Updated README.md

README.md

@@ -11,7 +11,7 @@ datasets:
 base_model:
   - google/efficientnet-b0
 model-index:
-  - name: EfficientNet_B0
+  - name: litert-community/efficientnet_b0
     results:
       - task:
           type: image-classification
@@ -53,8 +53,18 @@ acc@1 (on ImageNet-1K): 77.692%
 acc@5 (on ImageNet-1K): 93.532%    
 num_params: 5,288,548
 
+## How to Use
+
+**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.
+
+**3. Save the Script** Create a new file named `classify.py`, paste the script below into it, and save the file:
 
-## Use
 ```python
 #!/usr/bin/env python3
 import argparse, json
@@ -115,6 +125,14 @@ def main():
 if __name__ == "__main__":
     main()
 ```
+
+**4. Execute the Python Script**  Run the below command:
+
+```bash 
+python classify.py --image cat.jpg
+```
+
+
 ### BibTeX entry and citation info
 
 ```bibtex