tensorblock/LDCC_LoRA_full-GGUF

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cong1230/LDCC_LoRA_full - GGUF

This repo contains GGUF format model files for cong1230/LDCC_LoRA_full.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.

Filename	Quant type	File Size	Description
LDCC_LoRA_full-Q2_K.gguf	Q2_K	4.939 GB	smallest, significant quality loss - not recommended for most purposes
LDCC_LoRA_full-Q3_K_S.gguf	Q3_K_S	5.751 GB	very small, high quality loss
LDCC_LoRA_full-Q3_K_M.gguf	Q3_K_M	6.430 GB	very small, high quality loss
LDCC_LoRA_full-Q3_K_L.gguf	Q3_K_L	7.022 GB	small, substantial quality loss
LDCC_LoRA_full-Q4_0.gguf	Q4_0	7.468 GB	legacy; small, very high quality loss - prefer using Q3_K_M
LDCC_LoRA_full-Q4_K_S.gguf	Q4_K_S	7.525 GB	small, greater quality loss
LDCC_LoRA_full-Q4_K_M.gguf	Q4_K_M	7.968 GB	medium, balanced quality - recommended
LDCC_LoRA_full-Q5_0.gguf	Q5_0	9.083 GB	legacy; medium, balanced quality - prefer using Q4_K_M
LDCC_LoRA_full-Q5_K_S.gguf	Q5_K_S	9.083 GB	large, low quality loss - recommended
LDCC_LoRA_full-Q5_K_M.gguf	Q5_K_M	9.341 GB	large, very low quality loss - recommended
LDCC_LoRA_full-Q6_K.gguf	Q6_K	10.800 GB	very large, extremely low quality loss
LDCC_LoRA_full-Q8_0.gguf	Q8_0	13.988 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/LDCC_LoRA_full-GGUF --include "LDCC_LoRA_full-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/LDCC_LoRA_full-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'