Update README.md

README.md

@@ -22,31 +22,20 @@ import joblib
 model = joblib.load(
 	hf_hub_download("DineshKumar1329/Sentiment_Analysis", "sklearn_model.joblib")
 )
-# only load pickle files from sources you trust
-# read more about it here https://skops.readthedocs.io/en/stable/persistence.html
 
-# Load the TF-IDF vectorizer used during training
 tfidf_vectorizer = joblib.load('/content/vectorizer_model.joblib')  # Replace with your actual filename
 
-
-# Take user input
 user_input = input("Enter a sentence: ")
 
-# Clean the user input
 cleaned_input = clean_text(user_input)
 
-# Transform the cleaned text data using the TF-IDF vectorizer
 input_matrix = tfidf_vectorizer.transform([cleaned_input])
 
-# Make prediction
 prediction = model.predict(input_matrix)[0]
 
-# Display the prediction
 print(f"Predicted Sentiment: {prediction}")
-# Create a DataFrame with the results
 df_result = pd.DataFrame({'User_Input': [user_input], 'Predicted_Sentiment': [prediction]})
 
-# Save the DataFrame to an Excel file (append if the file already exists)
 excel_filename = '/content/output_predictions.xlsx'  # Replace with your desired filename
 try:
     # Load existing predictions from the Excel file
@@ -59,5 +48,4 @@ except FileNotFoundError:
     # If the file doesn't exist, create a new DataFrame
     df_combined = df_result
 
-# Save the combined DataFrame to the Excel file
 df_combined.to_excel(excel_filename, index=False)