diff --git a/Testing Abliterated Models Performance and Training Effects.md b/Testing Abliterated Models Performance and Training Effects.md
index 9fb12ee..9d7f1bf 100644
--- a/Testing Abliterated Models Performance and Training Effects.md	
+++ b/Testing Abliterated Models Performance and Training Effects.md	
@@ -1,3 +1,16 @@
+---
+created: '2026-04-05T05:39:22+00:00'
+id: ac34ef61-c715-432a-be39-5e3df4cd701b
+links: []
+modified: '2026-04-05T05:39:22+00:00'
+summary: Abliterated models typically show performance degradation, but fine-tuning
+  after abliteration can recover performance and create uncensored models that rival
+  or outperform originals, as demonstrated by mradermacher/Qwen3-30B-A3B-abliterated-erotic-i1-GGUF
+  and mlabonne/NeuralDaredevil-8B-abliterated.
+tags: []
+title: Testing Abliterated Models Performance and Training Effects
+---
+
 9/26/25
 
 #AI #MachineLearning #ModelTesting #Abliteration #FineTuning #Qwen3 #Llama3 #UncensoredModels