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gemma-2-27b-it-abliterated-GGUF

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metadata
base_model: byroneverson/gemma-2-27b-it-abliterated
pipeline_tag: text-generation
license: gemma
language:
  - en
tags:
  - gemma
  - gemma-2
  - chat
  - it
  - abliterated
  - TensorBlock
  - GGUF
library_name: transformers
TensorBlock

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byroneverson/gemma-2-27b-it-abliterated - GGUF

This repo contains GGUF format model files for byroneverson/gemma-2-27b-it-abliterated.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.

Prompt template 

<bos><start_of_turn>user
{prompt}<end_of_turn>
<start_of_turn>model

Model file specification

Filename Quant type File Size Description
gemma-2-27b-it-abliterated-Q2_K.gguf Q2_K 9.732 GB smallest, significant quality loss - not recommended for most purposes
gemma-2-27b-it-abliterated-Q3_K_S.gguf Q3_K_S 11.333 GB very small, high quality loss
gemma-2-27b-it-abliterated-Q3_K_M.gguf Q3_K_M 12.503 GB very small, high quality loss
gemma-2-27b-it-abliterated-Q3_K_L.gguf Q3_K_L 13.522 GB small, substantial quality loss
gemma-2-27b-it-abliterated-Q4_0.gguf Q4_0 14.555 GB legacy; small, very high quality loss - prefer using Q3_K_M
gemma-2-27b-it-abliterated-Q4_K_S.gguf Q4_K_S 14.658 GB small, greater quality loss
gemma-2-27b-it-abliterated-Q4_K_M.gguf Q4_K_M 15.502 GB medium, balanced quality - recommended
gemma-2-27b-it-abliterated-Q5_0.gguf Q5_0 17.587 GB legacy; medium, balanced quality - prefer using Q4_K_M
gemma-2-27b-it-abliterated-Q5_K_S.gguf Q5_K_S 17.587 GB large, low quality loss - recommended
gemma-2-27b-it-abliterated-Q5_K_M.gguf Q5_K_M 18.075 GB large, very low quality loss - recommended
gemma-2-27b-it-abliterated-Q6_K.gguf Q6_K 20.809 GB very large, extremely low quality loss
gemma-2-27b-it-abliterated-Q8_0.gguf Q8_0 26.950 GB very large, extremely low quality loss - not recommended

Downloading instruction

Command line

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

huggingface-cli download tensorblock/gemma-2-27b-it-abliterated-GGUF --include "gemma-2-27b-it-abliterated-Q2_K.gguf" --local-dir MY_LOCAL_DIR

If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:

huggingface-cli download tensorblock/gemma-2-27b-it-abliterated-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'