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nbeerbower/Mistral-Nemo-Gutenberg-Doppel-12B-v2 - GGUF

This repo contains GGUF format model files for nbeerbower/Mistral-Nemo-Gutenberg-Doppel-12B-v2.

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

Prompt template

<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

Model file specification

Filename Quant type File Size Description
Mistral-Nemo-Gutenberg-Doppel-12B-v2-Q2_K.gguf Q2_K 4.791 GB smallest, significant quality loss - not recommended for most purposes
Mistral-Nemo-Gutenberg-Doppel-12B-v2-Q3_K_S.gguf Q3_K_S 5.534 GB very small, high quality loss
Mistral-Nemo-Gutenberg-Doppel-12B-v2-Q3_K_M.gguf Q3_K_M 6.083 GB very small, high quality loss
Mistral-Nemo-Gutenberg-Doppel-12B-v2-Q3_K_L.gguf Q3_K_L 6.562 GB small, substantial quality loss
Mistral-Nemo-Gutenberg-Doppel-12B-v2-Q4_0.gguf Q4_0 7.072 GB legacy; small, very high quality loss - prefer using Q3_K_M
Mistral-Nemo-Gutenberg-Doppel-12B-v2-Q4_K_S.gguf Q4_K_S 7.120 GB small, greater quality loss
Mistral-Nemo-Gutenberg-Doppel-12B-v2-Q4_K_M.gguf Q4_K_M 7.477 GB medium, balanced quality - recommended
Mistral-Nemo-Gutenberg-Doppel-12B-v2-Q5_0.gguf Q5_0 8.519 GB legacy; medium, balanced quality - prefer using Q4_K_M
Mistral-Nemo-Gutenberg-Doppel-12B-v2-Q5_K_S.gguf Q5_K_S 8.519 GB large, low quality loss - recommended
Mistral-Nemo-Gutenberg-Doppel-12B-v2-Q5_K_M.gguf Q5_K_M 8.728 GB large, very low quality loss - recommended
Mistral-Nemo-Gutenberg-Doppel-12B-v2-Q6_K.gguf Q6_K 10.056 GB very large, extremely low quality loss
Mistral-Nemo-Gutenberg-Doppel-12B-v2-Q8_0.gguf Q8_0 13.022 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/Mistral-Nemo-Gutenberg-Doppel-12B-v2-GGUF --include "Mistral-Nemo-Gutenberg-Doppel-12B-v2-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/Mistral-Nemo-Gutenberg-Doppel-12B-v2-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
340
GGUF
Model size
12.2B params
Architecture
llama

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Inference API
Unable to determine this model’s pipeline type. Check the docs .

Model tree for tensorblock/Mistral-Nemo-Gutenberg-Doppel-12B-v2-GGUF

Datasets used to train tensorblock/Mistral-Nemo-Gutenberg-Doppel-12B-v2-GGUF