Update app.py

app.py

@@ -5,7 +5,7 @@ import transformers
 bert_mlm_positive, bert_mlm_negative, bert_clf, tokenizer = torch.load('model.pt', map_location='cpu')
 
 def get_replacements(sentence: str, num_tokens, k_best, epsilon=1e-3):
-  tokens_info = tokenizer(sentence, return_tensors="pt").to(device)
+  tokens_info = tokenizer(sentence, return_tensors="pt")
   probs_positive = bert_mlm_positive(**tokens_info).logits.softmax(dim=-1)[0]
   probs_neagtive = bert_mlm_negative(**tokens_info).logits.softmax(dim=-1)[0]
   
@@ -34,7 +34,7 @@ def beamsearch(sentence: str, max_word_changes: int, k_best: int, beam_size:int)
       new_beam = list(set(new_beam))
       clf_probs = []
       for line in new_beam:
-        tokens_info = tokenizer(line, return_tensors="pt").to(device)
+        tokens_info = tokenizer(line, return_tensors="pt")
         clf_probs.append(bert_clf(**tokens_info).logits.softmax(dim=-1)[0][1])
       top_indexes = np.argsort(clf_probs)[-beam_size:]
       beam = [new_beam[i] for i in top_indexes]