Update README.md

README.md

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 license: unknown
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+## How to Use
+
+Here is an example of how to use this model to get predictions and convert them back to labels:
+
+```python
+import tensorflow as tf
+from transformers import TFAutoModelForSequenceClassification, AutoTokenizer
+import joblib
+
+# Load the model and tokenizer
+model = TFAutoModelForSequenceClassification.from_pretrained("NeuEraAI/Stress_Classifier_BERT")
+tokenizer = AutoTokenizer.from_pretrained("NeuEraAI/Stress_Classifier_BERT")
+
+# Load your label encoder
+label_encoder = joblib.load("label_encoder.joblib")
+
+def decode_predictions(predictions):
+    # Extract predicted indices (assuming predictions is a list of dicts with 'label' keys)
+    predicted_indices = [int(pred['label'].split('_')[-1]) for pred in predictions]
+    # Decode the indices to original labels
+    decoded_labels = label_encoder.inverse_transform(predicted_indices)
+    return decoded_labels
+
+# Example usage
+text = "Your example input text here."
+decode_predictions(model.predict(text))