tensorblock/Kan-LLaMA-7B-SFT-v0.1-sharded-GGUF

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fierysurf/Kan-LLaMA-7B-SFT-v0.1-sharded - GGUF

This repo contains GGUF format model files for fierysurf/Kan-LLaMA-7B-SFT-v0.1-sharded.

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

Model file specification

Filename	Quant type	File Size	Description
Kan-LLaMA-7B-SFT-v0.1-sharded-Q2_K.gguf	Q2_K	2.615 GB	smallest, significant quality loss - not recommended for most purposes
Kan-LLaMA-7B-SFT-v0.1-sharded-Q3_K_S.gguf	Q3_K_S	3.038 GB	very small, high quality loss
Kan-LLaMA-7B-SFT-v0.1-sharded-Q3_K_M.gguf	Q3_K_M	3.388 GB	very small, high quality loss
Kan-LLaMA-7B-SFT-v0.1-sharded-Q3_K_L.gguf	Q3_K_L	3.687 GB	small, substantial quality loss
Kan-LLaMA-7B-SFT-v0.1-sharded-Q4_0.gguf	Q4_0	3.925 GB	legacy; small, very high quality loss - prefer using Q3_K_M
Kan-LLaMA-7B-SFT-v0.1-sharded-Q4_K_S.gguf	Q4_K_S	3.956 GB	small, greater quality loss
Kan-LLaMA-7B-SFT-v0.1-sharded-Q4_K_M.gguf	Q4_K_M	4.180 GB	medium, balanced quality - recommended
Kan-LLaMA-7B-SFT-v0.1-sharded-Q5_0.gguf	Q5_0	4.760 GB	legacy; medium, balanced quality - prefer using Q4_K_M
Kan-LLaMA-7B-SFT-v0.1-sharded-Q5_K_S.gguf	Q5_K_S	4.760 GB	large, low quality loss - recommended
Kan-LLaMA-7B-SFT-v0.1-sharded-Q5_K_M.gguf	Q5_K_M	4.891 GB	large, very low quality loss - recommended
Kan-LLaMA-7B-SFT-v0.1-sharded-Q6_K.gguf	Q6_K	5.647 GB	very large, extremely low quality loss
Kan-LLaMA-7B-SFT-v0.1-sharded-Q8_0.gguf	Q8_0	7.313 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/Kan-LLaMA-7B-SFT-v0.1-sharded-GGUF --include "Kan-LLaMA-7B-SFT-v0.1-sharded-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/Kan-LLaMA-7B-SFT-v0.1-sharded-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'