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import streamlit as st
import time
from multipage import MultiPage
from transformers import pipeline
import torch
def app():
st.markdown('## Text Generation task')
st.write('Write something and AI will continue the sentence ')
st.markdown('## ')
@st.cache(allow_output_mutation=True, suppress_st_warning =True, show_spinner=False)
def get_model():
return pipeline('text-generation', model=model, do_sample=True, skip_special_tokens=True)
col1, col2 = st.columns([2,1])
with col1:
prompt= st.text_area('Your prompt here',
'''Who is Elon Musk?''')
with col2:
select_model = st.radio(
"Select the model to use:",
('OPT-125m', 'OPT-350m'), index = 1)
if select_model == 'OPT-350m':
model = 'facebook/opt-350m'
elif select_model == 'OPT-125m':
model = 'facebook/opt-125m'
with st.spinner('Loading Model... (This may take a while)'):
generator = get_model()
st.success('Model loaded correctly!')
with col1:
gen = st.info('Generating text...')
answer = generator(prompt,
max_length=80, no_repeat_ngram_size=2,
early_stopping=True, num_beams=8,
skip_special_tokens=True)
gen.empty()
lst = answer[0]['generated_text']
t = st.empty()
for i in range(len(lst)):
t.markdown("#### %s..." % lst[0:i])
time.sleep(0.04)
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