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Vistral-24B-Instruct-GGUF

GGUF
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llama.cpp
imatrix
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How to use from
llama.cpp
Install from brew 
brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Vikhrmodels/Vistral-24B-Instruct-GGUF:
# Run inference directly in the terminal:
llama-cli -hf Vikhrmodels/Vistral-24B-Instruct-GGUF:
Install from WinGet (Windows) 
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Vikhrmodels/Vistral-24B-Instruct-GGUF:
# Run inference directly in the terminal:
llama-cli -hf Vikhrmodels/Vistral-24B-Instruct-GGUF:
Use pre-built binary 
# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf Vikhrmodels/Vistral-24B-Instruct-GGUF:
# Run inference directly in the terminal:
./llama-cli -hf Vikhrmodels/Vistral-24B-Instruct-GGUF:
Build from source code 
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf Vikhrmodels/Vistral-24B-Instruct-GGUF:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Vikhrmodels/Vistral-24B-Instruct-GGUF:
Use Docker 
docker model run hf.co/Vikhrmodels/Vistral-24B-Instruct-GGUF:
Quick Links

Vistral-24B-Instruct

Описание

Vistral - это наша новая флагманская унимодальная LLM (Large Language Model) представляющая из себя улучшенную версию mistralai/Mistral-Small-3.2-24B-Instruct-2506 командой VikhrModels, адаптированную преимущественно для русского и английского языков. Удалён визуальный энкодер, убрана мультимодальность. Сохранена стандартная архитектура "MistralForCausalLM" без изменений в базовой структуре модели.

Весь использованный код для обучения доступен в нашем репозитории effective_llm_alignment на GitHub, а основные датасеты доступны в нашем профиле на HF.

Модель доступна на нашем сайте Chat Vikhr

@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}
}
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llama
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mistralai/Mistral-Small-3.1-24B-Base-2503
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Paper for Vikhrmodels/Vistral-24B-Instruct-GGUF