| |
| import streamlit as st |
| from transformers import BartForConditionalGeneration, BartTokenizer |
|
|
| |
| model_name = "facebook/bart-large-cnn" |
| model = BartForConditionalGeneration.from_pretrained(model_name) |
| tokenizer = BartTokenizer.from_pretrained(model_name) |
|
|
| |
| st.title("ANavya Text Summarizer") |
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|
| |
| text_input = st.text_area("Enter Text Here:") |
|
|
| |
| 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 |
|
|
| |
| if st.button("Submit", key="ANavya"): |
| if text_input: |
| st.subheader("Summary:") |
| summary = summarize_text(text_input) |
| st.write(summary) |
|
|
| |
| st.sidebar.markdown("Created by [Team Anavya]") |
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|
