tensorblock/SauerkrautLM-Nemo-12b-Instruct-GGUF

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VAGOsolutions/SauerkrautLM-Nemo-12b-Instruct - GGUF

This repo contains GGUF format model files for VAGOsolutions/SauerkrautLM-Nemo-12b-Instruct.

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

Prompt template

<s>[INST] {system_prompt}

{prompt}[/INST]

Model file specification

Filename	Quant type	File Size	Description
SauerkrautLM-Nemo-12b-Instruct-Q2_K.gguf	Q2_K	4.462 GB	smallest, significant quality loss - not recommended for most purposes
SauerkrautLM-Nemo-12b-Instruct-Q3_K_S.gguf	Q3_K_S	5.154 GB	very small, high quality loss
SauerkrautLM-Nemo-12b-Instruct-Q3_K_M.gguf	Q3_K_M	5.665 GB	very small, high quality loss
SauerkrautLM-Nemo-12b-Instruct-Q3_K_L.gguf	Q3_K_L	6.111 GB	small, substantial quality loss
SauerkrautLM-Nemo-12b-Instruct-Q4_0.gguf	Q4_0	6.586 GB	legacy; small, very high quality loss - prefer using Q3_K_M
SauerkrautLM-Nemo-12b-Instruct-Q4_K_S.gguf	Q4_K_S	6.631 GB	small, greater quality loss
SauerkrautLM-Nemo-12b-Instruct-Q4_K_M.gguf	Q4_K_M	6.964 GB	medium, balanced quality - recommended
SauerkrautLM-Nemo-12b-Instruct-Q5_0.gguf	Q5_0	7.934 GB	legacy; medium, balanced quality - prefer using Q4_K_M
SauerkrautLM-Nemo-12b-Instruct-Q5_K_S.gguf	Q5_K_S	7.934 GB	large, low quality loss - recommended
SauerkrautLM-Nemo-12b-Instruct-Q5_K_M.gguf	Q5_K_M	8.128 GB	large, very low quality loss - recommended
SauerkrautLM-Nemo-12b-Instruct-Q6_K.gguf	Q6_K	9.366 GB	very large, extremely low quality loss
SauerkrautLM-Nemo-12b-Instruct-Q8_0.gguf	Q8_0	12.128 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-Nemo-12b-Instruct-GGUF --include "SauerkrautLM-Nemo-12b-Instruct-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-Nemo-12b-Instruct-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'