Update README.md

README.md

@@ -13,4 +13,27 @@ pipeline_tag: image-classification
 **DagsHub & Mlflow Experiement Tracking:** [Here](https://dagshub.com/andrewmayes14/mlflow/experiments/#/)
 
 ## Project Overview
-As a volunteer at 'Le Refuge,' a local animal protection association, I embarked on a mission to develop a machine learning tool that could aid in the classification of dog breeds from their vast image database. The project was inspired by my own experience finding my beloved pet, Snooky, through this association. To give back, I aimed to streamline their data management process by implementing an advanced breed classification algorithm.
+As a volunteer at 'Le Refuge,' a local animal protection association, I embarked on a mission to develop a machine learning tool that could aid in the classification of dog breeds from their vast image database. The project was inspired by my own experience finding my beloved pet, Snooky, through this association. To give back, I aimed to streamline their data management process by implementing an advanced breed classification algorithm.
+
+```python
+from transformers import pipeline
+
+# Specify the model you want to use
+model_name = "amaye15/ViT-Standford-Dogs"  # Example: Vision Transformer
+
+# Load the image classification pipeline with the specified model
+image_classifier = pipeline("image-classification", model=model_name)
+
+# Path or URL to your image
+image_path_or_url = "path_or_url_to_your_image"
+
+# Get predictions
+predictions = image_classifier(image_path_or_url)
+
+# Define the number of top predictions you want to see (top k)
+top_k = 5
+
+# Print the top k predictions
+for prediction in predictions[:top_k]:
+    print(f"Class: {prediction['label']}, Confidence: {prediction['score']:.2f}")
+```