SummLlama3.1-8B-GGUF Open-Source Summary Generation Model - Multiple Quantization Versions Aid in Rapid Information Extraction

Summllama3.1 8B GGUF

Developed by tensorblock

An 8B-parameter summary generation model optimized based on Llama3 architecture, offering multiple quantization versions

Large Language Model #Text Summarization Optimization #Llama3 Architecture #Multi-scenario Adaptation

Downloads 52

Release Time : 1/2/2025

Model Overview

This is an 8B-parameter language model specifically designed for text summarization tasks, optimized based on the Llama3 architecture, providing multiple quantization versions from Q2 to Q8 to meet different hardware requirements

Model Features

Multiple Quantization Versions

Offers 12 quantization versions from Q2_K to Q8_0 to meet different hardware and performance needs

Efficient Summarization Capability

Specifically optimized for text summarization tasks, capable of generating accurate and concise summaries

Hardware Compatibility

GGUF format compatible with various consumer-grade hardware for easy local deployment

Model Capabilities

Text summarization generation

Long-text compression

Key information extraction

Use Cases

Content Processing

News Summarization

Automatically generate concise summaries of news articles

Condensed version retaining key facts and main points

Research Report Condensation

Compress lengthy academic papers or research reports into executive summaries

Brief version highlighting core findings and conclusions

Business Applications

Meeting Minutes Summarization

Automatically generate summaries of key discussion points from meetings

Concise record including decision points and action items

🚀 DISLab/SummLlama3.1-8B - GGUF

This repository offers GGUF format model files for DISLab/SummLlama3.1-8B, which are designed for summarization tasks. These files are quantized using machines provided by TensorBlock, and are compatible with llama.cpp as of commit b4242.

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

🚀 Quick Start

Downloading the Model

You can download the model files through the command line.

Step 1: Install Huggingface Client

pip install -U "huggingface_hub[cli]"

Step 2: Download a Single Model File

huggingface-cli download tensorblock/SummLlama3.1-8B-GGUF --include "SummLlama3.1-8B-Q2_K.gguf" --local-dir MY_LOCAL_DIR

Step 3: Download Multiple Model Files

If you want to download multiple model files that match a certain pattern (e.g., *Q4_K*gguf), you can use the following command:

huggingface-cli download tensorblock/SummLlama3.1-8B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'

✨ Features

Our Projects

We have other awesome projects as well:

Project	Description
Awesome MCP Servers	A comprehensive collection of Model Context Protocol (MCP) servers. 👀 See what we built 👀
TensorBlock Studio	A lightweight, open, and extensible multi-LLM interaction studio. 👀 See what we built 👀

📚 Documentation

Prompt template

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

Cutting Knowledge Date: December 2023
Today Date: 26 Jul 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

Property	Details
Library Name	transformers
Model Type	DISLab/SummLlama3.1-8B - GGUF
Pipeline Tag	summarization
Tags	TensorBlock, GGUF

Filename	Quant type	File Size	Description
SummLlama3.1-8B-Q2_K.gguf	Q2_K	3.179 GB	smallest, significant quality loss - not recommended for most purposes
SummLlama3.1-8B-Q3_K_S.gguf	Q3_K_S	3.665 GB	very small, high quality loss
SummLlama3.1-8B-Q3_K_M.gguf	Q3_K_M	4.019 GB	very small, high quality loss
SummLlama3.1-8B-Q3_K_L.gguf	Q3_K_L	4.322 GB	small, substantial quality loss
SummLlama3.1-8B-Q4_0.gguf	Q4_0	4.661 GB	legacy; small, very high quality loss - prefer using Q3_K_M
SummLlama3.1-8B-Q4_K_S.gguf	Q4_K_S	4.693 GB	small, greater quality loss
SummLlama3.1-8B-Q4_K_M.gguf	Q4_K_M	4.921 GB	medium, balanced quality - recommended
SummLlama3.1-8B-Q5_0.gguf	Q5_0	5.599 GB	legacy; medium, balanced quality - prefer using Q4_K_M
SummLlama3.1-8B-Q5_K_S.gguf	Q5_K_S	5.599 GB	large, low quality loss - recommended
SummLlama3.1-8B-Q5_K_M.gguf	Q5_K_M	5.733 GB	large, very low quality loss - recommended
SummLlama3.1-8B-Q6_K.gguf	Q6_K	6.596 GB	very large, extremely low quality loss
SummLlama3.1-8B-Q8_0.gguf	Q8_0	8.541 GB	very large, extremely low quality loss - not recommended

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