.

pages/8_Models.py

@@ -22,10 +22,28 @@ def run():
     model = LogisticRegression()
     # (Insert a sample dataset and training procedure here)
 
+
+    # Deep Learning Example: Using Pretrained Transformers
+    st.write("### Example: Transformer Model for Sentiment Analysis")
+
+    # Initialize the NLP pipeline for sentiment analysis
+    nlp_pipeline = pipeline("sentiment-analysis")
+
+    def analyze_sentiment(user_sentence):
+        response = nlp_pipeline(user_sentence)
+        return response[0]
+
+    # Example usage
+    user_sentence = st.text_input("Enter a sentence for sentiment analysis:")
+    if user_sentence:
+        response = analyze_sentiment(user_sentence)
+        st.write(f"Sentiment: {response['label']}, Score: {response['score']}")
+
+
     # Deep Learning Example: Using Pretrained Transformers
-    st.write("### Example: Transformer Model")
-    nlp = pipeline("sentiment-analysis")
-    st.write(nlp("I love machine learning!"))
+    #st.write("### Example: Transformer Model")
+    #nlp = pipeline("sentiment-analysis")
+    #st.write(nlp("I love machine learning!"))
 
     st.write("## Quiz: Conceptual Questions")
     q1 = st.radio("What is a transformer model used for?", ["Text classification", "Image processing", "Time series analysis"])