diff --git a/docs/docs/modules/model_io/output_parsers/types/pydantic.ipynb b/docs/docs/modules/model_io/output_parsers/types/pydantic.ipynb
index 0dbea9e950aff4..07c06633286255 100644
--- a/docs/docs/modules/model_io/output_parsers/types/pydantic.ipynb
+++ b/docs/docs/modules/model_io/output_parsers/types/pydantic.ipynb
@@ -8,7 +8,7 @@
     "# Pydantic parser\n",
     "This output parser allows users to specify an arbitrary Pydantic Model and query LLMs for outputs that conform to that schema.\n",
     "\n",
-    "Keep in mind that large language models are leaky abstractions! You'll have to use an LLM with sufficient capacity to generate well-formed JSON. In the OpenAI family, DaVinci can do reliably but Curie's ability already drops off dramatically. \n",
+    "Keep in mind that large language models are leaky abstractions! You'll have to use an LLM with sufficient capacity to generate well-formed JSON. In the OpenAI family, DaVinci can do reliably but [Curie](https://wiprotechblogs.medium.com/davinci-vs-curie-a-comparison-between-gpt-3-engines-for-extractive-summarization-b568d4633b3b)'s ability already drops off dramatically. \n",
     "\n",
     "Use Pydantic to declare your data model. Pydantic's BaseModel is like a Python dataclass, but with actual type checking + coercion."
    ]