Update README.md

README.md

@@ -17,4 +17,36 @@ The sentiment analysis model is trained using a Support Vector Machine (SVM) cla
 
 
 
+# Usage :
+
+from huggingface_hub import hf_hub_download
+import joblib
+from sklearn.preprocessing import LabelEncoder
+
+model = joblib.load(
+    hf_hub_download("DineshKumar1329/Sentiment_Analysis", "sklearn_model.joblib")
+)
+
+tfidf_vectorizer = joblib.load('/content/vectorizer_model.joblib')  # Replace with your path
+
+def clean_text(text):
+  return text.lower()
+
+def predict_sentiment(user_input):
+  """Predicts sentiment for a given user input."""
+  cleaned_text = clean_text(user_input)
+  input_matrix = tfidf_vectorizer.transform([cleaned_text])
+  prediction = model.predict(input_matrix)[0]
+
+  if isinstance(model.classes_, LabelEncoder):
+    prediction = model.classes_.inverse_transform([prediction])[0]
+
+  return prediction
+
+user_input = input("Enter a sentence: ")
+
+predicted_sentiment = predict_sentiment(user_input)
+
+print(f"Predicted Sentiment: {predicted_sentiment}")
+