Upload check.py

check.py

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+# import necessary libraries
+import streamlit as st
+from transformers import BartForConditionalGeneration, BartTokenizer
+
+# Load BART model and tokenizer
+model_name = "facebook/bart-large-cnn"
+model = BartForConditionalGeneration.from_pretrained(model_name)
+tokenizer = BartTokenizer.from_pretrained(model_name)
+
+# Streamlit app
+st.title("ANavya Text Summarizer")
+
+# Create a text input box
+text_input = st.text_area("Enter Text Here:")
+
+# Function to summarize text
+def summarize_text(text):
+    input_ids = tokenizer.encode(text, return_tensors="pt", max_length=1024, truncation=True)
+    summary_ids = model.generate(input_ids, max_length=150, min_length=40, length_penalty=2.0, num_beams=4, early_stopping=True)
+    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+    return summary
+
+# Create a submit button
+if st.button("Submit", key="ANavya"):
+    if text_input:
+        st.subheader("Summary:")
+        summary = summarize_text(text_input)
+        st.write(summary)
+
+# Display a footer or additional information
+st.sidebar.markdown("Created by [Team Anavya]")
+