| import torch | |
| from transformers import MLukeTokenizer | |
| from torch import nn | |
| tokenizer = MLukeTokenizer.from_pretrained('studio-ousia/luke-japanese-base-lite') | |
| model = torch.load('C:\\[modelのあるディレクトリ]\\My_luke_model_pn.pth') | |
| text=input() | |
| encoded_dict = tokenizer.encode_plus( | |
| text, | |
| return_attention_mask = True, # Attention maksの作成 | |
| return_tensors = 'pt', # Pytorch tensorsで返す | |
| ) | |
| 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') |