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45680a7 da92290 0fbbee1 da92290 0fbbee1 70bf880 0fbbee1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | import os
os.system("pip install transformers")
os.system("pip install sentencepiece")
os.system("pip install torch torchvision")
import streamlit as st
from transformers import T5Tokenizer, T5ForConditionalGeneration
tokenizer = T5Tokenizer.from_pretrained("t5-base")
model = T5ForConditionalGeneration.from_pretrained("t5-base")
st.title('T5 Text Generation App')
st.write('Enter the text you want to generate:')
input_text = st.text_input('Input Text', 'Once upon a time,')
if st.button('Generate Text'):
input_text = input_text.strip()
input_text = "generate text:{}".format(input_text) # Add the generation prefix
input_ids = tokenizer.encode(input_text, return_tensors='pt', max_length=512, truncation=True)
outputs = model.generate(input_ids, max_length=512) # Specify the maximum length of the generated text
generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
st.write('Generated Text:')
st.write(generated_text)
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