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