43 lines
1.8 KiB
Markdown
43 lines
1.8 KiB
Markdown
---
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library_name: llamacpp
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model_name: Vikhr-Qwen-2.5-0.5B-instruct
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base_model:
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- Vikhrmodels/Vikhr-Qwen-2.5-0.5B-instruct
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language:
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- ru
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- en
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license: apache-2.0
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tags:
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- instruct
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datasets:
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- Vikhrmodels/GrandMaster-PRO-MAX
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pipeline_tag: text-generation
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---
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# 💨📟 Vikhr-Qwen-2.5-0.5B-Instruct
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#### RU
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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.
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#### EN
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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.
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- [HF model](https://huggingface.co/Vikhrmodels/Vikhr-Qwen-2.5-0.5B-instruct)
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**Рекомендуемая температура для генерации: 0.3** / **Recommended generation temperature: 0.3**.
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### Авторы / Authors
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- Sergei Bratchikov, [NLP Wanderer](https://t.me/nlpwanderer), [Vikhr Team](https://t.me/vikhrlabs)
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- Nikolay Kompanets, [LakoMoor](https://t.me/lakomoor), [Vikhr Team](https://t.me/vikhrlabs)
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- Konstantin Korolev, [Vikhr Team](https://t.me/vikhrlabs)
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- Aleksandr Nikolich, [Vikhr Team](https://t.me/vikhrlabs)
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```
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@article{nikolich2024vikhr,
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title={Vikhr: The Family of Open-Source Instruction-Tuned Large Language Models for Russian},
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author={Aleksandr Nikolich and Konstantin Korolev and Sergey Bratchikov and Nikolay Kompanets and Artem Shelmanov},
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journal={arXiv preprint arXiv:2405.13929},
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year={2024},
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url={https://arxiv.org/pdf/2405.13929}
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} |