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.

Prompt template


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