Update README.md

README.md

@@ -1,20 +1,30 @@
 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)
-#moving the model to device(GPU/CPU)
+
 
 def generate(text):
+
   model.eval()
   input_ids = tokenizer.encode("WebNLG:{} </s>".format(text), return_tensors="pt")  # Batch size 1
-  # input_ids.to(dev)
+
   s = time.time()
   outputs = model.generate(input_ids)
   gen_text=tokenizer.decode(outputs[0]).replace('<pad>','').replace('</s>','')
@@ -24,4 +34,5 @@ def generate(text):
   return gen_text
 
 
+
 generate(' Russia | leader | Putin')