Update README.md

README.md

@@ -14,20 +14,13 @@ library_name: transformers
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-NOTE: This is a current WIP (work in progress).
 
-Abliteration method:
-
-1. Obtain refusal direction with llama-cpp-python.
-2. Orthogonalization performed with torch directly to .safetensors. (one at a time)
-
-It is a rather larger model so it may take me another day or two to figure out which layer I should be using for the direction vector.
-
-First attempt: Layer 20 was used to obtain refusal direction vector. Refusal mitigation sort of worked but not perfect.
+# gemma-2-27b-it-abliterated
 
-Second attempt: (Current) Layer 23 was used (mid-point of model). Half-way has proven to work with other model so this should be fine.
+This is a novel approach to abliterating a model on CPU only. 
+1. Obtain refusal direction vector using a quant model with llama.cpp (llama-cpp-python and ggml-python).
+2. Orthogonalize each .safetensors files directly from original repo and upload to a new repo. (one at a time)
 
-# gemma-2-27b-it-abliterated
 Check out the <a href="https://huggingface.co/byroneverson/gemma-2-27b-it-abliterated/blob/main/abliterate-gemma-2-27b-it.ipynb">jupyter notebook</a> for details of how this model was abliterated from glm-4-9b-chat.
 
 ![Logo](https://huggingface.co/byroneverson/gemma-2-27b-it-abliterated/resolve/main/logo.png "Logo")