Create app.py

app.py

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+import streamlit as st
+from transformers import pipeline
+
+model_name = "Safna/abstractive" 
+
+summarizer = pipeline("summarization", model= AutoModelForSeq2SeqLM.from_pretrained(model_name), tokenizer= AutoTokenizer.from_pretrained("sshleifer/distilbart-xsum-12-3"))
+
+
+st.title("Text Summarization App")
+
+input_text = st.text_area("Enter the text you want to summarize:")
+
+if st.button("Generate Summary"):
+    if input_text:
+        with st.spinner("Generating summary..."):
+            summary = summarizer(input_text, max_length=64, min_length=10, length_penalty=2.0, num_beams=4, early_stopping=True)
+        st.subheader("Generated Summary:")
+        st.write(summary[0]["summary_text"])
+
+# Instructions
+st.sidebar.header("Instructions")
+st.sidebar.markdown("1. Enter the text you want to summarize.")
+st.sidebar.markdown("2. Click the 'Generate Summary' button.")