Create app.py

app.py

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+import gradio as gr
+import torch
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+model_path = "你的模型名稱或資料夾路徑"  # 根據你模型的位置來填
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+model = AutoModelForSequenceClassification.from_pretrained(model_path)
+model.eval()
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model.to(device)
+
+def detect_ai(text):
+    inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True).to(device)
+    with torch.no_grad():
+        outputs = model(**inputs)
+        probs = torch.softmax(outputs.logits, dim=1).squeeze()
+        human_prob = probs[0].item()
+        ai_prob = probs[1].item()
+        label = "AI 生成" if ai_prob > human_prob else "人類撰寫"
+        return f"預測：{label}\nAI 機率：{ai_prob:.2%}\n人類機率：{human_prob:.2%}"
+
+demo = gr.Interface(
+    fn=detect_ai,
+    inputs=gr.Textbox(label="請貼上要分析的文字", lines=10, placeholder="貼上或輸入內容..."),
+    outputs="text",
+    title="AI vs 人類文字偵測器",
+    description="這個工具可以幫助你判斷輸入的文字是 AI 生成還是人類撰寫。",
+)
+
+demo.launch()