diff --git a/docs/GPTQ-models-(4-bit-mode).md b/docs/GPTQ-models-(4-bit-mode).md
index 8eaf86ca..a576213f 100644
--- a/docs/GPTQ-models-(4-bit-mode).md
+++ b/docs/GPTQ-models-(4-bit-mode).md
@@ -6,7 +6,7 @@ AutoGPTQ is the recommended way to create new quantized models: https://github.c
 
 ### Installation
 
-To load a model quantized with AutoGPTQ in the web UI, manual installation is currently necessary:
+To load a model quantized with AutoGPTQ in the web UI, you need to first manually install the AutoGPTQ library:
 
 ```
 conda activate textgen
@@ -14,11 +14,11 @@ git clone https://github.com/PanQiWei/AutoGPTQ.git && cd AutoGPTQ
 pip install .
 ```
 
-You are going to need to have `nvcc` installed (see the [instructions below](https://github.com/oobabooga/text-generation-webui/blob/main/docs/GPTQ-models-(4-bit-mode).md#step-0-install-nvcc)).
+The last command requires `nvcc` to be installed (see the [instructions below](https://github.com/oobabooga/text-generation-webui/blob/main/docs/GPTQ-models-(4-bit-mode).md#step-0-install-nvcc)).
 
 ### Usage
 
-Place the output folder generated by AutoGPTQ in your `models/` folder and load it with the `--autogptq` flag:
+When you quantize a model using AutoGPTQ, a folder containing a filed called `quantize_config.json` will be generated. Place that folder inside your `models/` folder and load it with the `--autogptq` flag:
 
 ```
 python server.py --autogptq --model model_name