| This is the detoxification baseline model trained on the [train](https://github.com/skoltech-nlp/russe_detox_2022/blob/main/data/input/train.tsv) part of "RUSSE 2022: Russian Text Detoxification Based on Parallel Corpora" competition. The source sentences are Russian toxic messages from Odnoklassniki, Pikabu, and Twitter platforms. The base model is [ruT5](https://huggingface.co/sberbank-ai/ruT5-base) provided from Sber. | |
| **How to use** | |
| ```python | |
| from transformers import T5ForConditionalGeneration, AutoTokenizer | |
| base_model_name = 'sberbank-ai/ruT5-base' | |
| model_name = 'SkolkovoInstitute/ruT5-base-detox' | |
| tokenizer = AutoTokenizer.from_pretrained(base_model_name) | |
| model = T5ForConditionalGeneration.from_pretrained(model_name) | |
| ``` | |
| ## Licensing Information | |
| [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License][cc-by-nc-sa]. | |
| [![CC BY-NC-SA 4.0][cc-by-nc-sa-image]][cc-by-nc-sa] | |
| [cc-by-nc-sa]: http://creativecommons.org/licenses/by-nc-sa/4.0/ | |
| [cc-by-nc-sa-image]: https://i.creativecommons.org/l/by-nc-sa/4.0/88x31.png |