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README.md

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+Quantization made by Richard Erkhov.
+
+[Github](https://github.com/RichardErkhov)
+
+[Discord](https://discord.gg/pvy7H8DZMG)
+
+[Request more models](https://github.com/RichardErkhov/quant_request)
+
+
+gemma-2-27b-it-abliterated - GGUF
+- Model creator: https://huggingface.co/byroneverson/
+- Original model: https://huggingface.co/byroneverson/gemma-2-27b-it-abliterated/
+
+
+| Name | Quant method | Size |
+| ---- | ---- | ---- |
+| [gemma-2-27b-it-abliterated.Q2_K.gguf](https://huggingface.co/RichardErkhov/byroneverson_-_gemma-2-27b-it-abliterated-gguf/blob/main/gemma-2-27b-it-abliterated.Q2_K.gguf) | Q2_K | 9.73GB |
+| [gemma-2-27b-it-abliterated.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/byroneverson_-_gemma-2-27b-it-abliterated-gguf/blob/main/gemma-2-27b-it-abliterated.IQ3_XS.gguf) | IQ3_XS | 10.76GB |
+| [gemma-2-27b-it-abliterated.IQ3_S.gguf](https://huggingface.co/RichardErkhov/byroneverson_-_gemma-2-27b-it-abliterated-gguf/blob/main/gemma-2-27b-it-abliterated.IQ3_S.gguf) | IQ3_S | 11.33GB |
+| [gemma-2-27b-it-abliterated.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/byroneverson_-_gemma-2-27b-it-abliterated-gguf/blob/main/gemma-2-27b-it-abliterated.Q3_K_S.gguf) | Q3_K_S | 11.33GB |
+| [gemma-2-27b-it-abliterated.IQ3_M.gguf](https://huggingface.co/RichardErkhov/byroneverson_-_gemma-2-27b-it-abliterated-gguf/blob/main/gemma-2-27b-it-abliterated.IQ3_M.gguf) | IQ3_M | 11.6GB |
+| [gemma-2-27b-it-abliterated.Q3_K.gguf](https://huggingface.co/RichardErkhov/byroneverson_-_gemma-2-27b-it-abliterated-gguf/blob/main/gemma-2-27b-it-abliterated.Q3_K.gguf) | Q3_K | 12.5GB |
+| [gemma-2-27b-it-abliterated.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/byroneverson_-_gemma-2-27b-it-abliterated-gguf/blob/main/gemma-2-27b-it-abliterated.Q3_K_M.gguf) | Q3_K_M | 12.5GB |
+| [gemma-2-27b-it-abliterated.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/byroneverson_-_gemma-2-27b-it-abliterated-gguf/blob/main/gemma-2-27b-it-abliterated.Q3_K_L.gguf) | Q3_K_L | 13.52GB |
+| [gemma-2-27b-it-abliterated.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/byroneverson_-_gemma-2-27b-it-abliterated-gguf/blob/main/gemma-2-27b-it-abliterated.IQ4_XS.gguf) | IQ4_XS | 13.92GB |
+| [gemma-2-27b-it-abliterated.Q4_0.gguf](https://huggingface.co/RichardErkhov/byroneverson_-_gemma-2-27b-it-abliterated-gguf/blob/main/gemma-2-27b-it-abliterated.Q4_0.gguf) | Q4_0 | 14.56GB |
+| [gemma-2-27b-it-abliterated.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/byroneverson_-_gemma-2-27b-it-abliterated-gguf/blob/main/gemma-2-27b-it-abliterated.IQ4_NL.gguf) | IQ4_NL | 14.65GB |
+| [gemma-2-27b-it-abliterated.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/byroneverson_-_gemma-2-27b-it-abliterated-gguf/blob/main/gemma-2-27b-it-abliterated.Q4_K_S.gguf) | Q4_K_S | 14.66GB |
+| [gemma-2-27b-it-abliterated.Q4_K.gguf](https://huggingface.co/RichardErkhov/byroneverson_-_gemma-2-27b-it-abliterated-gguf/blob/main/gemma-2-27b-it-abliterated.Q4_K.gguf) | Q4_K | 15.5GB |
+| [gemma-2-27b-it-abliterated.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/byroneverson_-_gemma-2-27b-it-abliterated-gguf/blob/main/gemma-2-27b-it-abliterated.Q4_K_M.gguf) | Q4_K_M | 15.5GB |
+| [gemma-2-27b-it-abliterated.Q4_1.gguf](https://huggingface.co/RichardErkhov/byroneverson_-_gemma-2-27b-it-abliterated-gguf/blob/main/gemma-2-27b-it-abliterated.Q4_1.gguf) | Q4_1 | 16.07GB |
+| [gemma-2-27b-it-abliterated.Q5_0.gguf](https://huggingface.co/RichardErkhov/byroneverson_-_gemma-2-27b-it-abliterated-gguf/blob/main/gemma-2-27b-it-abliterated.Q5_0.gguf) | Q5_0 | 17.59GB |
+| [gemma-2-27b-it-abliterated.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/byroneverson_-_gemma-2-27b-it-abliterated-gguf/blob/main/gemma-2-27b-it-abliterated.Q5_K_S.gguf) | Q5_K_S | 17.59GB |
+| [gemma-2-27b-it-abliterated.Q5_K.gguf](https://huggingface.co/RichardErkhov/byroneverson_-_gemma-2-27b-it-abliterated-gguf/blob/main/gemma-2-27b-it-abliterated.Q5_K.gguf) | Q5_K | 18.08GB |
+| [gemma-2-27b-it-abliterated.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/byroneverson_-_gemma-2-27b-it-abliterated-gguf/blob/main/gemma-2-27b-it-abliterated.Q5_K_M.gguf) | Q5_K_M | 18.08GB |
+| [gemma-2-27b-it-abliterated.Q5_1.gguf](https://huggingface.co/RichardErkhov/byroneverson_-_gemma-2-27b-it-abliterated-gguf/blob/main/gemma-2-27b-it-abliterated.Q5_1.gguf) | Q5_1 | 19.1GB |
+| [gemma-2-27b-it-abliterated.Q6_K.gguf](https://huggingface.co/RichardErkhov/byroneverson_-_gemma-2-27b-it-abliterated-gguf/blob/main/gemma-2-27b-it-abliterated.Q6_K.gguf) | Q6_K | 20.81GB |
+| [gemma-2-27b-it-abliterated.Q8_0.gguf](https://huggingface.co/RichardErkhov/byroneverson_-_gemma-2-27b-it-abliterated-gguf/blob/main/gemma-2-27b-it-abliterated.Q8_0.gguf) | Q8_0 | 26.95GB |
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+
+
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+Original model description:
+---
+base_model: google/gemma-2-27b-it
+pipeline_tag: text-generation
+license: gemma
+language:
+- en
+tags:
+- gemma
+- gemma-2
+- chat
+- it
+- abliterated
+library_name: transformers
+---
+
+
+
+# gemma-2-27b-it-abliterated
+
+## Now accepting abliteration requests. If you would like to see a model abliterated, follow me and leave me a message with model link.
+
+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 gemma-2-27b-it.
+
+![Logo](https://huggingface.co/byroneverson/gemma-2-27b-it-abliterated/resolve/main/logo.png "Logo")
+