Fix AutoGPTQ version to 0.2.2 in requirements.txt. Adapt README.md.

Right now AutoGPTQ 0.3 is installed from requirements.txt and users are then asked to uninstall that and install AutoGPTQ 0.2.2 from source. It is much easier to fix the version to 0.2.2 in requirements.txt in the first place.
Also fix some README.md issues.

README.md

@@ -18,7 +18,7 @@ Install conda
 conda create -n localGPT
 ```
 
-Activate 
+Activate
 
 ```shell
 conda activate localGPT
@@ -30,17 +30,6 @@ In order to set your environment up to run the code here, first install all requ
 pip install -r requirements.txt
 ```
 
-Then install AutoGPTQ - if you want to run quantized models for GPU
-
-```shell
-git clone https://github.com/PanQiWei/AutoGPTQ.git
-cd AutoGPTQ
-git checkout v0.2.2
-pip install .
-```
-
-For more support on [AutoGPTQ] (https://github.com/PanQiWei/AutoGPTQ).
-
 ## Test dataset
 
 This repo uses a [Constitution of USA ](https://constitutioncenter.org/media/files/constitution.pdf) as an example.
@@ -57,7 +46,7 @@ Run the following command to ingest all the data.
 `defaults to cuda`
 
 ```shell
-python ingest.py 
+python ingest.py
 ```
 
 Use the device type argument to specify a given device.
@@ -120,7 +109,7 @@ GGML quantized models for Apple Silicon (M1/M2) are supported through the llama-
 
 ## Troubleshooting
 
-**Install MPS:**  
+**Install MPS:**
 1- Follow this [page](https://developer.apple.com/metal/pytorch/) to build up PyTorch with Metal Performance Shaders (MPS) support. PyTorch uses the new MPS backend for GPU training acceleration. It is good practice to verify mps support using a simple Python script as mentioned in the provided link.
 
 2- By following the page, here is an example of what you may initiate in your terminal
@@ -136,7 +125,7 @@ pip install pdfminer.six
 pip install xformers
 ```
 
-**Upgrade packages:**  
+**Upgrade packages:**
 Your langchain or llama-cpp version could be outdated. Upgrade your packages by running install again.
 
 ```shell
@@ -278,7 +267,7 @@ This is a test project to validate the feasibility of a fully local solution for
       ```shell
          conda install -c pytorch torchvision cudatoolkit=10.1 pytorch
       ```
-   - If doesn't work try re installing 
+   - If doesn't work, try reinstalling
       ```shell
          pip uninstall torch
          pip cache purge

requirements.txt

@@ -11,7 +11,7 @@ transformers
 protobuf==3.20.0; sys_platform != 'darwin'
 protobuf==3.20.0; sys_platform == 'darwin' and platform_machine != 'arm64'
 protobuf==3.20.3; sys_platform == 'darwin' and platform_machine == 'arm64'
-auto-gptq
+auto-gptq==0.2.2
 docx2txt
 
 # Utilities