From 8bcadfd446cbf350815a8d6e6d007b162cce174d Mon Sep 17 00:00:00 2001 From: Ari Roffe Date: Tue, 19 Dec 2023 23:13:17 -0600 Subject: [PATCH] docs: nit embedding_distance.ipynb (#14929) **Description:** Fix the docs about embedding distance evaluations guide. --- docs/docs/guides/evaluation/string/embedding_distance.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/docs/guides/evaluation/string/embedding_distance.ipynb b/docs/docs/guides/evaluation/string/embedding_distance.ipynb index 9ab5d1ebce..3d9030ddd3 100644 --- a/docs/docs/guides/evaluation/string/embedding_distance.ipynb +++ b/docs/docs/guides/evaluation/string/embedding_distance.ipynb @@ -9,7 +9,7 @@ "# Embedding Distance\n", "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/langchain-ai/langchain/blob/master/docs/docs/guides/evaluation/string/embedding_distance.ipynb)\n", "\n", - "To measure semantic similarity (or dissimilarity) between a prediction and a reference label string, you could use a vector vector distance metric the two embedded representations using the `embedding_distance` evaluator.[[1]](#cite_note-1)\n", + "To measure semantic similarity (or dissimilarity) between a prediction and a reference label string, you could use a vector distance metric the two embedded representations using the `embedding_distance` evaluator.[[1]](#cite_note-1)\n", "\n", "\n", "**Note:** This returns a **distance** score, meaning that the lower the number, the **more** similar the prediction is to the reference, according to their embedded representation.\n",