Update README.md

README.md

@@ -6,16 +6,37 @@ tags:
 - text-generation-inference
 datasets:
 - s-nlp/ru_paradetox
+base_model:
+- ai-forever/ruT5-base
 ---
-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.
+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/ai-forever/ruT5-base).
 
 **How to use**
 ```python
 from transformers import T5ForConditionalGeneration, AutoTokenizer
 
-base_model_name = 'sberbank-ai/ruT5-base'
-model_name = 'SkolkovoInstitute/ruT5-base-detox'
+base_model_name = 'ai-forever/ruT5-base'
+model_name = 's-nlp/ruT5-base-detox'
 
 tokenizer = AutoTokenizer.from_pretrained(base_model_name)
 model = T5ForConditionalGeneration.from_pretrained(model_name)
-```
+
+input_ids = tokenizer.encode('Это полная хуйня!', return_tensors='pt')
+output_ids = model.generate(input_ids, max_length=50, num_return_sequences=1)
+output_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
+print(output_text)
+# Это полный бред!
+```
+
+## Citation
+
+```
+@article{dementievarusse,
+  title={RUSSE-2022: Findings of the First Russian Detoxification Shared Task Based on Parallel Corpora},
+  author={Dementieva, Daryna and Logacheva, Varvara and Nikishina, Irina and Fenogenova, Alena and Dale, David and Krotova, Irina and Semenov, Nikita and Shavrina, Tatiana and Panchenko, Alexander}
+}
+```
+
+**License**
+
+This model is licensed under the OpenRAIL++ License, which supports the development of various technologies—both industrial and academic—that serve the public good.