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