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KISTI-KONI/KONI-Llama3-8B-20240630 - GGUF

This repo contains GGUF format model files for KISTI-KONI/KONI-Llama3-8B-20240630.

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
KONI-Llama3-8B-20240630-Q2_K.gguf Q2_K 3.179 GB smallest, significant quality loss - not recommended for most purposes
KONI-Llama3-8B-20240630-Q3_K_S.gguf Q3_K_S 3.664 GB very small, high quality loss
KONI-Llama3-8B-20240630-Q3_K_M.gguf Q3_K_M 4.019 GB very small, high quality loss
KONI-Llama3-8B-20240630-Q3_K_L.gguf Q3_K_L 4.322 GB small, substantial quality loss
KONI-Llama3-8B-20240630-Q4_0.gguf Q4_0 4.661 GB legacy; small, very high quality loss - prefer using Q3_K_M
KONI-Llama3-8B-20240630-Q4_K_S.gguf Q4_K_S 4.693 GB small, greater quality loss
KONI-Llama3-8B-20240630-Q4_K_M.gguf Q4_K_M 4.921 GB medium, balanced quality - recommended
KONI-Llama3-8B-20240630-Q5_0.gguf Q5_0 5.599 GB legacy; medium, balanced quality - prefer using Q4_K_M
KONI-Llama3-8B-20240630-Q5_K_S.gguf Q5_K_S 5.599 GB large, low quality loss - recommended
KONI-Llama3-8B-20240630-Q5_K_M.gguf Q5_K_M 5.733 GB large, very low quality loss - recommended
KONI-Llama3-8B-20240630-Q6_K.gguf Q6_K 6.596 GB very large, extremely low quality loss
KONI-Llama3-8B-20240630-Q8_0.gguf Q8_0 8.541 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/KONI-Llama3-8B-20240630-GGUF --include "KONI-Llama3-8B-20240630-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/KONI-Llama3-8B-20240630-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
17
GGUF
Model size
8.03B params
Architecture
llama

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Inference Examples
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