wangleon/line-scam-detector

1import gradio as gr2from transformers import BertTokenizer, BertForSequenceClassification3import torch4 5# 載入 tokenizer 和模型6tokenizer = BertTokenizer.from_pretrained("ckiplab/bert-base-chinese")7model = BertForSequenceClassification.from_pretrained("ckiplab/bert-base-chinese", num_labels=2)8model.eval()9 10# 預測函式11def predict(text):12    inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)13    with torch.no_grad():14        outputs = model(**inputs)15        logits = outputs.logits16        prediction = torch.argmax(logits, dim=1).item()17        return "詐騙訊息" if prediction == 1 else "正常訊息"18 19# Gradio UI20iface = gr.Interface(fn=predict, inputs="text", outputs="text", title="Line詐騙訊息辨識器")21iface.launch()22