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tensorblock/
p208p2002_llama-chinese-81M-GGUF

Name: p208p2002_llama-chinese-81M-GGUF
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p208p2002/llama-chinese-81M - GGUF

This repo contains GGUF format model files for p208p2002/llama-chinese-81M.

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
llama-chinese-81M-Q2_K.gguf	Q2_K	0.037 GB	smallest, significant quality loss - not recommended for most purposes
llama-chinese-81M-Q3_K_S.gguf	Q3_K_S	0.042 GB	very small, high quality loss
llama-chinese-81M-Q3_K_M.gguf	Q3_K_M	0.045 GB	very small, high quality loss
llama-chinese-81M-Q3_K_L.gguf	Q3_K_L	0.047 GB	small, substantial quality loss
llama-chinese-81M-Q4_0.gguf	Q4_0	0.051 GB	legacy; small, very high quality loss - prefer using Q3_K_M
llama-chinese-81M-Q4_K_S.gguf	Q4_K_S	0.051 GB	small, greater quality loss
llama-chinese-81M-Q4_K_M.gguf	Q4_K_M	0.052 GB	medium, balanced quality - recommended
llama-chinese-81M-Q5_0.gguf	Q5_0	0.059 GB	legacy; medium, balanced quality - prefer using Q4_K_M
llama-chinese-81M-Q5_K_S.gguf	Q5_K_S	0.059 GB	large, low quality loss - recommended
llama-chinese-81M-Q5_K_M.gguf	Q5_K_M	0.060 GB	large, very low quality loss - recommended
llama-chinese-81M-Q6_K.gguf	Q6_K	0.067 GB	very large, extremely low quality loss
llama-chinese-81M-Q8_0.gguf	Q8_0	0.087 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/p208p2002_llama-chinese-81M-GGUF --include "llama-chinese-81M-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/p208p2002_llama-chinese-81M-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'