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instructkr/ko-wand-136M - GGUF

This repo contains GGUF format model files for instructkr/ko-wand-136M.

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
ko-wand-136M-Q2_K.gguf Q2_K 0.061 GB smallest, significant quality loss - not recommended for most purposes
ko-wand-136M-Q3_K_S.gguf Q3_K_S 0.069 GB very small, high quality loss
ko-wand-136M-Q3_K_M.gguf Q3_K_M 0.073 GB very small, high quality loss
ko-wand-136M-Q3_K_L.gguf Q3_K_L 0.077 GB small, substantial quality loss
ko-wand-136M-Q4_0.gguf Q4_0 0.084 GB legacy; small, very high quality loss - prefer using Q3_K_M
ko-wand-136M-Q4_K_S.gguf Q4_K_S 0.084 GB small, greater quality loss
ko-wand-136M-Q4_K_M.gguf Q4_K_M 0.087 GB medium, balanced quality - recommended
ko-wand-136M-Q5_0.gguf Q5_0 0.098 GB legacy; medium, balanced quality - prefer using Q4_K_M
ko-wand-136M-Q5_K_S.gguf Q5_K_S 0.098 GB large, low quality loss - recommended
ko-wand-136M-Q5_K_M.gguf Q5_K_M 0.100 GB large, very low quality loss - recommended
ko-wand-136M-Q6_K.gguf Q6_K 0.113 GB very large, extremely low quality loss
ko-wand-136M-Q8_0.gguf Q8_0 0.146 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-wand-136M-GGUF --include "ko-wand-136M-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-wand-136M-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
3
GGUF
Model size
136M params
Architecture
llama

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5-bit

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Inference Providers NEW
This model is not currently available via any of the supported third-party Inference Providers, and HF Inference API was unable to determine this model's library.

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