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--- |
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language: pl |
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tags: |
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- T5 |
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- translation |
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- summarization |
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- question answering |
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- reading comprehension |
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datasets: |
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- ccnet |
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- nkjp |
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- wikipedia |
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- open subtitles |
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- free readings |
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license: cc-by-4.0 |
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--- |
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# plT5 Small |
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**plT5** models are T5-based language models trained on Polish corpora. Models were optimized for the original T5 denoising target. |
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## Corpus |
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plT5 was trained on six different corpora available for Polish language: |
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| Corpus | Tokens | Documents | |
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| :------ | ------: | ------: | |
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| [CCNet Middle](https://github.com/facebookresearch/cc_net) | 3243M | 7.9M | |
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| [CCNet Head](https://github.com/facebookresearch/cc_net) | 2641M | 7.0M | |
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| [National Corpus of Polish](http://nkjp.pl/index.php?page=14&lang=1)| 1357M | 3.9M | |
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| [Open Subtitles](http://opus.nlpl.eu/OpenSubtitles-v2018.php) | 1056M | 1.1M |
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| [Wikipedia](https://dumps.wikimedia.org/) | 260M | 1.4M | |
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| [Wolne Lektury](https://wolnelektury.pl/) | 41M | 5.5k | |
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## Tokenizer |
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The training dataset was tokenized into subwords using a sentencepiece unigram with |
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vocabulary size of 50k tokens. |
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## Usage |
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Example code: |
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```python |
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from transformers import AutoTokenizer, AutoModel |
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tokenizer = AutoTokenizer.from_pretrained("allegro/plT5-small") |
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model = AutoModel.from_pretrained("allegro/plT5-small") |
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``` |
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## License |
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CC BY 4.0 |
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## Citation |
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If you use this model, please cite the following paper: |
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``` |
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``` |
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## Authors |
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The model was trained by [**Machine Learning Research Team at Allegro**](https://ml.allegro.tech/) and [**Linguistic Engineering Group at Institute of Computer Science, Polish Academy of Sciences**](http://zil.ipipan.waw.pl/). |
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You can contact us at: <a href="mailto:[email protected]">[email protected]</a> |
