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kimwooglae/WebSquareAI-Instruct-KoSOLAR-10.7b-v0.5.34 - GGUF

This repo contains GGUF format model files for kimwooglae/WebSquareAI-Instruct-KoSOLAR-10.7b-v0.5.34.

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
WebSquareAI-Instruct-KoSOLAR-10.7b-v0.5.34-Q2_K.gguf Q2_K 4.079 GB smallest, significant quality loss - not recommended for most purposes
WebSquareAI-Instruct-KoSOLAR-10.7b-v0.5.34-Q3_K_S.gguf Q3_K_S 4.747 GB very small, high quality loss
WebSquareAI-Instruct-KoSOLAR-10.7b-v0.5.34-Q3_K_M.gguf Q3_K_M 5.278 GB very small, high quality loss
WebSquareAI-Instruct-KoSOLAR-10.7b-v0.5.34-Q3_K_L.gguf Q3_K_L 5.733 GB small, substantial quality loss
WebSquareAI-Instruct-KoSOLAR-10.7b-v0.5.34-Q4_0.gguf Q4_0 6.163 GB legacy; small, very high quality loss - prefer using Q3_K_M
WebSquareAI-Instruct-KoSOLAR-10.7b-v0.5.34-Q4_K_S.gguf Q4_K_S 6.210 GB small, greater quality loss
WebSquareAI-Instruct-KoSOLAR-10.7b-v0.5.34-Q4_K_M.gguf Q4_K_M 6.553 GB medium, balanced quality - recommended
WebSquareAI-Instruct-KoSOLAR-10.7b-v0.5.34-Q5_0.gguf Q5_0 7.497 GB legacy; medium, balanced quality - prefer using Q4_K_M
WebSquareAI-Instruct-KoSOLAR-10.7b-v0.5.34-Q5_K_S.gguf Q5_K_S 7.497 GB large, low quality loss - recommended
WebSquareAI-Instruct-KoSOLAR-10.7b-v0.5.34-Q5_K_M.gguf Q5_K_M 7.697 GB large, very low quality loss - recommended
WebSquareAI-Instruct-KoSOLAR-10.7b-v0.5.34-Q6_K.gguf Q6_K 8.913 GB very large, extremely low quality loss
WebSquareAI-Instruct-KoSOLAR-10.7b-v0.5.34-Q8_0.gguf Q8_0 11.544 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/WebSquareAI-Instruct-KoSOLAR-10.7b-v0.5.34-GGUF --include "WebSquareAI-Instruct-KoSOLAR-10.7b-v0.5.34-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/WebSquareAI-Instruct-KoSOLAR-10.7b-v0.5.34-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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llama

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