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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))