Update README.md

README.md

@@ -24,10 +24,13 @@ LUKE achieves state-of-the-art results on five popular NLP benchmarks including
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 import torch
+
 from transformers import MLukeTokenizer
+
 from torch import nn 
 
 tokenizer = MLukeTokenizer.from_pretrained('studio-ousia/luke-japanese-base-lite')
+
 model = torch.load('C:\\[My_luke_model_pn.pthのあるディレクトリ]\\My_luke_model_pn.pth')
 
 text=input()
@@ -40,10 +43,13 @@ encoded_dict = tokenizer.encode_plus(
 
 pre = model(encoded_dict['input_ids'], token_type_ids=None, attention_mask=encoded_dict['attention_mask'])
 SOFTMAX=nn.Softmax(dim=0)
+
 num=SOFTMAX(pre.logits[0])
+
 if num[1]>0.5:
     print(str(num[1]))
     print('ポジティブ')
+
 else:
     print(str(num[1]))
     print('ネガティブ')