# Sequence Generation

This is a sequence-to-sequence model based on T5-base, specifically designed for decomposing complex questions into multiple sub-questions.

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

This model is a fine-tuned version based on indobenchmark/indobart-v2, designed for AMR-to-text conversion tasks.

ReasTAP is a table reasoning-based pretrained model that injects table reasoning skills through synthetic reasoning examples and is fine-tuned on the WikiSQL dataset.

This model is a text summarization model fine-tuned on the samsum dataset based on facebook/bart-large-xsum, specializing in generating dialogue summaries.

An English-to-Japanese translation model fine-tuned on the kde4 dataset, based on Helsinki-NLP/opus-tatoeba-en-ja

Italian news summarization model based on IT5 Efficient Small EL32 architecture, fine-tuned on Fanpage and Il Post datasets

A Chinese couplet generation model based on the GPT2 architecture, pre-trained with the UER-py framework, capable of generating Chinese text that conforms to traditional couplet formats.

This model is a fine-tuned English-to-Traditional Chinese translation model based on Helsinki-NLP/opus-mt-en-zh on the kde4 dataset, achieving a Bleu score of 39.0863.

A speech processing model based on HuBERT and BART architecture, supporting Automatic Speech Recognition (ASR) tasks

An mbart model trained from scratch on an unknown dataset, specific uses and features require further details

English to Romanian translation model fine-tuned on the wmt16 dataset based on the T5-small model

This is a text processing model supporting Russian, primarily used for text generation and text completion tasks.