Update README.md

README.md

@@ -4,26 +4,22 @@ tags: []
 ---
 
 ## Model Usage
+```
 import gradio as gr
 from transformers import pipeline
 from PIL import Image
 import numpy as np
 
-### Define function to perform inference
 def predict_image(image):
-    # Initialize the pipeline outside the function if possible for efficiency
     pipe = pipeline("image-classification", model="itsTomLie/Jaundice_Classifier")
 
-    # Convert NumPy array to PIL Image if necessary
     if isinstance(image, np.ndarray):
         image = Image.fromarray(image.astype('uint8'))
-    elif isinstance(image, str):  # If image is a file path
+    elif isinstance(image, str): 
         image = Image.open(image)
 
-    # Perform prediction
     result = pipe(image)
 
-    # Extract label and confidence
     label = result[0]['label']
     confidence = result[0]['score']
 
@@ -31,7 +27,6 @@ def predict_image(image):
 
     return label, confidence
 
-### Create Gradio interface
 interface = gr.Interface(
     fn=predict_image,
     inputs=gr.Image(type="numpy", label="Upload an Image"),
@@ -39,7 +34,7 @@ interface = gr.Interface(
 )
 
 interface.launch(debug=True)
-
+```
 
 # Model Card for Model ID