# T5 Fine-tuned Model

A statically quantized model based on the T5 architecture, specialized for academic paper abstract generation tasks

A text summarization generation model fine-tuned based on t5-small, performing well in the field of financial news

A T5-small fine-tuned model for medical record summarization, used to generate concise summaries of patient medical records

Korean text summarization model based on T5 architecture, specifically fine-tuned for news reporting

A text summarization model based on the T5-Small architecture, fine-tuned on the CNN/Daily Mail dataset for generative text summarization.

A T5-small fine-tuned model for generating summaries of U.S. Congressional bills

A T5-based Spanish question generation model, fine-tuned from the machine-translated Spanish version of the FairytaleQA dataset

A Russian text summarization model fine-tuned from ai-forever/ruT5-base, trained on approximately 60,000 samples, suitable for summarization tasks such as news articles.

A Russian text and dialogue summarization model fine-tuned based on ruT5-base, supporting multi-domain Russian text summarization tasks

A T5-based fine-tuned Portuguese legal text summarization model, specifically designed for automatic summarization of judicial cases

A T5-small fine-tuned model for generating tags for machine learning articles, automatically converting article content into relevant tags

Korean news summarization generation model based on T5 architecture, fine-tuned on the naver-news-summarization-ko dataset

A Korean text summarization model fine-tuned based on paust/pko-t5-large, capable of generating concise summaries from long Korean texts

A Korean text summarization model based on the T5 architecture, capable of generating concise summaries for long Korean texts

TGL-3 is a fine-tuned abstract generation model based on t5-small, trained on 23,000 openreview.net abstract data entries, supporting academic text summarization tasks.

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

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

A fine-tuned headline generation model based on t5-small, used to generate concise headlines from news text

This is a T5-base architecture model fine-tuned on the WikiSQL dataset for generating questions from tables.

Titlewave is a Chrome browser extension designed to help users choose better titles for Stack Overflow questions. This model is used to generate new title suggestions based on the question body.

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

T5-based doc2query model for document expansion and training data generation

This model is a fine-tuned version of t5-small on an unknown dataset, primarily used for text rewriting tasks, specifically targeting PubMed-related texts.

This model is fine-tuned from Google's T5-base model on an emotion recognition dataset, designed for text sentiment classification tasks, capable of classifying text into 6 basic emotions.

This model is a fine-tuned T5-base model on Twitter sentiment extraction dataset, specifically designed for sentiment text segment extraction tasks.

T5-base fine-tuned model for cocktail recipe generation

A paper abstract-to-title generation model fine-tuned on mt5-small, trained for 4 hours on the arxiv dataset

A French text summarization model based on T5 Transformer, fine-tuned specifically for French generative text summarization tasks.