From 496ffcfea91c2652aedeaf1aaef2b902b4f9b77c Mon Sep 17 00:00:00 2001
From: redoomed1 <161974310+redoomed1@users.noreply.github.com>
Date: Fri, 15 Nov 2024 09:15:51 -0800
Subject: [PATCH] Apply suggestion from code review

Co-Authored-By: fria <138676274+friadev@users.noreply.github.com>
Co-Authored-By: Triple T <78900789+I-I-IT@users.noreply.github.com>

Signed-off-by: redoomed1 <161974310+redoomed1@users.noreply.github.com>
---
 docs/ai-chat.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/ai-chat.md b/docs/ai-chat.md
index 0c8f89a97a..636cca96cc 100755
--- a/docs/ai-chat.md
+++ b/docs/ai-chat.md
@@ -23,7 +23,7 @@ Alternatively, you can run AI models locally so that your data never leaves your
 
 ## Hardware for Local AI Models
 
-Local models are also fairly accessible. It's possible to run smaller models at lower speeds on as little as 8GB of RAM. Using more powerful hardware such as a dedicated GPU with sufficient VRAM or a modern system with fast LPDDR5X memory will offer the best experience.
+Local models are also fairly accessible. It's possible to run smaller models at lower speeds on as little as 8GB of RAM. Using more powerful hardware such as a dedicated GPU with sufficient VRAM or a modern system with fast LPDDR5X memory offers the best experience.
 
 LLMs can usually be differentiated by the number of parameters, which can vary between 1.3B to 405B for open-source models available for end users. For example, models below 6.7B parameters are only good for basic tasks like text summaries, while models between 7B and 13B are a great compromise between quality and speed. Models with advanced reasoning capabilities are generally around 70B.