Update app.py

app.py

@@ -3,6 +3,7 @@ import altair as alt
 import torch
 from transformers import AlbertTokenizer, AlbertForSequenceClassification
 import sentencepiece as spm
+import pandas as pd
 
 # Load pre-trained model and tokenizer
 model_name = "albert-base-v2"
@@ -21,7 +22,9 @@ def classify_text(text):
 st.title("ALBERT Text Classification App")
 
 # Create input box for user to enter text
-text_input = st.text_area("Enter text to classify", height=200)
+default_text = "Streamlit-Altair: A component that allows the creation of Altair visualizations within Streamlit.\nStreamlit-Bokeh: A component that allows the creation of Bokeh visualizations within Streamlit.\nStreamlit-Plotly: A component that allows the creation of Plotly visualizations within Streamlit.\nStreamlit-Mapbox: A component that allows the creation of Mapbox maps within Streamlit.\nStreamlit-DeckGL: A component that allows the creation of Deck.GL visualizations within Streamlit.\nStreamlit-Wordcloud: A component that allows the creation of word clouds within Streamlit.\nStreamlit-Audio: A component that allows the playing of audio files within Streamlit.\nStreamlit-Video: A component that allows the playing of video files within Streamlit.\nStreamlit-EmbedCode: A component that allows the embedding of code snippets within Streamlit.\nStreamlit-Components: A component that provides a library of custom Streamlit components created by the Streamlit community."
+text_input = st.text_area("Enter text to classify", default_text, height=200)
+
 
 # Classify input text and display results
 if st.button("Classify"):