Update README.md

README.md

@@ -12,7 +12,7 @@ library_name: transformers
 This model was abliterated by computing a refusal vector an 8-bit bitsandbytes quant, and then applying the vector to the full weight model.
 Abliteration was performed locally using a CUDA GPU, the VRAM memory consumption appeared to be constrained to be under 12GB.
 
-Layer 18 was selected, as measurements of the refusal direction magnitude, signal-to-noise ratio, and angle between the means of the "harmful" and "harmless" directions suggested that intervention based on this layer would be relatively efficient and effective.
+Layer 18 was selected for derivation of the refusal direction, as measurements of the refusal direction magnitude, signal-to-noise ratio, and angle between the means of the "harmful" and "harmless" directions suggested that intervention based on this layer would be relatively efficient and effective.
 
 No additional fine-tuning was performed on these weights. Repair is required for proper use.