import streamlit as st
from transformers import AutoTokenizer
from transformers import TFAUTOModelForSequenceClassification 
import tensorflow as tf

tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased')
model = TFAUTOModelForSequenceClassification.from_pretrained('./')



text = st.text_area('Your StackOverFlow Question')

def preprocess_predict(text):
    inputs = tokenizer.encode(text,
         add_special_tokens = True,
         padding='max_length', 
         truncation=True, 
         max_length=SEQ_LEN, 
         return_token_type_ids=False,
         return_tensors = 'tf')
     
     preds = model.predict(imputs)
     probabilities = tf.nn.softmax(preds['logits'])
     class_preds = np.argmax(probabilities,axis=1)
         
  return class_preds
  
 
if text =True
     out = preprocess_predict(text)
     st.json(out)