Borealis
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Borealis-5b-it
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View details ↗it-5.2-fp16-cp
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View details ↗it-5.3-fp16-32k-GGUF
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View details ↗it-5.4-fp16-orpo-v2-GGUF
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View details ↗kolibri-vikhr-mistral-0427
VikhrmodelsThis is an instruction following model (based on Vikhr Base) optimized for Russian language. It was trained using kolibrify via curriculum learning on a multitude of instruction datasets. The model uses ChatML template. It was trained to be sensitive to the system prompt, experiment with it. Primary uses: information retrieval, classification, semantic analysis, translation (en-ru), etc. Currently in pre-alpha.
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View details ↗QVikhr-2.5-1.5B-Instruct-r_GGUF
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View details ↗QVikhr-2.5-1.5B-Instruct-SMPO_GGUF
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View details ↗QVikhr-3-4B-Instruction
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View details ↗QVikhr-3-4B-Instruction-GGUF
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View details ↗QVikhr-3-8B-Instruction
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View details ↗QVikhr-3-8B-Instruction-GGUF
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View details ↗salt-116k
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View details ↗Vikhr-7B-instruct_0.3
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View details ↗Vikhr-7B-instruct_0.4
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View details ↗Vikhr-7B-instruct_0.4-GGUF
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View details ↗Vikhr-Gemma-2B-instruct
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View details ↗Vikhr-Gemma-2B-instruct-GGUF
VikhrmodelsМощная инструктивная модель на основе Gemma 2 2B, обученная на русскоязычном датасете GrandMaster-PRO-MAX.
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View details ↗Vikhr-Llama-3.2-1B-Instruct
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View details ↗Vikhr-Llama-3.2-1B-instruct-GGUF
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View details ↗Vikhr-Llama3.1-8B-Instruct-R-21-09-24
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View details ↗Vikhr-Nemo-12B-Instruct-R-21-09-24
Vikhrmodels**Vikhr-Nemo** - это наша флагманская унимодальная LLM (Large Language Model) представляющая из себя улучшенную версию mistralai/Mistral-Nemo-Instruct-2407 командой **VikhrModels**, адаптированную преимущественно для русского и английского языков. Для ее обучения мы использовали несколько этапов включающих в себя **SFT** и **SMPO** - нашу собственную вариацию DPO, подробнее читайте в секции *"Как эта модель создавалась"*. Модель оптимизированна для различных вариантов использования, включая ризонинг, суммаризацию, код, roleplay, поддержание диалога. Vikhr-Nemo обладает возможностью многоязычной генерации, и высокопроизводительными возможностями RAG. Модель иммет лучшие оценки среди прочих на наших инструктивных и RAG бенчарках и, поэтому, мы верим, что в некоторых задачах (например, RAG) может быть не хуже gpt-4o-mini от OpenAI. Весь использованный код для обучения доступен в нашем репозитории effective_llm_alignment на GitHub, а основные датасеты доступны в нашем профиле на HF.
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View details ↗Vikhr-Qwen-2.5-0.5b-Instruct
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View details ↗Vikhr-Qwen-2.5-0.5B-instruct-GGUF
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