Update README.md

README.md

@@ -144,13 +144,34 @@ Users (both direct and downstream) should be aware of the following recommendati
 Use the code below to get started with the model:
 
 ```python
-from transformers import pipeline
-
-classifier = pipeline("text-classification", model="LaciaStudio/Luna_v1")
-
-text = "text-example"
-result = classifier(text)
-print(result)
+import pickle
+import re
+import numpy as np
+import tensorflow as tf
+
+model = tf.keras.models.load_model("path/to/model.h5") 
+with open("path/to/vectorizer.pkl", "rb") as vec_file:
+    vectorizer = pickle.load(vec_file)
+
+def clean_text(text):
+    return re.sub(r"[^\w\s]", "", text).lower()
+
+def classify_text(text, threshold=0.5):
+    text = clean_text(text)
+    words = text.split()
+    X = vectorizer.transform(words).toarray()
+    predictions = model.predict(X)
+    result = {}
+    for word, pred in zip(words, predictions):
+        result[word] = {"probability": round(float(pred), 3), "classification": "Dirty word" if pred >= threshold else "Normal"}
+    return result
+
+if __name__ == "__main__":
+    text = "text example here"
+    result = classify_text(text)
+    print("Classification result:")
+    for word, data in result.items():
+        print(f"{word}: {data['probability']} ({data['classification']})")
 ```
 
 ## Training Details