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athirdpath/CleverGirl-20b-Blended - GGUF

This repo contains GGUF format model files for athirdpath/CleverGirl-20b-Blended.

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
CleverGirl-20b-Blended-Q2_K.gguf Q2_K 6.911 GB smallest, significant quality loss - not recommended for most purposes
CleverGirl-20b-Blended-Q3_K_S.gguf Q3_K_S 8.064 GB very small, high quality loss
CleverGirl-20b-Blended-Q3_K_M.gguf Q3_K_M 9.039 GB very small, high quality loss
CleverGirl-20b-Blended-Q3_K_L.gguf Q3_K_L 9.898 GB small, substantial quality loss
CleverGirl-20b-Blended-Q4_0.gguf Q4_0 10.517 GB legacy; small, very high quality loss - prefer using Q3_K_M
CleverGirl-20b-Blended-Q4_K_S.gguf Q4_K_S 10.586 GB small, greater quality loss
CleverGirl-20b-Blended-Q4_K_M.gguf Q4_K_M 11.215 GB medium, balanced quality - recommended
CleverGirl-20b-Blended-Q5_0.gguf Q5_0 12.825 GB legacy; medium, balanced quality - prefer using Q4_K_M
CleverGirl-20b-Blended-Q5_K_S.gguf Q5_K_S 12.825 GB large, low quality loss - recommended
CleverGirl-20b-Blended-Q5_K_M.gguf Q5_K_M 13.185 GB large, very low quality loss - recommended
CleverGirl-20b-Blended-Q6_K.gguf Q6_K 15.278 GB very large, extremely low quality loss
CleverGirl-20b-Blended-Q8_0.gguf Q8_0 19.787 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/CleverGirl-20b-Blended-GGUF --include "CleverGirl-20b-Blended-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/CleverGirl-20b-Blended-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
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GGUF
Model size
20B params
Architecture
llama

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