The Best 721 Text Generation Tools in 2025

BART model pre-trained on English corpus, specifically fine-tuned for the CNN/Daily Mail dataset, suitable for text summarization tasks

Parrot is a T5-based paraphrasing framework designed to accelerate the training of Natural Language Understanding (NLU) models through high-quality paraphrase generation for data augmentation.

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

A T5-based model specialized in extracting atomic claims from summary texts, serving as a key component in summary factuality assessment pipelines.

UniEval is a unified multidimensional evaluator for automatic evaluation of natural language generation tasks, supporting assessment across multiple interpretable dimensions.

A text paraphrasing model fine-tuned based on the PEGASUS architecture, capable of generating sentences with the same meaning but different expressions.

This is a Korean text summarization model based on the T5 architecture, specifically designed for Korean text summarization tasks. It is trained on multiple Korean datasets by fine-tuning the paust/pko-t5-base model.

PEGASUS is a Transformer-based pretrained model specifically designed for abstractive text summarization tasks.

A dialogue summarization model based on the BART-large architecture, fine-tuned specifically for the SAMSum corpus, suitable for generating dialogue summaries.

A Korean text summarization model based on the KoBART architecture, capable of generating concise summaries of Korean news articles.

A text paraphrasing model trained on the T5-base architecture, capable of generating high-quality paraphrased text, claimed to be one of the best paraphrasing models on the Hugging Face platform

A keyphrase extraction model fine-tuned based on BART-base, suitable for scientific literature and news text keyphrase extraction tasks

A grammar correction model based on the T5 architecture, capable of automatically fixing grammatical errors in input text.

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

English sentence paraphrase generation model based on T5 architecture, trained using Google PAWS dataset

A text summarization model fine-tuned based on the T5 Small architecture, capable of generating concise and coherent summaries of input texts.

This model is a text summarization model based on the Long-T5 architecture, specifically designed to generate easy-to-understand summaries of scientific papers.

A GPT-2 fine-tuned text-to-image prompt generation model trained on 250,000 user-submitted prompts from Midjourney

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

PEGASUS is an abstractive summarization model based on pre-training with gap sentences, developed by Google Research.

A T5 model fine-tuned on the SuperPrompt dataset, designed to expand brief text prompts into more detailed descriptions.

PEGASUS is an abstractive summarization pretraining model based on gap sentence generation, focusing on text summarization tasks, with performance enhanced through mixed dataset training and various optimization strategies.

A sequence-to-sequence model based on the BART architecture, specifically designed for abstractive summarization of meeting dialogues, supporting multilingual meeting record processing.

mBART-large-50 is a multilingual sequence-to-sequence model supporting text summarization and generation tasks in 50 languages.

A T5 model trained on 500,000 articles with titles, used to generate concise and accurate single-line titles for given articles.

A book summarization model based on the Long-T5 architecture, capable of processing long documents and generating high-quality summaries.

A model based on the Long-T5 architecture, specifically designed for generating popular summaries of scientific papers, transforming complex research content into text understandable by non-specialists.

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

A summary generation model based on the BookSum dataset, excelling at producing concise and accurate summaries from book content.

This is an experimental model designed to correct spelling errors and punctuation in English text.

Two enhanced versions of the Command-R 35B model for horror themes, strengthened with the DARK HORROR NEO Imatrix dataset to enhance horror element generation

CodeT5-base is a multilingual code summarization model based on the T5 architecture, supporting six programming languages: Ruby, JavaScript, Go, Python, Java, and PHP.

A T5-based prompt enhancement model that expands brief prompts into detailed descriptions

A text summarization model based on the LED architecture, specifically designed for generating summaries of technical, academic, and narrative long texts.

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

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

PEGASUS-XSum is a pre-trained text summarization model based on the PEGASUS architecture, specifically optimized for extreme summarization (XSum) tasks.

A Russian text summarization model developed by SberDevices, based on the T5 architecture with 1.7B parameters

Russian news summarization model based on MBART architecture, optimized for Gazeta.ru news articles

This is a sequence-to-sequence model based on the BART architecture, specifically designed for dialogue summarization tasks.

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

Russian news headline generation model based on rut5-base, optimized for the Telegram platform