From a7f08f868b2bff55562aa305df82b2a9afac6387 Mon Sep 17 00:00:00 2001 From: Cha Hwa Young Date: Sun, 19 Jan 2025 11:45:32 +0900 Subject: [PATCH] docs: Fix typos and update formatting in 04-FlashRank-Reranker.ipynb --- 11-Reranker/04-FlashRank-Reranker.ipynb | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/11-Reranker/04-FlashRank-Reranker.ipynb b/11-Reranker/04-FlashRank-Reranker.ipynb index 61cd90c19..6383a8ecd 100644 --- a/11-Reranker/04-FlashRank-Reranker.ipynb +++ b/11-Reranker/04-FlashRank-Reranker.ipynb @@ -16,9 +16,9 @@ "\n", "## Overview\n", "\n", - "> [FlashRank](https://github.com/PrithivirajDamodaran/FlashRank) is an ultra-lightweight and ultra-fast Python library designed to add reranking to existing search and `retrieval` pipelines. It is based on state-of-the-art (`SoTA`) `cross-encoders`.\n", + "> [FlashRank](https://github.com/PrithivirajDamodaran/FlashRank) is an ultra-lightweight and ultra-fast Python library designed to add reranking to existing search and **retrieval** pipelines. It is based on state-of-the-art (**SoTA**) **cross-encoders**.\n", "\n", - "This notebook introduces the use of `FlashRank-Reranker` within the LangChain framework, showcasing how to apply reranking techniques to improve the quality of search or `retrieval` results. It provides practical code examples and explanations for integrating `FlashRank` into a LangChain pipeline, highlighting its efficiency and effectiveness. The focus is on leveraging `FlashRank`'s capabilities to enhance the ranking of outputs in a streamlined and scalable way.\n", + "This notebook introduces the use of `FlashRank-Reranker` within the LangChain framework, showcasing how to apply reranking techniques to improve the quality of search or **retrieval** results. It provides practical code examples and explanations for integrating `FlashRank` into a LangChain pipeline, highlighting its efficiency and effectiveness. The focus is on leveraging `FlashRank`'s capabilities to enhance the ranking of outputs in a streamlined and scalable way.\n", "\n", "### Table of Contents\n", "\n", @@ -63,7 +63,7 @@ "id": "7d83ee066d91fb4f", "metadata": {}, "source": [ - "You can alternatively set OPENAI_API_KEY in .env file and load it.\n", + "You can alternatively set OPENAI_API_KEY in `.env` file and load it.\n", "\n", "[Note] This is not necessary if you've already set OPENAI_API_KEY in previous steps." ] @@ -137,7 +137,7 @@ "source": [ "## FlashrankRerank\n", "\n", - "Load data for a simple example and create a retriever." + "Load data for a simple example and create a **retriever**." ] }, { @@ -185,7 +185,7 @@ "id": "ea07e244c9171d26", "metadata": {}, "source": [ - "Now, let's wrap the base `retriever` with a `ContextualCompressionRetriever` and use `FlashrankRerank` as the compressor." + "Now, let's wrap the base **retriever** with a `ContextualCompressionRetriever` and use `FlashrankRerank` as the compressor." ] }, { @@ -224,7 +224,7 @@ "id": "4a147fc787860bac", "metadata": {}, "source": [ - "Compare the results after reanker is applied." + "Compare the results after reranker is applied." ] }, {