# Lightweight T5

A text summarization model fine-tuned based on the T5-small architecture, specifically designed for processing stock news content

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

A dialogue summarization model fine-tuned based on the T5 Small architecture, specifically optimized for the Samsung/samsum dataset, capable of generating concise and accurate dialogue summaries.

A Hausa-to-Chinese translation model fine-tuned based on T5-small, achieving a BLEU score of 30.0183 on the evaluation set.

This is a GGUF format model converted from MBZUAI/LaMini-Flan-T5-248M, suitable for text generation tasks.

This model is a fine-tuned version of google/flan-t5-base on the samsum dialogue summarization dataset, specifically designed for dialogue summarization tasks.

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

A lightweight text summarization model fine-tuned on the xsum dataset based on t5-small, featuring fast generation speed and low resource usage

A lightweight model fine-tuned on T5-small that generates SQL queries from natural language with table structures, supporting multi-table join operations.

A lightweight Chinese version of mT5-small model specialized in natural language transformation tasks

This is a T5 model customized for Arabic and English tasks, serving as an alternative to the google/mt5-base model, with a smaller size and a focus on Arabic and English-related tasks.

A T5 model customized for Arabic and English tasks, smaller in size and optimized for specific languages.

A legal text translation model optimized based on T5-small architecture, specializing in English to Czech legal document translation

Lightweight T5 model specialized for translating legal texts from Swedish to English, trained on three parallel corpora

A small T5 model specialized for French to English legal text translation

Small T5 model for Czech legal text to English translation, based on 60 million parameter architecture