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mT5 Small for Formal-to-informal Style Transfer 🤗
This repository contains the checkpoint for the mT5 Small model fine-tuned on Formal-to-informal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele Sarti and Malvina Nissim.
A comprehensive overview of other released materials is provided in the gsarti/it5 repository. Refer to the paper for additional details concerning the reported scores and the evaluation approach.
Using the model
Model checkpoints are available for usage in Tensorflow, Pytorch and JAX. They can be used directly with pipelines as:
from transformers import pipelines
f2i = pipeline("text2text-generation", model='it5/mt5-small-formal-to-informal')
f2i("Vi ringrazio infinitamente per vostra disponibilità")
>>> [{"generated_text": "e grazie per la vostra disponibilità!"}]
or loaded using autoclasses:
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("it5/mt5-small-formal-to-informal")
model = AutoModelForSeq2SeqLM.from_pretrained("it5/mt5-small-formal-to-informal")
If you use this model in your research, please cite our work as:
@article{sarti-nissim-2022-it5,
title={{IT5}: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation},
author={Sarti, Gabriele and Nissim, Malvina},
journal={ArXiv preprint 2203.03759},
url={https://arxiv.org/abs/2203.03759},
year={2022},
month={mar}
}
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Collection including gsarti/mt5-small-formal-to-informal
Collection
Materials for the paper "IT5:Text-to-text Pretraining for Italian Language Understanding and Generation" published at LREC/COLING 2024
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