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AIdenU/LLAMA-2-13b-ko-Y24-DPO_v2.0 - GGUF

This repo contains GGUF format model files for AIdenU/LLAMA-2-13b-ko-Y24-DPO_v2.0.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.

Prompt template


Model file specification

Filename Quant type File Size Description
LLAMA-2-13b-ko-Y24-DPO_v2.0-Q2_K.gguf Q2_K 4.854 GB smallest, significant quality loss - not recommended for most purposes
LLAMA-2-13b-ko-Y24-DPO_v2.0-Q3_K_S.gguf Q3_K_S 5.659 GB very small, high quality loss
LLAMA-2-13b-ko-Y24-DPO_v2.0-Q3_K_M.gguf Q3_K_M 6.338 GB very small, high quality loss
LLAMA-2-13b-ko-Y24-DPO_v2.0-Q3_K_L.gguf Q3_K_L 6.930 GB small, substantial quality loss
LLAMA-2-13b-ko-Y24-DPO_v2.0-Q4_0.gguf Q4_0 7.366 GB legacy; small, very high quality loss - prefer using Q3_K_M
LLAMA-2-13b-ko-Y24-DPO_v2.0-Q4_K_S.gguf Q4_K_S 7.423 GB small, greater quality loss
LLAMA-2-13b-ko-Y24-DPO_v2.0-Q4_K_M.gguf Q4_K_M 7.866 GB medium, balanced quality - recommended
LLAMA-2-13b-ko-Y24-DPO_v2.0-Q5_0.gguf Q5_0 8.972 GB legacy; medium, balanced quality - prefer using Q4_K_M
LLAMA-2-13b-ko-Y24-DPO_v2.0-Q5_K_S.gguf Q5_K_S 8.972 GB large, low quality loss - recommended
LLAMA-2-13b-ko-Y24-DPO_v2.0-Q5_K_M.gguf Q5_K_M 9.230 GB large, very low quality loss - recommended
LLAMA-2-13b-ko-Y24-DPO_v2.0-Q6_K.gguf Q6_K 10.679 GB very large, extremely low quality loss
LLAMA-2-13b-ko-Y24-DPO_v2.0-Q8_0.gguf Q8_0 13.831 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/LLAMA-2-13b-ko-Y24-DPO_v2.0-GGUF --include "LLAMA-2-13b-ko-Y24-DPO_v2.0-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/LLAMA-2-13b-ko-Y24-DPO_v2.0-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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llama

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Inference Examples
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