This model is a multilingual summarization model based on the mT5 architecture, specifically fine-tuned for Sinhala to generate abstractive summaries of CNN Daily Mail Sinhala news.

Natural Language ProcessingTransformers

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

Natural Language ProcessingTransformersEnglish

A text summarization model fine-tuned on the CNN/DailyMail news dataset based on the T5-small model, capable of generating concise summaries of news articles.

Natural Language ProcessingTransformers

An English abstractive summarization model fine-tuned on MBART-large-50, trained on the CNN/DailyMail dataset, excelling at generating concise summaries for news articles.

Natural Language ProcessingTransformersEnglish

A Dutch news summarization model based on the T5 architecture, fine-tuned for the Dutch version of CNN Daily Mail

Natural Language ProcessingJaxOther

A Dutch news summarization model fine-tuned on mbart-large-cc25, supporting CNN/DailyMail and XSum format summarization tasks

Natural Language ProcessingTransformersOther

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

Natural Language ProcessingTransformersEnglish

This model is a fine-tuned T5 architecture for news summarization, trained on the CNN/DailyMail news dataset.

Natural Language ProcessingJaxEnglish

This model is a summarization generation model trained on the CNN/Daily Mail dataset, primarily used for generating concise summaries of news articles.

Natural Language ProcessingTransformers

A summarization model trained on the CNN/Daily Mail dataset, capable of automatically generating concise summaries of news articles.

Natural Language ProcessingJax

News summarization model based on ALBERT and GPT2 architectures, fine-tuned on the CNN/DailyMail dataset

Natural Language ProcessingTransformers