Create app.py

app.py

@@ -0,0 +1,23 @@
+import streamlit as st
+import transformers
+import numpy as np
+
+# Load the pre-trained model
+model = transformers.pipeline("text2text-generation", model="mrm8488/t5-base-finetuned-topic-modeling")
+
+# Define the Streamlit app
+def main():
+    st.title("Topic Modeling with Hugging Face")
+    text = st.text_area("Enter some text to generate topics", height=200)
+
+    if st.button("Generate Topics"):
+        # Generate topics
+        topics = model(text, max_length=50, do_sample=True, num_beams=5, temperature=0.7)
+
+        # Print topics
+        st.write("Top 5 topics:")
+        for i in range(5):
+            st.write(f"{i+1}. {topics[i]['generated_text']}")
+
+if __name__ == "__main__":
+    main()