docs: run codespell on all notebooks (#736)

* run codespell on all notebooks

* fix codespell

examples/tutorials/tnt-llm/tnt-llm.ipynb

@@ -762,7 +762,7 @@
     "\n",
     "#### Label Training Data\n",
     "\n",
-    "Use an LLM to label the data in a fully-automated fashion. For beter accuracy, you can sample a portion of the results to label by hand as well to verify the quality.\n"
+    "Use an LLM to label the data in a fully-automated fashion. For better accuracy, you can sample a portion of the results to label by hand as well to verify the quality.\n"
    ]
   },
   {
@@ -1048,7 +1048,7 @@
    "source": [
     "## Conclusion\n",
     "\n",
-    "Congrats on implementing TNT-LLM! While most folks use clustering-based approachs like LDA, k-means, etc. it can often be hard to really interpret what each cluster represents. TNT-LLM generates human-interpretable labels you can use downstream to monitor and improve your application.\n",
+    "Congrats on implementing TNT-LLM! While most folks use clustering-based approaches like LDA, k-means, etc. it can often be hard to really interpret what each cluster represents. TNT-LLM generates human-interpretable labels you can use downstream to monitor and improve your application.\n",
     "\n",
     "The technique also lends itself to hierarchical sub-categorizing: once you have the above taxonomy, use it to label your data, then on each sub-category, generate a new taxonomy using a similar technique to the one described above!\n"
    ]