tensorblock/orthogonal-2x7B-v2-base-GGUF

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LoSboccacc/orthogonal-2x7B-v2-base - GGUF

This repo contains GGUF format model files for LoSboccacc/orthogonal-2x7B-v2-base.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.

Run them on the TensorBlock client using your local machine ↗

Prompt template

<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

Model file specification

Filename	Quant type	File Size	Description
orthogonal-2x7B-v2-base-Q2_K.gguf	Q2_K	4.761 GB	smallest, significant quality loss - not recommended for most purposes
orthogonal-2x7B-v2-base-Q3_K_S.gguf	Q3_K_S	5.588 GB	very small, high quality loss
orthogonal-2x7B-v2-base-Q3_K_M.gguf	Q3_K_M	6.206 GB	very small, high quality loss
orthogonal-2x7B-v2-base-Q3_K_L.gguf	Q3_K_L	6.730 GB	small, substantial quality loss
orthogonal-2x7B-v2-base-Q4_0.gguf	Q4_0	7.281 GB	legacy; small, very high quality loss - prefer using Q3_K_M
orthogonal-2x7B-v2-base-Q4_K_S.gguf	Q4_K_S	7.342 GB	small, greater quality loss
orthogonal-2x7B-v2-base-Q4_K_M.gguf	Q4_K_M	7.783 GB	medium, balanced quality - recommended
orthogonal-2x7B-v2-base-Q5_0.gguf	Q5_0	8.874 GB	legacy; medium, balanced quality - prefer using Q4_K_M
orthogonal-2x7B-v2-base-Q5_K_S.gguf	Q5_K_S	8.874 GB	large, low quality loss - recommended
orthogonal-2x7B-v2-base-Q5_K_M.gguf	Q5_K_M	9.133 GB	large, very low quality loss - recommended
orthogonal-2x7B-v2-base-Q6_K.gguf	Q6_K	10.567 GB	very large, extremely low quality loss
orthogonal-2x7B-v2-base-Q8_0.gguf	Q8_0	13.686 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/orthogonal-2x7B-v2-base-GGUF --include "orthogonal-2x7B-v2-base-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/orthogonal-2x7B-v2-base-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'