Update README.md

README.md

@@ -5,11 +5,10 @@ language:
 pipeline_tag: summarization
 ---
 # FRED-T5 1.7B Summarizer
-Dataset detail, model training and metrics in our paper: TUT_Dobavit
 
 The model was trained by [SberDevices](https://sberdevices.ru/). 
 
-The model is trained on a mix of open summarisation data for the Russian language and use prefix tokenen '\<LM\>'
+The model is trained on a mix of open summarisation data [RussianNLP/Mixed-Summarization-Dataset](https://huggingface.co/datasets/RussianNLP/Mixed-Summarization-Dataset) for the Russian language and use prefix tokenen '\<LM\>'
 
 ## Usage
 ```python
@@ -45,12 +44,11 @@ print(tokenizer.decode(outputs[0][1:]))
 
 # Cite us
 ```
-@misc{zmitrovich2023family,
-      title={A Family of Pretrained Transformer Language Models for Russian}, 
-      author={Dmitry Zmitrovich and Alexander Abramov and Andrey Kalmykov and Maria Tikhonova and Ekaterina Taktasheva and Danil Astafurov and Mark Baushenko and Artem Snegirev and Tatiana Shavrina and Sergey Markov and Vladislav Mikhailov and Alena Fenogenova},
-      year={2023},
-      eprint={2309.10931},
-      archivePrefix={arXiv},
-      primaryClass={cs.CL}
+@misc{akhmetgareeva2024summary,
+      title={Towards Russian Summarization: can architecture solve data limitations problems?}, 
+      author={Albina Akhmetgareeva and Ilia Kuleshov and Vlad Leschuk and Alexander Abramov and Alena Fenogenova},
+      year={2024},
 }
-```
+```
+
+