Update app.py

app.py

@@ -37,21 +37,21 @@ warnings.filterwarnings("ignore")
 # Models #
 ###############################################
 
-# summary_model = T5ForConditionalGeneration.from_pretrained('t5-base')
-# summary_tokenizer = T5Tokenizer.from_pretrained('t5-base')
-# device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-# summary_model = summary_model.to(device)
+summary_model = T5ForConditionalGeneration.from_pretrained('t5-base')
+summary_tokenizer = T5Tokenizer.from_pretrained('t5-base')
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+summary_model = summary_model.to(device)
 
 
-# glove_file = 'glove.6B.300d.txt'
-# tmp_file = 'word2vec-glove.6B.300d.txt'
-# glove2word2vec(glove_file, tmp_file)
-# model = KeyedVectors.load_word2vec_format(tmp_file)
+glove_file = 'glove.6B.300d.txt'
+tmp_file = 'word2vec-glove.6B.300d.txt'
+glove2word2vec(glove_file, tmp_file)
+model = KeyedVectors.load_word2vec_format(tmp_file)
 
 
-# question_model = T5ForConditionalGeneration.from_pretrained('ramsrigouthamg/t5_squad_v1')
-# question_tokenizer = T5Tokenizer.from_pretrained('ramsrigouthamg/t5_squad_v1')
-# question_model = question_model.to(device)
+question_model = T5ForConditionalGeneration.from_pretrained('ramsrigouthamg/t5_squad_v1')
+question_tokenizer = T5Tokenizer.from_pretrained('ramsrigouthamg/t5_squad_v1')
+question_model = question_model.to(device)
 
 ###############################################
 def Process_audio(fileName):