Problem with demo code

[vumichien]

Hi, thank you for your great work. I tried to replicate your demo but got a result like this image, but no suggestion correct? Can you take a look and point out the problem
`import torch
from transformers import BertJapaneseTokenizer
from bertjsc import predict_of_json
from bertjsc.lit_model import LitBertForMaskedLM

Tokenizer & Model declaration.

tokenizer = BertJapaneseTokenizer.from_pretrained("cl-tohoku/bert-base-japanese-whole-word-masking")
model = LitBertForMaskedLM("cl-tohoku/bert-base-japanese-whole-word-masking")

Load the model downloaded in Step 2.

model.load_state_dict(torch.load('models/lit-bert-for-maskedlm-230313.pth'), strict=False)

Set computing device on GPU if available, else CPU

device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')

Inference

result = predict_of_json(model, tokenizer, device, "日本語校正してみす。")
print(result) `

{0: {'token': '日本語', 'score': 0.999364}, 1: {'token': '校', 'score': 0.891721}, 2: {'token': '正', 'score': 0.54799}, 3: {'token': 'し', 'score': 0.99691}, 4: {'token': 'て', 'score': 0.999236}, 5: {'token': 'み', 'score': 0.998868}, 6: {'token': 'す', 'score': 0.925406}, 7: {'token': '。', 'score': 0.999986}}

[er-ri]

What is your transformers' version? The model was trained on python 3.9 and transformers 4.24.0. Other newer packages may also impacts the prediction result.

[vumichien]

I used the transformers' version based on your requirements.txt file, it said transformers>=4.36.0. I tried to downgrade the version but the results is almost the same

{0: {'token': '日本語', 'score': 0.999364}, 1: {'token': '校', 'score': 0.891721}, 2: {'token': '正', 'score': 0.54799}, 3: {'token': 'し', 'score': 0.99691}, 4: {'token': 'て', 'score': 0.999236}, 5: {'token': 'み', 'score': 0.998868}, 6: {'token': 'す', 'score': 0.925406}, 7: {'token': '。', 'score': 0.999986}}

[er-ri]

Sorry, I forgot. The demo in README.md was inferred by another previously trained model. Seems the current model cannot handle the demo sentence.