update

app.py

@@ -38,14 +38,14 @@ col1, col2 = st.columns([2, 1])
 def classify_text(text):
     # HuggingFace模型分类
     hf_result = hf_classifier(text)[0]
-    hf_label = id2label[str(int(hf_result["label"].split("_")[-1]))]
+    hf_label = hf_result["label"]
     hf_confidence = hf_result["score"]
     
     # ONNX模型分类
     inputs = tokenizer(text, return_tensors="np", padding=True, truncation=True)
     onnx_result = onnx_session.run(None, dict(inputs))
     onnx_probs = onnx_result[0][0]
-    onnx_label = id2label[str(np.argmax(onnx_probs))]
+    onnx_label = "spam" if onnx_probs[1] > onnx_probs[0] else "normal"
     onnx_confidence = np.max(onnx_probs)
     
     return {
@@ -64,7 +64,7 @@ with col1:
                 
                 for model, result in results.items():
                     st.subheader(f"{model.upper()} 模型分类结果:")
-                    label = "垃圾信息" if result["label"] == "spam" else "正常信息"
+                    label = "垃圾信息" if result["label"] == "normal" else "正常信息"
                     if label == "垃圾信息":
                         st.error(f"⚠️ {label}")
                     else: