---
library_name: llamacpp
model_name: Vikhr-Qwen-2.5-0.5B-instruct
base_model:
- Vikhrmodels/Vikhr-Qwen-2.5-0.5B-instruct
language:
- ru
- en
license: apache-2.0
tags:
- instruct
datasets:
- Vikhrmodels/GrandMaster-PRO-MAX
pipeline_tag: text-generation
---

# 💨📟 Vikhr-Qwen-2.5-0.5B-Instruct

#### RU

Инструктивная модель на основе **Qwen-2.5-0.5B-Instruct**, обученная на русскоязычном датасете **GrandMaster-PRO-MAX**. В **4 раза эффективнее** базовой модели, и идеально подходит для запуска на слабых мобильных устройствах.

#### EN

Instructive model based on **Qwen-2.5-0.5B-Instruct**, trained on the Russian-language dataset **GrandMaster-PRO-MAX**. It is **4 times more efficient** than the base model, making it perfect for deployment on low-end mobile devices.

- [HF model](https://huggingface.co/Vikhrmodels/Vikhr-Qwen-2.5-0.5B-instruct)

**Рекомендуемая температура для генерации: 0.3** / **Recommended generation temperature: 0.3**.

### Авторы / Authors
- Sergei Bratchikov, [NLP Wanderer](https://t.me/nlpwanderer), [Vikhr Team](https://t.me/vikhrlabs)
- Nikolay Kompanets, [LakoMoor](https://t.me/lakomoor), [Vikhr Team](https://t.me/vikhrlabs)
- Konstantin Korolev, [Vikhr Team](https://t.me/vikhrlabs)
- Aleksandr Nikolich, [Vikhr Team](https://t.me/vikhrlabs)
```
@article{nikolich2024vikhr,
  title={Vikhr: The Family of Open-Source Instruction-Tuned Large Language Models for Russian},
  author={Aleksandr Nikolich and Konstantin Korolev and Sergey Bratchikov and Nikolay Kompanets and Artem Shelmanov},
  journal={arXiv preprint arXiv:2405.13929},
  year={2024},
  url={https://arxiv.org/pdf/2405.13929}
}