GGUF
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GGUF
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tolgadev/llama-2-7b-ruyallm - GGUF

This repo contains GGUF format model files for tolgadev/llama-2-7b-ruyallm.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.

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Model file specification

Filename Quant type File Size Description
llama-2-7b-ruyallm-Q2_K.gguf Q2_K 2.413 GB smallest, significant quality loss - not recommended for most purposes
llama-2-7b-ruyallm-Q3_K_S.gguf Q3_K_S 2.804 GB very small, high quality loss
llama-2-7b-ruyallm-Q3_K_M.gguf Q3_K_M 3.130 GB very small, high quality loss
llama-2-7b-ruyallm-Q3_K_L.gguf Q3_K_L 3.409 GB small, substantial quality loss
llama-2-7b-ruyallm-Q4_0.gguf Q4_0 3.628 GB legacy; small, very high quality loss - prefer using Q3_K_M
llama-2-7b-ruyallm-Q4_K_S.gguf Q4_K_S 3.657 GB small, greater quality loss
llama-2-7b-ruyallm-Q4_K_M.gguf Q4_K_M 3.865 GB medium, balanced quality - recommended
llama-2-7b-ruyallm-Q5_0.gguf Q5_0 4.403 GB legacy; medium, balanced quality - prefer using Q4_K_M
llama-2-7b-ruyallm-Q5_K_S.gguf Q5_K_S 4.403 GB large, low quality loss - recommended
llama-2-7b-ruyallm-Q5_K_M.gguf Q5_K_M 4.525 GB large, very low quality loss - recommended
llama-2-7b-ruyallm-Q6_K.gguf Q6_K 5.226 GB very large, extremely low quality loss
llama-2-7b-ruyallm-Q8_0.gguf Q8_0 6.769 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/llama-2-7b-ruyallm-GGUF --include "llama-2-7b-ruyallm-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/llama-2-7b-ruyallm-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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GGUF
Model size
6.84B params
Architecture
llama

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Dataset used to train tensorblock/llama-2-7b-ruyallm-GGUF