# News summarization

Indonesian text summarization model fine-tuned from facebook/bart-large-cnn

A news analysis model fine-tuned based on Llama-3.2-3B, supporting summarization, sentiment analysis, stock ticker extraction, and ad recognition

A text summarization model fine-tuned on the XSum dataset using LoRA technology, based on the T5-small model

An Indonesian abstract generation model based on PEGASUS architecture, fine-tuned on the Liputan6 news dataset, suitable for automatic summarization of Indonesian news content.

A Portuguese summarization model fine-tuned from Google T5-small, optimized for Portuguese text summarization tasks

A Thai text summarization model fine-tuned based on the mT5 architecture, capable of generating concise summaries between 40-140 characters

This is a Hebrew text summarization model that can automatically generate concise summaries from input Hebrew texts.

A Thai text summarization model fine-tuned based on mT5-small, specifically designed for generating article titles

A lightweight text summarization model based on the BART architecture, compressing the original model size through knowledge distillation while retaining core summarization capabilities

An mT5 model fine-tuned on the XL-Sum dataset for 45 languages, designed for multilingual summarization tasks.

Hungarian abstractive summarization model based on mT5-base architecture, trained on HunSum-1 dataset

BART is a Transformer-based sequence-to-sequence model specifically designed for text summarization tasks.

This is a fine-tuned mT5-small model for Greek text summarization tasks, capable of generating summaries for Greek texts.

A Brazilian Portuguese abstractive text summarization model fine-tuned on PTT5, supporting summarization for various text types including news.

A text summarization model fine-tuned based on google/long-t5-tglobal-base, performing well on XSum and CNN/DailyMail datasets.

This model is a text summarization model fine-tuned on the multi_news dataset based on distilbart-cnn-12-6, specifically designed for multi-document summarization tasks.

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.

Abstractive summarization model fine-tuned on the Arabic summarization dataset xlsum based on AraT5-base

A multilingual summarization model based on mT5, specifically fine-tuned for Arabic on the XLSum dataset

This model is a generative summarization model fine-tuned on the Persian summarization dataset pn_summary based on mT5_multilingual_XLSum

A summarization generation model fine-tuned on the xlsum Arabic dataset based on google/mt5-base

A Turkish text summarization model fine-tuned on the mlsum/tu dataset based on google/mt5-base

mT5 model fine-tuned on XL-Sum dataset for 45 languages, designed for multilingual summarization tasks

A large-scale summarization model based on the BART architecture, fine-tuned specifically on the xsum dataset, excelling at generating concise news summaries.

This model is a Persian text summarization model based on the mT5-base architecture, specifically optimized for the pn_summary dataset, capable of generating high-quality Persian text summaries.

An encoder-decoder model based on RoBERTa architecture, specifically designed for extreme summarization tasks, fine-tuned on the BBC XSum dataset.

An encoder-decoder model for Indonesian text summarization fine-tuned based on BERT-base and GPT2-small, suitable for generating summaries of Indonesian texts.

This is an encoder-decoder model based on the BERT-small architecture, specifically fine-tuned for summarization tasks on the CNN/Dailymail dataset.

keyT5 is a text-to-keyword model based on the T5 architecture, primarily used for extracting keywords from Russian text.