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 --- 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." ]