Update README.md

README.md

@@ -65,17 +65,20 @@ id2label = {idx: label for label, idx in label2id.items()}
 model = AutoModelForSequenceClassification.from_pretrained("atulgupta002/banking_customer_service_query_intent_classifier")
 tokenizer = AutoTokenizer.from_pretrained("atulgupta002/banking_customer_service_query_intent_classifier")
 
-# Example text input
-query = "I want to apply for a new credit card"
+def predict(text):
+    inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
+    
+    with torch.no_grad():
+        outputs = model(**inputs)
+        logits = outputs.logits
+        predicted_class_id = logits.argmax().item()
 
-# Tokenize input text
-inputs = tokenizer(query, return_tensors="pt", truncation=True, padding=True)
+    return id2label[predicted_class_id]
 
-# Get model prediction
-outputs = model(**inputs)
-logits = outputs.logits
+query = "I want to apply for a new credit card"
+print(predict(query))
+```
 
-# Get predicted intent class
-predicted_class = logits.argmax().item()
-print(f"Predicted intent: {id2label[predicted_class]}")
+## Sample output
 
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/643c6f86ae8d93dc39515286/2Y4ty_VgbvBOigWAQwHIS.png)