Create app.py

app.py

@@ -0,0 +1,30 @@
+import streamlit as st
+from transformers import pipeline
+
+# Load the sentiment classifier model
+distilled_student_sentiment_classifier = pipeline(
+    model="lxyuan/distilbert-base-multilingual-cased-sentiments-student",
+    return_all_scores=True
+)
+
+# Define the Streamlit app
+def main():
+    # Add a title to the app
+    st.title("DistilBERT Sentiment Analysis")
+
+    # Add a text input field for user input
+    user_input = st.text_input("Enter text:")
+
+    # Perform sentiment analysis when the user submits input
+    if st.button("Analyze"):
+        # Perform sentiment analysis on the input text
+        result = distilled_student_sentiment_classifier(user_input)
+
+        # Display the sentiment analysis results
+        st.write("Sentiment Analysis Results:")
+        for item in result:
+            st.write(f"Label: {item['label']}, Score: {item['score']}")
+
+# Run the Streamlit app
+if __name__ == "__main__":
+    main()