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MarinaraSpaghetti/NemoMix-Unleashed-12B - GGUF

This repo contains GGUF format model files for MarinaraSpaghetti/NemoMix-Unleashed-12B.

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
NemoMix-Unleashed-12B-Q2_K.gguf Q2_K 4.462 GB smallest, significant quality loss - not recommended for most purposes
NemoMix-Unleashed-12B-Q3_K_S.gguf Q3_K_S 5.154 GB very small, high quality loss
NemoMix-Unleashed-12B-Q3_K_M.gguf Q3_K_M 5.665 GB very small, high quality loss
NemoMix-Unleashed-12B-Q3_K_L.gguf Q3_K_L 6.111 GB small, substantial quality loss
NemoMix-Unleashed-12B-Q4_0.gguf Q4_0 6.586 GB legacy; small, very high quality loss - prefer using Q3_K_M
NemoMix-Unleashed-12B-Q4_K_S.gguf Q4_K_S 6.631 GB small, greater quality loss
NemoMix-Unleashed-12B-Q4_K_M.gguf Q4_K_M 6.964 GB medium, balanced quality - recommended
NemoMix-Unleashed-12B-Q5_0.gguf Q5_0 7.934 GB legacy; medium, balanced quality - prefer using Q4_K_M
NemoMix-Unleashed-12B-Q5_K_S.gguf Q5_K_S 7.934 GB large, low quality loss - recommended
NemoMix-Unleashed-12B-Q5_K_M.gguf Q5_K_M 8.128 GB large, very low quality loss - recommended
NemoMix-Unleashed-12B-Q6_K.gguf Q6_K 9.366 GB very large, extremely low quality loss
NemoMix-Unleashed-12B-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/NemoMix-Unleashed-12B-GGUF --include "NemoMix-Unleashed-12B-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/NemoMix-Unleashed-12B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
173
GGUF
Model size
12.2B params
Architecture
llama

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Inference API
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