From 2420957f8b9fd16c0735c1809fe4a75c7db0f730 Mon Sep 17 00:00:00 2001
From: Christopher Sharkey <ev2900@gmail.com>
Date: Sat, 16 Nov 2024 13:08:30 -0500
Subject: [PATCH] Updating downloads

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 README.md | 2 +-
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 # OpenSearch kNN Vector Search
 
-<img width="275" alt="map-user" src="https://img.shields.io/badge/cloudformation template deployments-16-blue"> <img width="85" alt="map-user" src="https://img.shields.io/badge/views-2292-green"> <img width="125" alt="map-user" src="https://img.shields.io/badge/unique visits-796-green">
+<img width="275" alt="map-user" src="https://img.shields.io/badge/cloudformation template deployments-16-blue"> <img width="85" alt="map-user" src="https://img.shields.io/badge/views-2300-green"> <img width="125" alt="map-user" src="https://img.shields.io/badge/unique visits-796-green">
 
 This example uses the publicly avaiable [Amazon Product Question Answer](https://registry.opendata.aws/amazon-pqa/) (PQA) data set. In this example, the questions in the PQA data set are tokenized and represented as vectors. BERT via. Hugging Face is used to generate the embeddings. The vector representation of the questions (embeddings) are loading to an OpenSearch index as a *knn_vector* data type