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from transformers import AutoTokenizer, AutoModelForSequenceClassification | |
import streamlit as st | |
import torch | |
import requests | |
from bs4 import BeautifulSoup | |
import re | |
import pandas as pd | |
import numpy as np | |
st.title("Hugging Face Sentiment Analysis Spaces Example") | |
st.subheader("What framework would you like to use for Sentiment Analysis") | |
#tokenizer to break the text into tokens to feed into the model | |
tokenizer = AutoTokenizer.from_pretrained('nlptown/bert-base-multilingual-uncased-sentiment') | |
#model actually processing and using the transformer | |
model = AutoModelForSequenceClassification.from_pretrained("nlptown/bert-base-multilingual-uncased-sentiment") | |
#pipeline to predict review score | |
# def predict(review): | |