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Bart Large Finetuned Qtsumm

Developed by yale-nlp
A BART-based model specifically designed for query-oriented table summarization tasks, fine-tuned on the QTSumm dataset
Downloads 201
Release Time : 10/20/2023

Model Overview

This model generates query-relevant text summaries for tabular data, capable of converting structured table information into natural language descriptions

Model Features

Query-oriented summarization
Capable of generating targeted table summaries based on specific queries
Table comprehension capability
Excels at processing structured tabular data and extracting key information
BART-based architecture
Utilizes the powerful sequence-to-sequence generation capabilities of the BART model

Model Capabilities

Table data understanding
Query-relevant summarization generation
Structured data to text conversion

Use Cases

Data analysis
Business report generation
Automatically generates executive summaries from business data tables
Saves time on manual report writing
Scientific data interpretation
Converts complex scientific data tables into easily understandable descriptions
Helps non-experts understand research findings
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