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import streamlit as st
import time
from transformers import pipeline
import torch
st.markdown('## Text-generation OPT from Meta ')
@st.cache(allow_output_mutation=True)
def get_model():
return pipeline('text-generation', model=model)
col1, col2 = st.beta_columns([2,1])
with col2:
select_model = st.radio(
"Select the model to use:",
('OPT-125m', 'OPT-350m', 'OPT-1.3b'))
if select_model == 'OPT-1.3b':
model = 'facebook/opt-1.3b'
elif select_model == 'OPT-350m':
model = 'facebook/opt-350m'
elif select_model == 'OPT-125m':
model = 'facebook/opt-125m'
if select_model:
with st.spinner('Loading Model... (This may take a while)'):
generator = get_model()
#time.sleep(2)
st.success('Model loaded correctly!')
with col1:
prompt= st.text_area('Your prompt here',
'''AI will help humanity?''')
# answer = ['ciao come stai stutto bene']
# lst = ''.join(answer)
answer = generator(prompt, max_length=60, no_repeat_ngram_size=2, early_stopping=True, num_beams=5)
lst = answer[0]['generated_text']
t = st.empty()
for i in range(len(lst)):
t.markdown(" %s..." % lst[0:i])
time.sleep(0.04) |