allegro/plt5-base

Model

plT5 Base

8

7 commits

2 linked in READMEs

updated Aug 3, 2022

See the code

README

plT5 Base

plT5 models are T5-based language models trained on Polish corpora. The models were optimized for the original T5 denoising target.

Corpus

plT5 was trained on six different corpora available for Polish language:

CorpusTokensDocuments
CCNet Middle3243M7.9M
CCNet Head2641M7.0M
National Corpus of Polish1357M3.9M
Open Subtitles1056M1.1M
Wikipedia260M1.4M
Wolne Lektury41M5.5k

Tokenizer

The training dataset was tokenized into subwords using a sentencepiece unigram model with vocabulary size of 50k tokens.

Usage

Example code:

from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("allegro/plt5-base")
model = AutoModel.from_pretrained("allegro/plt5-base")

License

CC BY 4.0

Citation

If you use this model, please cite the following paper:

@article{chrabrowa2022evaluation,
  title={Evaluation of Transfer Learning for Polish with a Text-to-Text Model},
  author={Chrabrowa, Aleksandra and Dragan, {\L}ukasz and Grzegorczyk, Karol and Kajtoch, Dariusz and Koszowski, Miko{\l}aj and Mroczkowski, Robert and Rybak, Piotr},
  journal={arXiv preprint arXiv:2205.08808},
  year={2022}
}

Authors

The model was trained by Machine Learning Research Team at Allegro and Linguistic Engineering Group at Institute of Computer Science, Polish Academy of Sciences.

You can contact us at: klejbenchmark@allegro.pl

endpoints_compatible
pytorch
question answering
reading comprehension
summarization
t5
T5
text2text-generation
text-generation-inference
transformers
translation

Contributors

rmroczkowski

5 commits

piotr-rybak

1 commits

system

1 commits

allegro/plt5-base

Model

plT5 Base

8

7 commits

2 linked in READMEs

updated Aug 3, 2022

See the code

README

plT5 Base

plT5 models are T5-based language models trained on Polish corpora. The models were optimized for the original T5 denoising target.

Corpus

plT5 was trained on six different corpora available for Polish language:

CorpusTokensDocuments
CCNet Middle3243M7.9M
CCNet Head2641M7.0M
National Corpus of Polish1357M3.9M
Open Subtitles1056M1.1M
Wikipedia260M1.4M
Wolne Lektury41M5.5k

Tokenizer

The training dataset was tokenized into subwords using a sentencepiece unigram model with vocabulary size of 50k tokens.

Usage

Example code:

from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("allegro/plt5-base")
model = AutoModel.from_pretrained("allegro/plt5-base")

License

CC BY 4.0

Citation

If you use this model, please cite the following paper:

@article{chrabrowa2022evaluation,
  title={Evaluation of Transfer Learning for Polish with a Text-to-Text Model},
  author={Chrabrowa, Aleksandra and Dragan, {\L}ukasz and Grzegorczyk, Karol and Kajtoch, Dariusz and Koszowski, Miko{\l}aj and Mroczkowski, Robert and Rybak, Piotr},
  journal={arXiv preprint arXiv:2205.08808},
  year={2022}
}

Authors

The model was trained by Machine Learning Research Team at Allegro and Linguistic Engineering Group at Institute of Computer Science, Polish Academy of Sciences.

You can contact us at: klejbenchmark@allegro.pl

endpoints_compatible
pytorch
question answering
reading comprehension
summarization
t5
T5
text2text-generation
text-generation-inference
transformers
translation

Contributors

rmroczkowski

5 commits

piotr-rybak

1 commits

system

1 commits