From a37389ac59793c1d4ed8c8760f3a42221709b988 Mon Sep 17 00:00:00 2001
From: Ammar Azman <88831990+Ammar-Azman@users.noreply.github.com>
Date: Mon, 8 Jan 2024 00:42:17 +0800
Subject: [PATCH] Adding reading source for Curie model (#15569)

Improving documentation

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---
 docs/docs/modules/model_io/output_parsers/types/pydantic.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

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 9c3675cf2f..f16d940a1d 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."
    ]