Wikipedia articles are already grouped into semantically related headers, so we will use these to define our sections. This preprocessing has already been done in [this notebook](fine-tuned_qa/olympics-1-collect-data.ipynb), so we will load the results and use them."
    ]
   },
   {

Original file line number	Diff line number	Diff line change
`@@ -195,7 +195,7 @@`
`195`	`195`	`"\n",`
`196`	`196`	`"We plan to use document embeddings to fetch the most relevant part of parts of our document library and insert them into the prompt that we provide to GPT-3. We therefore need to break up the document library into \"sections\" of context, which can be searched and retrieved separately. \n",`
`197`	`197`	`"\n",`
`198`		- "Sections should be large enough to contain enough information to answer a question; but small enough to fit one or several into the GPT-3 prompt. We find that approximately a paragraph of text is usually a good length, but you should experiment for your particular use case. In this example, Wikipedia articles are already grouped into semantically related headers, so we will use these to define our sections. This preprocessing has already been done in [this notebook](examples/fine-tuned_qa/olympics-1-collect-data.ipynb), so we will load the results and use them."
	`198`	+ "Sections should be large enough to contain enough information to answer a question; but small enough to fit one or several into the GPT-3 prompt. We find that approximately a paragraph of text is usually a good length, but you should experiment for your particular use case. In this example, Wikipedia articles are already grouped into semantically related headers, so we will use these to define our sections. This preprocessing has already been done in [this notebook](fine-tuned_qa/olympics-1-collect-data.ipynb), so we will load the results and use them."
`199`	`199`	`]`
`200`	`200`	`},`
`201`	`201`	`{`