tensorblock/shisa-base-7b-v1-GGUF

Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server

augmxnt/shisa-base-7b-v1 - GGUF

This repo contains GGUF format model files for augmxnt/shisa-base-7b-v1.

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

Filename	Quant type	File Size	Description
shisa-base-7b-v1-Q2_K.gguf	Q2_K	3.136 GB	smallest, significant quality loss - not recommended for most purposes
shisa-base-7b-v1-Q3_K_S.gguf	Q3_K_S	3.618 GB	very small, high quality loss
shisa-base-7b-v1-Q3_K_M.gguf	Q3_K_M	3.972 GB	very small, high quality loss
shisa-base-7b-v1-Q3_K_L.gguf	Q3_K_L	4.275 GB	small, substantial quality loss
shisa-base-7b-v1-Q4_0.gguf	Q4_0	4.610 GB	legacy; small, very high quality loss - prefer using Q3_K_M
shisa-base-7b-v1-Q4_K_S.gguf	Q4_K_S	4.642 GB	small, greater quality loss
shisa-base-7b-v1-Q4_K_M.gguf	Q4_K_M	4.870 GB	medium, balanced quality - recommended
shisa-base-7b-v1-Q5_0.gguf	Q5_0	5.544 GB	legacy; medium, balanced quality - prefer using Q4_K_M
shisa-base-7b-v1-Q5_K_S.gguf	Q5_K_S	5.544 GB	large, low quality loss - recommended
shisa-base-7b-v1-Q5_K_M.gguf	Q5_K_M	5.678 GB	large, very low quality loss - recommended
shisa-base-7b-v1-Q6_K.gguf	Q6_K	6.536 GB	very large, extremely low quality loss
shisa-base-7b-v1-Q8_0.gguf	Q8_0	8.465 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/shisa-base-7b-v1-GGUF --include "shisa-base-7b-v1-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/shisa-base-7b-v1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'