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---
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 <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.
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