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DopeorNope/Ko-Mixtral-v1.3-MoE-7Bx2 - GGUF

This repo contains GGUF format model files for DopeorNope/Ko-Mixtral-v1.3-MoE-7Bx2.

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

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Model file specification

Filename Quant type File Size Description
Ko-Mixtral-v1.3-MoE-7Bx2-Q2_K.gguf Q2_K 4.434 GB smallest, significant quality loss - not recommended for most purposes
Ko-Mixtral-v1.3-MoE-7Bx2-Q3_K_S.gguf Q3_K_S 5.204 GB very small, high quality loss
Ko-Mixtral-v1.3-MoE-7Bx2-Q3_K_M.gguf Q3_K_M 5.780 GB very small, high quality loss
Ko-Mixtral-v1.3-MoE-7Bx2-Q3_K_L.gguf Q3_K_L 6.268 GB small, substantial quality loss
Ko-Mixtral-v1.3-MoE-7Bx2-Q4_0.gguf Q4_0 6.781 GB legacy; small, very high quality loss - prefer using Q3_K_M
Ko-Mixtral-v1.3-MoE-7Bx2-Q4_K_S.gguf Q4_K_S 6.837 GB small, greater quality loss
Ko-Mixtral-v1.3-MoE-7Bx2-Q4_K_M.gguf Q4_K_M 7.248 GB medium, balanced quality - recommended
Ko-Mixtral-v1.3-MoE-7Bx2-Q5_0.gguf Q5_0 8.265 GB legacy; medium, balanced quality - prefer using Q4_K_M
Ko-Mixtral-v1.3-MoE-7Bx2-Q5_K_S.gguf Q5_K_S 8.265 GB large, low quality loss - recommended
Ko-Mixtral-v1.3-MoE-7Bx2-Q5_K_M.gguf Q5_K_M 8.506 GB large, very low quality loss - recommended
Ko-Mixtral-v1.3-MoE-7Bx2-Q6_K.gguf Q6_K 9.842 GB very large, extremely low quality loss
Ko-Mixtral-v1.3-MoE-7Bx2-Q8_0.gguf Q8_0 12.746 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/Ko-Mixtral-v1.3-MoE-7Bx2-GGUF --include "Ko-Mixtral-v1.3-MoE-7Bx2-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/Ko-Mixtral-v1.3-MoE-7Bx2-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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GGUF
Model size
12.9B params
Architecture
llama

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