tensorblock/SummLlama3.2-3B-GGUF

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DISLab/SummLlama3.2-3B - GGUF

This repo contains GGUF format model files for DISLab/SummLlama3.2-3B.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.

Run them on the TensorBlock client using your local machine ↗

Prompt template

<|begin_of_text|><|start_header_id|>system<|end_header_id|>

Cutting Knowledge Date: December 2023
Today Date: 20 Nov 2024

{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>

{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>

Model file specification

Filename	Quant type	File Size	Description
SummLlama3.2-3B-Q2_K.gguf	Q2_K	1.364 GB	smallest, significant quality loss - not recommended for most purposes
SummLlama3.2-3B-Q3_K_S.gguf	Q3_K_S	1.543 GB	very small, high quality loss
SummLlama3.2-3B-Q3_K_M.gguf	Q3_K_M	1.687 GB	very small, high quality loss
SummLlama3.2-3B-Q3_K_L.gguf	Q3_K_L	1.815 GB	small, substantial quality loss
SummLlama3.2-3B-Q4_0.gguf	Q4_0	1.917 GB	legacy; small, very high quality loss - prefer using Q3_K_M
SummLlama3.2-3B-Q4_K_S.gguf	Q4_K_S	1.928 GB	small, greater quality loss
SummLlama3.2-3B-Q4_K_M.gguf	Q4_K_M	2.019 GB	medium, balanced quality - recommended
SummLlama3.2-3B-Q5_0.gguf	Q5_0	2.270 GB	legacy; medium, balanced quality - prefer using Q4_K_M
SummLlama3.2-3B-Q5_K_S.gguf	Q5_K_S	2.270 GB	large, low quality loss - recommended
SummLlama3.2-3B-Q5_K_M.gguf	Q5_K_M	2.322 GB	large, very low quality loss - recommended
SummLlama3.2-3B-Q6_K.gguf	Q6_K	2.644 GB	very large, extremely low quality loss
SummLlama3.2-3B-Q8_0.gguf	Q8_0	3.422 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/SummLlama3.2-3B-GGUF --include "SummLlama3.2-3B-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/SummLlama3.2-3B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'