
# IT5 Small for Formal-to-informal Style Transfer 🤗

This repository contains the checkpoint for the [IT5 Small](https://huggingface.co/gsarti/it5-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](https://arxiv.org/abs/2203.03759) by [Gabriele Sarti](https://gsarti.com) and [Malvina Nissim](https://malvinanissim.github.io).  

A comprehensive overview of other released materials is provided in the [gsarti/it5](https://github.com/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:

```python
from transformers import pipelines

f2i = pipeline("text2text-generation", model='it5/it5-small-formal-to-informal')
f2i("Vi ringrazio infinitamente per vostra disponibilità")
>>> [{"generated_text": "e grazie per la vostra disponibilità!"}]
```

or loaded using autoclasses:

```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("it5/it5-small-formal-to-informal")
model = AutoModelForSeq2SeqLM.from_pretrained("it5/it5-small-formal-to-informal")
```

If you use this model in your research, please cite our work as:

```bibtex
@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}
}
```
{"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "style-transfer", "formality-style-transfer"], "datasets": ["yahoo/xformal_it"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "Questa performance \u00e8 a dir poco spiacevole."}, {"text": "In attesa di un Suo cortese riscontro, Le auguriamo un piacevole proseguimento di giornata."}, {"text": "Questa visione mi procura una goduria indescrivibile."}, {"text": "qualora ci\u00f2 possa interessarti, ti pregherei di contattarmi."}], "co2_eq_emissions": {"emissions": "8g", "source": "Google Cloud Platform Carbon Footprint", "training_type": "fine-tuning", "geographical_location": "Eemshaven, Netherlands, Europe", "hardware_used": "1 TPU v3-8 VM"}, "model-index": [{"name": "it5-small-formal-to-informal", "results": [{"task": {"type": "formality-style-transfer", "name": "Formal-to-informal Style Transfer"}, "dataset": {"name": "XFORMAL (Italian Subset)", "type": "xformal_it"}, "metrics": [{"type": "rouge1", "value": 0.65, "name": "Avg. Test Rouge1"}, {"type": "rouge2", "value": 0.45, "name": "Avg. Test Rouge2"}, {"type": "rougeL", "value": 0.631, "name": "Avg. Test RougeL"}, {"type": "bertscore", "value": 0.663, "name": "Avg. Test BERTScore", "args": [{"model_type": "dbmdz/bert-base-italian-xxl-uncased"}, {"lang": "it"}, {"num_layers": 10}, {"rescale_with_baseline": true}, {"baseline_path": "bertscore_baseline_ita.tsv"}]}]}]}]}
transformers pytorch tf jax t5 text2text-generation italian sequence-to-sequence style-transfer formality-style-transfer it dataset:yahoo/xformal_it arxiv:2203.03759 license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tf #jax #t5 #text2text-generation #italian #sequence-to-sequence #style-transfer #formality-style-transfer #it #dataset-yahoo/xformal_it #arxiv-2203.03759 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 


# IT5 Small for Formal-to-informal Style Transfer 

This repository contains the checkpoint for the IT5 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:



or loaded using autoclasses:



If you use this model in your research, please cite our work as:


# IT5 Small for Formal-to-informal Style Transfer 

This repository contains the checkpoint for the IT5 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:



or loaded using autoclasses:



If you use this model in your research, please cite our work as:
TAGS
#transformers #pytorch #tf #jax #t5 #text2text-generation #italian #sequence-to-sequence #style-transfer #formality-style-transfer #it #dataset-yahoo/xformal_it #arxiv-2203.03759 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # IT5 Small for Formal-to-informal Style Transfer 

This repository contains the checkpoint for the IT5 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:



or loaded using autoclasses:



If you use this model in your research, please cite our work as:
passage: TAGS
#transformers #pytorch #tf #jax #t5 #text2text-generation #italian #sequence-to-sequence #style-transfer #formality-style-transfer #it #dataset-yahoo/xformal_it #arxiv-2203.03759 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# IT5 Small for Formal-to-informal Style Transfer 

This repository contains the checkpoint for the IT5 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:



or loaded using autoclasses:



If you use this model in your research, please cite our work as: