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import streamlit as st
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import torch
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import pandas as pd
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st.write("""# Summerize your text""")
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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tokenizer = AutoTokenizer.from_pretrained("tokenizer")
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model = AutoModelForSeq2SeqLM.from_pretrained("pegasus_summery_model")
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text_input = st.text_area("text to summerize")
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if text_input:
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tokenized_text = tokenizer.encode_plus(
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str(text_input),
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return_attention_mask= True,
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return_tensors='pt'
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)
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generated_token = model.generate(
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input_ids = tokenized_text['input_ids'],
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attention_mask = tokenized_text["attention_mask"],
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use_cache=True,)
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pred = [tokenizer.decode(token_ids=ids, skip_special_tokens=True)for ids in generated_token]
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st.write("## Summerized Text")
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st.write(" ".join(pred)) |