tensorblock/kullama2-7b-ko-PGO-GGUF

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devhyun88/kullama2-7b-ko-PGO - GGUF

This repo contains GGUF format model files for devhyun88/kullama2-7b-ko-PGO.

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

Filename	Quant type	File Size	Description
kullama2-7b-ko-PGO-Q2_K.gguf	Q2_K	2.422 GB	smallest, significant quality loss - not recommended for most purposes
kullama2-7b-ko-PGO-Q3_K_S.gguf	Q3_K_S	2.815 GB	very small, high quality loss
kullama2-7b-ko-PGO-Q3_K_M.gguf	Q3_K_M	3.140 GB	very small, high quality loss
kullama2-7b-ko-PGO-Q3_K_L.gguf	Q3_K_L	3.419 GB	small, substantial quality loss
kullama2-7b-ko-PGO-Q4_0.gguf	Q4_0	3.639 GB	legacy; small, very high quality loss - prefer using Q3_K_M
kullama2-7b-ko-PGO-Q4_K_S.gguf	Q4_K_S	3.668 GB	small, greater quality loss
kullama2-7b-ko-PGO-Q4_K_M.gguf	Q4_K_M	3.877 GB	medium, balanced quality - recommended
kullama2-7b-ko-PGO-Q5_0.gguf	Q5_0	4.415 GB	legacy; medium, balanced quality - prefer using Q4_K_M
kullama2-7b-ko-PGO-Q5_K_S.gguf	Q5_K_S	4.415 GB	large, low quality loss - recommended
kullama2-7b-ko-PGO-Q5_K_M.gguf	Q5_K_M	4.537 GB	large, very low quality loss - recommended
kullama2-7b-ko-PGO-Q6_K.gguf	Q6_K	5.240 GB	very large, extremely low quality loss
kullama2-7b-ko-PGO-Q8_0.gguf	Q8_0	6.786 GB	very large, extremely low quality loss - not recommended

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

huggingface-cli download tensorblock/kullama2-7b-ko-PGO-GGUF --include "kullama2-7b-ko-PGO-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/kullama2-7b-ko-PGO-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'