# High ROUGE Score

A fine-tuned LED model specifically for financial text summarization tasks, based on pszemraj/led-large-book-summary, developed by the Warwick Business School GEN AI GROUP 15 team

A text summarization model fine-tuned on the xsum dataset based on the T5-small architecture, capable of generating concise summaries.

This model is a text summarization model fine-tuned on the samsum dataset based on google/pegasus-cnn_dailymail, specifically designed for dialogue summarization tasks.

A Turkish news summarization model fine-tuned based on mukayese/mt5-base-turkish-summarization, capable of generating concise and coherent summaries.

A Spanish clickbait news summarization model fine-tuned on the NoticIA dataset, capable of revealing the true content behind sensational headlines

A dialogue summarization model fine-tuned based on BART-large-xsum, specifically optimized for the SamSum dialogue dataset

A dialogue summarization generation model fine-tuned on the SAMSum dataset based on the BART-large architecture

A Chinese text summarization model fine-tuned based on mT5, trained on diverse Chinese datasets, capable of generating coherent and concise summaries for various texts.

A text generation model fine-tuned on the samsum dialogue summarization dataset based on Google's flan-t5-base model, excelling in dialogue summarization tasks

A summarization model based on the BERT2BERT architecture, fine-tuned specifically for the CNN/DailyMail dataset, capable of generating high-quality news summaries.

A text generation model fine-tuned on the samsum dialogue summarization dataset based on Google's flan-t5-base model

This model is a text summarization model fine-tuned on the samsum dataset based on facebook/bart-large-xsum, specializing in generating dialogue summaries.

A summary generation model fine-tuned on the stacked-samsum-1024 dataset based on google/flan-t5-large, using stacked summarization method to improve information extraction capability

A summarization model fine-tuned on the xsum dataset based on facebook/bart-base, excelling in generating concise and accurate summaries.

This is a fine-tuned summarization model based on T5-large, trained on XSUM and CNN Daily Mail datasets, excelling at generating concise and accurate summaries.

A specialized Chinese version of PAGASUS-base optimized for Chinese text summarization tasks, fine-tuned on multiple Chinese summarization datasets

A Chinese PEGASUS-large model specialized in text summarization tasks, fine-tuned on multiple Chinese summarization datasets

A BART model based on LSG technology, optimized for long-sequence summarization tasks, supporting input sequences up to 16,384 tokens in length

A Thai sentence summarization model fine-tuned based on mT5-base, developed by Computer Engineering students at King Mongkut's University of Technology Thonburi

A resume summary generation model fine-tuned based on distilbart-cnn-12-6, performing well on ROUGE metrics

A resume summary generation model fine-tuned based on BART-large architecture, with excellent performance on ROUGE metrics

A text summarization model based on the BART architecture, fine-tuned on an unknown dataset, excels at generating resume summaries

PEGASUS model fine-tuned on 2000 Bloomberg financial news articles, optimized for financial domain summarization

A dialogue summarization model based on the BART-large architecture, specifically fine-tuned on the SAMSum dialogue dataset, capable of generating high-quality dialogue summaries.

A summarization model based on the BERT2BERT architecture, fine-tuned specifically for the CNN/DailyMail dataset, suitable for news article summarization tasks.

A lightweight dialogue summarization model fine-tuned on the SAMSum dataset, trained using Amazon SageMaker and Hugging Face containers

A French text summarization model based on T5 Transformer, fine-tuned specifically for French generative text summarization tasks.

A sequence-to-sequence model based on the BART-large architecture, specifically fine-tuned for meeting summarization tasks and supports multi-dataset training

Spanish abstractive summarization model based on mT5-small architecture, trained on the MLSum Spanish dataset