Update README.md

README.md

@@ -30,7 +30,7 @@ model-index:
 
 # AlexNet
 
-The AlexNet architecture is a convolutional neural network pre-trained on the ImageNet-1k dataset. Originally introduced by Krizhevsky et al. in the landmark paper, [**ImageNet Classification with Deep Convolutional Neural Networks,**](https://papers.nips.cc/paper/2012/hash/c399862d3b9d6b76c8436e924a68c45b-Abstract.html), this model utilized deep layers and GPU acceleration to prove the effectiveness of deep learning.
+The AlexNet architecture is a convolutional neural network pre-trained on the ImageNet-1k dataset. Originally introduced by Krizhevsky et al. in the landmark paper, [**ImageNet Classification with Deep Convolutional Neural Networks**](https://papers.nips.cc/paper/2012/hash/c399862d3b9d6b76c8436e924a68c45b-Abstract.html), this model utilized deep layers and GPU acceleration to prove the effectiveness of deep learning.
 
 
 ## Model description
@@ -48,11 +48,11 @@ The model files were converted from pretrained weights from PyTorch Vision. The
 
 ## How to Use
 
-​​**1. Install Dependencies** Ensure your Python environment is set up with the required libraries. Run the following command in your terminal:   
+**1. Install Dependencies** Ensure your Python environment is set up with the required libraries. Run the following command in your terminal:   
 
 ```bash 
 pip install numpy Pillow huggingface_hub ai-edge-litert
-
+```
 
 
 **2. Prepare Your Image** The script expects an image file to analyze. Make sure you have an image (e.g., cat.jpg or car.png) saved in the same working directory as your script.
@@ -124,6 +124,7 @@ if __name__ == "__main__":
 
 ```bash 
 python classify.py --image cat.jpg
+```
 
 ### BibTeX entry and citation info