tensorblock/tiny-random-exaone-GGUF

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hyper-accel/tiny-random-exaone - GGUF

This repo contains GGUF format model files for hyper-accel/tiny-random-exaone.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4882.

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## Prompt template

[|system|]{system_prompt}[|endofturn|]
[|user|]{prompt}
[|assistant|]

Model file specification

Filename	Quant type	File Size	Description
tiny-random-exaone-Q2_K.gguf	Q2_K	0.135 GB	smallest, significant quality loss - not recommended for most purposes
tiny-random-exaone-Q3_K_S.gguf	Q3_K_S	0.147 GB	very small, high quality loss
tiny-random-exaone-Q3_K_M.gguf	Q3_K_M	0.148 GB	very small, high quality loss
tiny-random-exaone-Q3_K_L.gguf	Q3_K_L	0.150 GB	small, substantial quality loss
tiny-random-exaone-Q4_0.gguf	Q4_0	0.165 GB	legacy; small, very high quality loss - prefer using Q3_K_M
tiny-random-exaone-Q4_K_S.gguf	Q4_K_S	0.165 GB	small, greater quality loss
tiny-random-exaone-Q4_K_M.gguf	Q4_K_M	0.166 GB	medium, balanced quality - recommended
tiny-random-exaone-Q5_0.gguf	Q5_0	0.181 GB	legacy; medium, balanced quality - prefer using Q4_K_M
tiny-random-exaone-Q5_K_S.gguf	Q5_K_S	0.181 GB	large, low quality loss - recommended
tiny-random-exaone-Q5_K_M.gguf	Q5_K_M	0.182 GB	large, very low quality loss - recommended
tiny-random-exaone-Q6_K.gguf	Q6_K	0.199 GB	very large, extremely low quality loss
tiny-random-exaone-Q8_0.gguf	Q8_0	0.256 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/tiny-random-exaone-GGUF --include "tiny-random-exaone-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/tiny-random-exaone-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'