Vikhrmodels / QVikhr-3-4B-Instruction-GGUF

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Introduction of QVikhr-3-4B-Instruction-GGUF

Model Details of QVikhr-3-4B-Instruction-GGUF

QVikhr-3-4B-Instruction

RU

Инструктивная модель на основе Qwen/Qwen3-4B , обученная на русскоязычном датасете GrandMaster2 . Создана для высокоэффективной обработки текстов на русском и английском языках, обеспечивая точные ответы и быстрое выполнение задач.

EN

Instructive model based on Qwen/Qwen3-4B , trained on the Russian-language dataset GrandMaster2 . Designed for high-efficiency text processing in Russian and English, delivering precise responses and fast task execution.

Как цитировать / How to Cite
@inproceedings{nikolich2024vikhr,
  title={Vikhr: Advancing Open-Source Bilingual Instruction-Following Large Language Models for Russian and English},
  author={Aleksandr Nikolich and Konstantin Korolev and Sergei Bratchikov and Nikolay Kompanets and Igor Kiselev and Artem Shelmanov},
  booktitle={Proceedings of the 4th Workshop on Multilingual Representation Learning (MRL) @ EMNLP-2024},
  year={2024},
  publisher={Association for Computational Linguistics},
  url={[https://arxiv.org/pdf/2405.13929](https://arxiv.org/pdf/2405.13929)}
}

@misc{qwen3technicalreport,
      title={Qwen3 Technical Report}, 
      author={Qwen Team},
      year={2025},
      eprint={2505.09388},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2505.09388}, 
}

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526
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0
24-hour runs
0
3-day runs
109
7-day runs
-127
30-day runs

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