add note to all promptfoo lectures

prompt_evaluations/08_prompt_foo_model_graded/lesson.ipynb

@@ -6,6 +6,9 @@
    "source": [
     "# Model-graded evaluations with promptfoo\n",
     "\n",
+    "**Note: This lesson lives in a folder that contains relevant code files. Download the entire folder if you want to follow along and run the evaluation yourself**\n",
+    "\n",
+    "\n",
     "So far, we've only written code-graded evaluations. Whenever possible, code-graded evaluations are the simplest and least-expensive evaluations to run. They offer clear-cut, objective assessments based on predefined criteria, making them ideal for tasks with straightforward, quantifiable outcomes. The trouble is that code-graded evaluations can only grade certain types of outputs, primarily those that can be reduced to exact matches, numerical comparisons, or other programmable logic.\n",
     "\n",
     "However, many real-world applications of language models require more nuanced evaluation. Suppose we wanted to build a chatbot to be used in middle-school classrooms. We might want to evaluate the outputs to make sure they use age-appropriate language, maintain an educational tone, avoid answering non-academic questions, or provide explanations at a suitable complexity level for middle schoolers. These criteria are subjective and context-dependent, making them challenging to assess with traditional code-based methods. This is where model-graded evaluations can help!\n",