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Minirecord/llama13b_2s_dpo - GGUF

This repo contains GGUF format model files for Minirecord/llama13b_2s_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
llama13b_2s_dpo-Q2_K.gguf Q2_K 4.600 GB smallest, significant quality loss - not recommended for most purposes
llama13b_2s_dpo-Q3_K_S.gguf Q3_K_S 5.356 GB very small, high quality loss
llama13b_2s_dpo-Q3_K_M.gguf Q3_K_M 5.988 GB very small, high quality loss
llama13b_2s_dpo-Q3_K_L.gguf Q3_K_L 6.539 GB small, substantial quality loss
llama13b_2s_dpo-Q4_0.gguf Q4_0 6.955 GB legacy; small, very high quality loss - prefer using Q3_K_M
llama13b_2s_dpo-Q4_K_S.gguf Q4_K_S 7.008 GB small, greater quality loss
llama13b_2s_dpo-Q4_K_M.gguf Q4_K_M 7.421 GB medium, balanced quality - recommended
llama13b_2s_dpo-Q5_0.gguf Q5_0 8.459 GB legacy; medium, balanced quality - prefer using Q4_K_M
llama13b_2s_dpo-Q5_K_S.gguf Q5_K_S 8.459 GB large, low quality loss - recommended
llama13b_2s_dpo-Q5_K_M.gguf Q5_K_M 8.699 GB large, very low quality loss - recommended
llama13b_2s_dpo-Q6_K.gguf Q6_K 10.058 GB very large, extremely low quality loss
llama13b_2s_dpo-Q8_0.gguf Q8_0 13.027 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/llama13b_2s_dpo-GGUF --include "llama13b_2s_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/llama13b_2s_dpo-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
24
GGUF
Model size
13.2B params
Architecture
llama

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Inference API
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