Create app.py

app.py

@@ -0,0 +1,26 @@
+import streamlit as st
+from transformers import pipeline
+from datasets import load_dataset
+
+ds = load_dataset("abisee/cnn_dailymail", "3.0.0")
+t5_sum = pipeline("summarization", model= "t5-small")
+
+# Set the title for the Streamlit app
+st.title("T5 Summary Generator")
+
+# Text input for the user
+text = st.text_area("Enter your text: ")
+
+def generate_summaries_and_context(dataset_sample):
+    article = dataset_sample
+    summary = summarizer(article, max_length=150, min_length=40, do_sample=False)
+    
+    return summary[0]['summary_text']
+
+if st.button("Generate"):
+    generated_text = generate_text(text)
+    if generated_text:
+        # Display the generated text
+        st.subheader("Generated Blog Post")
+        st.write(generated_text)
+