README.md

metadata

base_model: google/gemma-2-27b-it
pipeline_tag: text-generation
license: apache-2.0
language:
  - en
tags:
  - gemma
  - gemma-2
  - chat
  - it
  - abliterated
library_name: transformers

gemma-2-27b-it-abliterated

This is a new approach for abliterating models using CPU only. I was able to abliterate this model using free kaggle processing with no accelerator.

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)

Check out the jupyter notebook for details of how this model was abliterated from glm-4-9b-chat.