Update app.py

app.py

@@ -18,12 +18,13 @@ def predict(input, history=[]):
     history = model.generate(bot_input_ids,
                             max_length=1000,
                             pad_token_id=tokenizer.eos_token_id,
-                            no_repeat_ngram_size=3,
-                            num_beams = 3,
-                            do_sample=True,
-                            top_k=20,
-                            top_p=0.8,
-                            temperature=0.8).tolist()
+                            #no_repeat_ngram_size=3,
+                            #num_beams = 3,
+                            #do_sample=True,
+                            #top_k=20,
+                            #top_p=0.8,
+                            #temperature=0.8
+                            ).tolist()
 
     # convert the tokens to text, and then split the responses into the right format
     response = tokenizer.decode(history[0]).split("<|endoftext|>")