Update README.md

README.md

@@ -19,30 +19,5 @@ 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}")
-
-
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/65dd9dc387458446d0a9da32/MlAfwDkAouKP5iWtzqHPj.png)