readme: import pandas as pd
  
  import os
  
  import torch
  
  from transformers import T5Tokenizer, T5ForConditionalGeneration
  
  from transformers.optimization import  Adafactor 
  
  import time
  
  import warnings
  
  warnings.filterwarnings('ignore')
  
  
  tokenizer = T5Tokenizer.from_pretrained('Sachinkelenjaguri/sa_T5_Table_to_text')
  
  model = T5ForConditionalGeneration.from_pretrained('Sachinkelenjaguri/sa_T5_Table_to_text', return_dict=True)
  
  
  def generate(text):
  
    model.eval()
    input_ids = tokenizer.encode("WebNLG:{} </s>".format(text), return_tensors="pt")  # Batch size 1
  
    s = time.time()
    outputs = model.generate(input_ids)
    gen_text=tokenizer.decode(outputs[0]).replace('<pad>','').replace('</s>','')
    elapsed = time.time() - s
    print('Generated in {} seconds'.format(str(elapsed)[:4]))
    
    return gen_text
  
  
  
  generate(' Russia | leader | Putin')