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README.md

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+### Student Progress Tracking
+
+**Description:** Classify student assessment results to monitor their progress and identify areas that require improvement.
+
+## How to Use
+Here is how to use this model to classify text into different categories:
+
+        from transformers import AutoModelForSequenceClassification, AutoTokenizer
+        
+        model_name = "interneuronai/student_progress_tracking_bart"
+        model = AutoModelForSequenceClassification.from_pretrained(model_name)
+        tokenizer = AutoTokenizer.from_pretrained(model_name)
+        
+        def classify_text(text):
+            inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=512)
+            outputs = model(**inputs)
+            predictions = outputs.logits.argmax(-1)
+            return predictions.item()
+        
+        text = "Your text here"
+        print("Category:", classify_text(text))