add example usage of model

README.md

@@ -177,6 +177,61 @@ Hardware: GPU (CUDA)
 
 ---
 
+# Example Usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+# Load model and tokenizer
+model_name = "learn-abc/banking-multilingual-intent-classifier"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model.to(device)
+model.eval()
+
+# Prediction function
+def predict_intent(text):
+    inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=64)
+    inputs = {k: v.to(device) for k, v in inputs.items()}
+    
+    with torch.no_grad():
+        outputs = model(**inputs)
+        prediction = torch.argmax(outputs.logits, dim=-1).item()
+        confidence = torch.softmax(outputs.logits, dim=-1)[0][prediction].item()
+    
+    predicted_intent = model.config.id2label[prediction]
+    
+    return {
+        "intent": predicted_intent,
+        "confidence": confidence
+    }
+
+# Example usage - English
+result = predict_intent("what is my balance")
+print(f"Intent: {result['intent']}, Confidence: {result['confidence']:.2f}")
+# Output: Intent: CHECK_BALANCE, Confidence: 0.99
+
+# Example usage - Bangla
+result = predict_intent("আমার ব্যালেন্স কত")
+print(f"Intent: {result['intent']}, Confidence: {result['confidence']:.2f}")
+# Output: Intent: CHECK_BALANCE, Confidence: 0.98
+
+# Example usage - Banglish (Romanized)
+result = predict_intent("amar balance koto ache")
+print(f"Intent: {result['intent']}, Confidence: {result['confidence']:.2f}")
+# Output: Intent: CHECK_BALANCE, Confidence: 0.97
+
+# Example usage - Code-mixed
+result = predict_intent("আমার last 10 transaction দেখাও")
+print(f"Intent: {result['intent']}, Confidence: {result['confidence']:.2f}")
+# Output: Intent: MINI_STATEMENT, Confidence: 0.98
+```
+
+---
+
 ## 8. Strengths
 
 * Strong multilingual generalization