# BART Fine-tuning

A few-shot summarization generation model based on BART-large, trained with 100 samples from the XSUM dataset, demonstrating the potential of few-shot learning in summarization tasks.

This model is a fine-tuned text summarization model based on facebook/bart-large-cnn, excelling in generating summaries for legal texts.

English dialogue summarization model fine-tuned based on BART-large-cnn, specifically optimized for the Samsung/samsum dataset

A fine-tuned text summarization model based on barthez-orangesum-abstract, excelling in French text summarization tasks

Fine-tuned based on Facebook's BART model, specifically designed for summarizing sections of financial 10K reports.

A text summarization model fine-tuned based on facebook/bart-base, excelling in generating concise and coherent summaries from lengthy texts.

A text keyword extraction model fine-tuned based on facebook/bart-large

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

A text summarization generation model fine-tuned on the multi_news dataset based on facebook/bart-base

This model is a text summarization model fine-tuned on the multi_news dataset based on facebook/bart-base, specifically designed for multi-document summarization tasks.

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 sequence-to-sequence model based on the BART architecture, specifically fine-tuned for Amazon English user reviews to generate review summaries

Model fine-tuned on the squad dataset based on facebook/bart-base, suitable for question answering tasks

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

A Swedish summarization model based on the BART architecture, fine-tuned on the CNN Daily Swedish dataset

GENRE is a sequence-to-sequence-based entity retrieval system that employs a fine-tuned BART architecture and generates unique entity names through constrained beam search technology.

This model is a fine-tuned version of facebook/bart-base on the samsum dataset, specifically designed for summarization tasks.

A Chinese text summarization model based on the BART architecture with 139 million parameters, excelling in text summarization tasks.

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

This model is a bart-base model fine-tuned on the CNN/DailyMail summarization dataset, excelling in text summarization tasks

A financial event summarization model fine-tuned based on BART-large architecture, with excellent performance on Rouge metrics

An English text summarization generator fine-tuned on the BART model, trained on the CNN-DailyMail dataset

This model is a seq2seq model based on the BART architecture, specifically designed for dialogue summarization tasks, fine-tuned on the SAMSum dataset.

A German abstract generation model fine-tuned on the mlsum de dataset based on facebook/bart-base

A Korean news summarization model fine-tuned based on the KoBART framework, suitable for extracting key information from long news articles to generate concise summaries.

This model is a BART-large-xsum model fine-tuned on the Samsum dataset, specifically designed for dialogue summarization tasks.

A weakly supervised topic label generation model based on BART, solving topic labeling tasks through generation rather than selection

This model is based on the BART architecture, fine-tuned on the SAMSum dialogue dataset for abstractive text summarization, specifically designed for generating dialogue summaries.

A news summarization model fine-tuned on the Gigaword dataset based on the BART-large architecture

A text generation model fine-tuned on the wsj_markets dataset based on the BART-large architecture, excelling in summarization tasks

This model is a fine-tuned version of facebook/bart-base on the pub_med_summarization_dataset, primarily designed for medical literature summarization tasks.

A text generation model fine-tuned on medical literature abstract datasets based on BART-large-cnn, excelling in medical abstract generation tasks

This model is a fine-tuned BART-base architecture for patent abstract processing, trained on 7 million patent abstract records, primarily for research reference in patent abstracts.