Update README.md

README.md

@@ -148,7 +148,7 @@ model = AutoModelForSequenceClassification.from_pretrained(model_name)
 model.eval()
 
 # 🧪 Example input
-text = "Turn off the fan"
+text = "Turn on the fan"
 
 # ✂️ Tokenize the input
 inputs = tokenizer(text, return_tensors="pt")
@@ -169,8 +169,8 @@ print(f"Predicted intent: {labels[pred]} (Confidence: {probs[0][pred]:.4f})")
 
 **Output**:
 ```plaintext
-Text: Turn off the fan
-Predicted intent: OFF (Confidence: 0.7824)
+Text: Turn on the fan
+Predicted intent: ON (Confidence: 0.7824)
 ```
 
 *Note*: Fine-tune the model for specific classification tasks to improve accuracy.