Update README.md

README.md

@@ -24,22 +24,22 @@ To use the emo-Classification model, you can utilize the Hugging Face Transforme
 from transformers import pipeline
 
 # Initialize the classifier
-classifier = pipeline(task="text-classification", model="Abhaykoul/emo-Classification", top_k=1)
+classifier = pipeline(task="text-classification", model="AI4free/emo-Classification", top_k=1)
 
-# Define the sentence to analyze
+# Define the sentence to analyze# Define the sentence to analyze
 sentences = ["I am not having a great day"]
 
 # Get the model output
 model_outputs = classifier(sentences)
 
 # Print the top emotion (first one in the list)
-print(f"Top emotion: {model_outputs[0][0]['label']} (Score: {model_outputs[0][0]['score']:.4f})")
+print(f"emotion: {model_outputs[0][0]['label']} (Score: {model_outputs[0][0]['score']:.4f})")
 ```
 
 ### Example Input and Output
 
 - **Input**: `"I am not having a great day"`
-- **Output**: `Top emotion: <emotion_label> (Score: <score>)`
+- **Output**: `emotion: <emotion_label> (Score: <score>)`
 
 ## Installation