distilbart-xsum-12-3 Open-source Abstract Generation Model - High-performance, Low-time-consumption Optimization for Text Summarization

Distilbart Xsum 12 3

Developed by sshleifer

DistilBART is a distilled version of the BART model, specifically optimized for summarization tasks, significantly reducing model parameters and inference time while maintaining high performance.

Text Generation EnglishOpen Source License:Apache-2.0 #News Summarization #Lightweight BART #Low-latency Inference

Downloads 579

Release Time : 3/2/2022

Model Overview

A lightweight summarization model based on the BART architecture, compressed from the original model using knowledge distillation techniques, suitable for text compression scenarios such as news summarization.

Model Features

Efficient Inference

Achieves 2.54x speedup compared to the original BART model, significantly reducing computational resource requirements.

Performance Balance

Strikes a good balance between model size and summarization quality (Rouge scores).

Multiple Variants Available

Offers variants with different parameter scales to accommodate various hardware conditions.

Model Capabilities

News Summarization

Long Text Compression

Key Information Extraction

Use Cases

Media Industry

Automatic News Summarization

Compress lengthy news reports into concise summaries

Achieves 21.37 Rouge-2 score on the XSum dataset

Knowledge Management

Document Summarization

Automatically generate summaries for technical documents or research reports

Property	Details
Model Type	Summarization models
Training Data	cnn_dailymail, xsum

Model Name	MM Params	Inference Time (MS)	Speedup	Rouge 2	Rouge-L
distilbart-xsum-12-1	222	90	2.54	18.31	33.37
distilbart-xsum-6-6	230	132	1.73	20.92	35.73
distilbart-xsum-12-3	255	106	2.16	21.37	36.39
distilbart-xsum-9-6	268	136	1.68	21.72	36.61
bart-large-xsum (baseline)	406	229	1	21.85	36.50
distilbart-xsum-12-6	306	137	1.68	22.12	36.99
bart-large-cnn (baseline)	406	381	1	21.06	30.63
distilbart-12-3-cnn	255	214	1.78	20.57	30.00
distilbart-12-6-cnn	306	307	1.24	21.26	30.59
distilbart-6-6-cnn	230	182	2.09	20.17	29.70

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Distilbart Xsum 12 3

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 DistilBART Model

🚀 Quick Start

💻 Usage Examples

Basic Usage

📚 Documentation

Metrics for DistilBART models

📄 License