以清洗過的維基百科及維基文庫重新訓練

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d3c1c605200c53792654eec2ac99ec76cac9b2387ef664c3e3e3876981269da5
+oid sha256:6201007c223880c9fbd554bbd26d0249e5bab0ad90e39108d709d312d138fe3a
 size 5515185528

modeling_kuixing.py

@@ -160,7 +160,7 @@ class KuiXingForCausalLM(PreTrainedModel, GenerationMixin):
         # lm_head.weight 是刻意省略的（weight tying），從 missing 中排除再判斷
         missing = [k for k in missing if k != "model.lm_head.weight"]
         if not missing and not unexpected:
-            print("✅ 魁星所有權重 key 完整對映，無缺漏。")
+            print("✅ 所有權重 key 完整對映，無缺漏。")
         else:
             if missing:    print(f"⚠️  缺少 key（{len(missing)}）：{missing[:5]}")
             if unexpected: print(f"⚠️  多餘 key（{len(unexpected)}）：{unexpected[:5]}")

tokenizer.model

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:13698a9916d5f488fcabeec6dc9bd6de65986ae171911ed6c5ab4af43b22c849
-size 1846838
+oid sha256:081434a9b3012410ba5f5987a359a4d3f11242356813164f73eb6c7748781f47
+size 1848887