Update README.md

README.md

@@ -20,6 +20,10 @@ Note that this is fairly experimental, so it might not turn out as well as expec
 
 I recommend using these generation parameters: `temperature=1.0`, `top_k=64`, `top_p=0.95`.
 
+## ⚡️ Quantization
+
+* **GGUF**: https://huggingface.co/mlabonne/gemma-3-12b-it-abliterated-GGUF
+
 ## ✂️ Layerwise abliteration
 
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/gXI5pTMfoX7uPUL-YJBXa.png)
@@ -29,8 +33,4 @@ In the original technique, a refusal direction is computed by comparing the resi
 Here, the model was abliterated by computing a refusal direction based on hidden states (inspired by [Sumandora's repo](https://github.com/Sumandora/remove-refusals-with-transformers/)) for most layers (layer 3 to 45), independently.
 This is combined with a refusal weight of 0.6 to upscale the importance of this refusal direction in each layer.
 
-This created a very high acceptance rate (>90%) and still produced coherent outputs.
-
-## ⚡️ Quantization
-
-* **GGUF**: https://huggingface.co/mlabonne/gemma-3-12b-it-abliterated-GGUF
+This created a very high acceptance rate (>90%) and still produced coherent outputs.