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tensorblock/
fiveflow_kolong-llama-v0.1-GGUF

Name: fiveflow_kolong-llama-v0.1-GGUF
Availability: InStock

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fiveflow/kolong-llama-v0.1 - GGUF

This repo contains GGUF format model files for fiveflow/kolong-llama-v0.1.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b5165.

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Filename	Quant type	File Size	Description
kolong-llama-v0.1-Q2_K.gguf	Q2_K	2.601 GB	smallest, significant quality loss - not recommended for most purposes
kolong-llama-v0.1-Q3_K_S.gguf	Q3_K_S	3.022 GB	very small, high quality loss
kolong-llama-v0.1-Q3_K_M.gguf	Q3_K_M	3.372 GB	very small, high quality loss
kolong-llama-v0.1-Q3_K_L.gguf	Q3_K_L	3.671 GB	small, substantial quality loss
kolong-llama-v0.1-Q4_0.gguf	Q4_0	3.907 GB	legacy; small, very high quality loss - prefer using Q3_K_M
kolong-llama-v0.1-Q4_K_S.gguf	Q4_K_S	3.938 GB	small, greater quality loss
kolong-llama-v0.1-Q4_K_M.gguf	Q4_K_M	4.163 GB	medium, balanced quality - recommended
kolong-llama-v0.1-Q5_0.gguf	Q5_0	4.741 GB	legacy; medium, balanced quality - prefer using Q4_K_M
kolong-llama-v0.1-Q5_K_S.gguf	Q5_K_S	4.741 GB	large, low quality loss - recommended
kolong-llama-v0.1-Q5_K_M.gguf	Q5_K_M	4.872 GB	large, very low quality loss - recommended
kolong-llama-v0.1-Q6_K.gguf	Q6_K	5.626 GB	very large, extremely low quality loss
kolong-llama-v0.1-Q8_0.gguf	Q8_0	7.286 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/fiveflow_kolong-llama-v0.1-GGUF --include "kolong-llama-v0.1-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/fiveflow_kolong-llama-v0.1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'