# News Summarization

A text summarization model trained based on the mt5-base architecture, capable of extracting key information from text to generate summaries.

A text summarization model fine-tuned on the XSum dataset based on T5-small

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

BART Large CNN is a pre-trained model based on the BART architecture, specifically designed for text summarization tasks.

This is a summarization model fine-tuned on the CNNDailyMail dataset based on the Flan T5 base model, capable of compressing news articles into concise summaries.

This is a statically quantized version of a T5-based news summarization model, supporting English text summarization tasks.

An improved Khmer text summarization model based on mT5-small, supporting inputs of up to 1024 tokens, suitable for summarizing Khmer articles, paragraphs, or documents.

A pre-trained model based on the BART architecture, specifically designed for text summarization tasks of English news articles.

BART Large CNN is a pre-trained model based on the BART architecture, specifically designed for text summarization tasks.

A Bengali text summarization model fine-tuned based on the MT5 model, suitable for generating concise summaries of Bengali texts.

This is an ONNX-optimized version of the facebook/bart-large-cnn model, primarily used for text summarization tasks.

A fine-tuned model based on Hugging Face Transformers library, supporting Tamil summarization and English-Tamil translation tasks.

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

A fine-tuned text summarization model based on the BART architecture, designed to generate concise and accurate summaries

A summarization model fine-tuned on the cnn_dailymail dataset based on google/mt5-small

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

DistilBART-CNN-12-6 is a distilled version of the BART model, optimized for text summarization tasks, with a smaller size while maintaining high performance.

News summarization model fine-tuned on google/pegasus-xsum, trained on the cnn_dailymail 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.

A fine-tuned T5 model specialized for TLDR news article summarization and headline generation

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

A news summarization model fine-tuned based on Pegasus architecture, specifically optimized for BBC news content

A lightweight pre-trained encoder-decoder model based on the Transformer architecture, optimized for text summarization tasks.

A lightweight pre-trained encoder-decoder model based on Transformer architecture, specialized for Chinese news summarization tasks.

This model is a fine-tuned version of facebook/bart-base on the XSum dataset, primarily used for summarization 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

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 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.

A text summarization model fine-tuned on the cnn_dailymail dataset based on the T5-small architecture, excelling in news summarization tasks

Randeng-Pegasus-238M-Summary-Chinese is a Chinese abstract generation model based on the PEGASUS architecture, developed by IDEA-CCNL, specifically designed for generating summaries of Chinese texts.

The MTL-Summarization Model is a text generation model specifically designed for summarization tasks, trained through supervised pre-training on multiple annotated summarization datasets.

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

A text summarization model fine-tuned based on the PEGASUS architecture, excelling in generating concise and accurate summaries

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

DistilBART is a distilled version of the BART model, optimized for text summarization tasks, significantly improving inference speed while maintaining high performance.

DistilBART is a distilled version of the BART model, focusing on text summarization tasks, significantly reducing model size and inference time while maintaining high performance.

DistilBART is a distilled version of the BART model, focusing on text summarization tasks, significantly improving inference speed while maintaining high performance.

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