p208p2002's picture
Update app.py
5cda48b
raw
history blame
752 Bytes
import gradio as gr
from transformers import BertTokenizerFast, BertForSequenceClassification
import torch
model = BertForSequenceClassification.from_pretrained('./ch-sent-check-model')
tokenizer = BertTokenizerFast.from_pretrained('./ch-sent-check-model')
def judge(sentence):
input_ids = tokenizer(sentence,return_tensors='pt')['input_ids']
out = model(input_ids)
logits = out.logits
pred = torch.argmax(logits,dim=-1).item()
pred_text = 'Incorrect' if pred == 0 else 'Correct'
return pred_text
iface = gr.Interface(
fn=judge,
inputs=gr.Textbox(
label="請輸入一段中文句子來檢測正確性",
lines=1,
value="請注意用字的鄭確性",
),
outputs="text"
)
iface.launch()