news-summarizer-t5-GGUF Open-source News Summarization Model - Free Deployment and Support for English Text Summarization

News Summarizer T5 GGUF

Developed by mradermacher

This is a statically quantized version of a T5-based news summarization model, supporting English text summarization tasks.

Text Generation EnglishOpen Source License:Apache-2.0 #News Summarization #Statically Quantized Model #Low-Resource Deployment

Downloads 167

Release Time : 4/1/2025

Model Overview

This model is a quantized version of SurAyush/news-summarizer-t5, focusing on generating concise summaries of news articles.

Model Features

Multiple Quantization Levels

Offers 12 different quantization levels from Q2_K to f16 to meet various scenario requirements.

Efficient Inference

Quantized models significantly reduce memory usage and computational resource demands, making them suitable for resource-constrained environments.

Quality Recommendations

Clearly marks recommended quantization versions (Q4_K_S/Q4_K_M) and highest-quality versions (Q6_K/Q8_0).

Model Capabilities

English Text Summarization

News Content Compression

Key Information Extraction

Use Cases

News Processing

News Brief Generation

Automatically compresses long news articles into concise summaries.

Content Preview Creation

Generates content previews for news aggregation platforms.

Information Processing

Document Summarization

Extracts key information from English documents.

🚀 News Summarizer T5 Quantized Model

This project provides static quantizations of the news summarization model, offering various quantization options for efficient usage.

🚀 Quick Start

If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi - part files.

✨ Features

Summarization: This model is designed for news summarization tasks.
Quantized Versions: It offers multiple static quantization versions for different needs.

📚 Documentation

About

Static quants of https://huggingface.co/SurAyush/news - summarizer - t5. Weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.

Provided Quants

(sorted by size, not necessarily quality. IQ - quants are often preferable over similar sized non - IQ quants)

Link	Type	Size/GB	Notes
GGUF	Q2_K	0.1
GGUF	Q3_K_S	0.1
GGUF	Q3_K_M	0.1	lower quality
GGUF	Q3_K_L	0.1
GGUF	IQ4_XS	0.1
GGUF	Q4_K_S	0.1	fast, recommended
GGUF	Q4_K_M	0.1	fast, recommended
GGUF	Q5_K_S	0.1
GGUF	Q5_K_M	0.1
GGUF	Q6_K	0.2	very good quality
GGUF	Q8_0	0.2	fast, best quality
GGUF	f16	0.2	16 bpw, overkill

Here is a handy graph by ikawrakow comparing some lower - quality quant types (lower is better):

And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.

📄 License

This project is licensed under the apache - 2.0 license.

🙏 Thanks

I thank my company, nethype GmbH, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.

Property	Details
Base Model	SurAyush/news - summarizer - t5
Language	en
Library Name	transformers
License	apache - 2.0
Quantized By	mradermacher
Tags	summarization, generated_from_trainer

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