metadata
library_name: transformers
base_model: DISLab/SummLlama3.2-3B
pipeline_tag: summarization
tags:
- TensorBlock
- GGUF
Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
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.
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'