diff --git a/examples/MEXICO_predict_example.ipynb b/examples/MEXICO_predict_example.ipynb
index 4e461654..41e679e8 100644
--- a/examples/MEXICO_predict_example.ipynb
+++ b/examples/MEXICO_predict_example.ipynb
@@ -229,7 +229,7 @@
    "source": [
     "df[df['prediction_is_key_smash'] == 1][[concatened_column_name, 'prediction_is_key_smash']] \\\n",
     "    .drop_duplicates(subset=[concatened_column_name]) \\\n",
-    "    .to_csv(f'../data/tmp/prediction_rf_ks_regex_enrich_normal.csv')"
+    "    .to_csv(f'../data/tmp/prediction_rf_ks_we_regex_enrich_normal.csv')"
    ]
   }
  ],
diff --git a/examples/MEXICO_predict_example_no_embeddings copy.ipynb b/examples/MEXICO_predict_example_no_embeddings.ipynb
similarity index 98%
rename from examples/MEXICO_predict_example_no_embeddings copy.ipynb
rename to examples/MEXICO_predict_example_no_embeddings.ipynb
index 9c873d4e..8efd35ed 100644
--- a/examples/MEXICO_predict_example_no_embeddings copy.ipynb	
+++ b/examples/MEXICO_predict_example_no_embeddings.ipynb
@@ -206,7 +206,7 @@
    "source": [
     "df[df['prediction_is_key_smash'] == 1][[concatened_column_name, 'prediction_is_key_smash']] \\\n",
     "    .drop_duplicates(subset=[concatened_column_name]) \\\n",
-    "    .to_csv(f'../data/tmp/prediction_rf_ks_we_regex_enrich_normal.csv')"
+    "    .to_csv(f'../data/tmp/prediction_rf_ks_regex_enrich_normal.csv')"
    ]
   }
  ],