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yunconglong/MoE_13B_DPO - GGUF

This repo contains GGUF format model files for yunconglong/MoE_13B_DPO.

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
MoE_13B_DPO-Q2_K.gguf Q2_K 4.434 GB smallest, significant quality loss - not recommended for most purposes
MoE_13B_DPO-Q3_K_S.gguf Q3_K_S 5.204 GB very small, high quality loss
MoE_13B_DPO-Q3_K_M.gguf Q3_K_M 5.780 GB very small, high quality loss
MoE_13B_DPO-Q3_K_L.gguf Q3_K_L 6.268 GB small, substantial quality loss
MoE_13B_DPO-Q4_0.gguf Q4_0 6.781 GB legacy; small, very high quality loss - prefer using Q3_K_M
MoE_13B_DPO-Q4_K_S.gguf Q4_K_S 6.837 GB small, greater quality loss
MoE_13B_DPO-Q4_K_M.gguf Q4_K_M 7.248 GB medium, balanced quality - recommended
MoE_13B_DPO-Q5_0.gguf Q5_0 8.265 GB legacy; medium, balanced quality - prefer using Q4_K_M
MoE_13B_DPO-Q5_K_S.gguf Q5_K_S 8.265 GB large, low quality loss - recommended
MoE_13B_DPO-Q5_K_M.gguf Q5_K_M 8.506 GB large, very low quality loss - recommended
MoE_13B_DPO-Q6_K.gguf Q6_K 9.842 GB very large, extremely low quality loss
MoE_13B_DPO-Q8_0.gguf Q8_0 12.746 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/MoE_13B_DPO-GGUF --include "MoE_13B_DPO-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/MoE_13B_DPO-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
145
GGUF
Model size
12.9B params
Architecture
llama

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