Update tutorials/structured-output-instructor/structured_output_instr…

…uctor.ipynb

Co-authored-by: Hatice Ozen <139392640+hozen-groq@users.noreply.github.com>

tutorials/structured-output-instructor/structured_output_instructor.ipynb

@@ -5,7 +5,7 @@
    "metadata": {},
    "source": [
     "# Structured Output with Groq and Instructor\n",
-    "While large language models (LLMs) are often employed for building chatbots or conversational agents, numerous real-world applications require a different approach - one that goes beyond mere dialogue and involves producing structured, machine-readable outputs.\n",
+    "While Large Language Models (LLMs) are often employed for building chatbots or conversational agents, numerous real-world applications require a different approach - one that goes beyond mere dialogue and involves producing structured, machine-readable outputs.\n",
     "\n",
     "Consider a typical scenario: we want to produce structured JSON data from an LLM. While tools like Python's `json` module allow us to handle this data, they also come with their own set of challenges, such as validating data types and ensuring consistency across outputs. Manually checking these aspects can be tedious and error-prone. LLMs also tend to forget to include a comma or a closing bracket ('}') somewhere in the produced JSON from time to time, which would invalidate the whole JSON output.\n",
     "\n",