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SauerkrautLM-Gemma-7b-GGUF

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metadata
license: other
license_name: gemma-terms-of-use
license_link: https://ai.google.dev/gemma/terms
language:
  - de
  - en
tags:
  - sft
  - dpo
  - laserRMT
  - laser-QLoRa
  - finetune
  - work in progress
  - alpha
  - TensorBlock
  - GGUF
base_model: VAGOsolutions/SauerkrautLM-Gemma-7b
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VAGOsolutions/SauerkrautLM-Gemma-7b - GGUF

This repo contains GGUF format model files for VAGOsolutions/SauerkrautLM-Gemma-7b.

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

Prompt template

Model file specification

Filename Quant type File Size Description
SauerkrautLM-Gemma-7b-Q2_K.gguf Q2_K 3.242 GB smallest, significant quality loss - not recommended for most purposes
SauerkrautLM-Gemma-7b-Q3_K_S.gguf Q3_K_S 3.709 GB very small, high quality loss
SauerkrautLM-Gemma-7b-Q3_K_M.gguf Q3_K_M 4.069 GB very small, high quality loss
SauerkrautLM-Gemma-7b-Q3_K_L.gguf Q3_K_L 4.386 GB small, substantial quality loss
SauerkrautLM-Gemma-7b-Q4_0.gguf Q4_0 4.668 GB legacy; small, very high quality loss - prefer using Q3_K_M
SauerkrautLM-Gemma-7b-Q4_K_S.gguf Q4_K_S 4.700 GB small, greater quality loss
SauerkrautLM-Gemma-7b-Q4_K_M.gguf Q4_K_M 4.964 GB medium, balanced quality - recommended
SauerkrautLM-Gemma-7b-Q5_0.gguf Q5_0 5.570 GB legacy; medium, balanced quality - prefer using Q4_K_M
SauerkrautLM-Gemma-7b-Q5_K_S.gguf Q5_K_S 5.570 GB large, low quality loss - recommended
SauerkrautLM-Gemma-7b-Q5_K_M.gguf Q5_K_M 5.723 GB large, very low quality loss - recommended
SauerkrautLM-Gemma-7b-Q6_K.gguf Q6_K 6.529 GB very large, extremely low quality loss
SauerkrautLM-Gemma-7b-Q8_0.gguf Q8_0 8.454 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/SauerkrautLM-Gemma-7b-GGUF --include "SauerkrautLM-Gemma-7b-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/SauerkrautLM-Gemma-7b-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'