tensorblock/reka-flash-3-GGUF

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RekaAI/reka-flash-3 - GGUF

This repo contains GGUF format model files for RekaAI/reka-flash-3.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4823.

human: {system_prompt} {prompt} <sep> assistant:

Filename	Quant type	File Size	Description
reka-flash-3-Q2_K.gguf	Q2_K	8.631 GB	smallest, significant quality loss - not recommended for most purposes
reka-flash-3-Q3_K_S.gguf	Q3_K_S	9.935 GB	very small, high quality loss
reka-flash-3-Q3_K_M.gguf	Q3_K_M	10.863 GB	very small, high quality loss
reka-flash-3-Q3_K_L.gguf	Q3_K_L	11.412 GB	small, substantial quality loss
reka-flash-3-Q4_0.gguf	Q4_0	11.924 GB	legacy; small, very high quality loss - prefer using Q3_K_M
reka-flash-3-Q4_K_S.gguf	Q4_K_S	12.628 GB	small, greater quality loss
reka-flash-3-Q4_K_M.gguf	Q4_K_M	13.610 GB	medium, balanced quality - recommended
reka-flash-3-Q5_0.gguf	Q5_0	14.460 GB	legacy; medium, balanced quality - prefer using Q4_K_M
reka-flash-3-Q5_K_S.gguf	Q5_K_S	14.792 GB	large, low quality loss - recommended
reka-flash-3-Q5_K_M.gguf	Q5_K_M	15.635 GB	large, very low quality loss - recommended
reka-flash-3-Q6_K.gguf	Q6_K	18.441 GB	very large, extremely low quality loss
reka-flash-3-Q8_0.gguf	Q8_0	22.217 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/reka-flash-3-GGUF --include "reka-flash-3-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/reka-flash-3-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'