How to use from
llama.cpp
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf twirlz/SICS-1-35B:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf twirlz/SICS-1-35B:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf twirlz/SICS-1-35B:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf twirlz/SICS-1-35B:Q4_K_M
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 twirlz/SICS-1-35B:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf twirlz/SICS-1-35B:Q4_K_M
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 twirlz/SICS-1-35B:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf twirlz/SICS-1-35B:Q4_K_M
Use Docker
docker model run hf.co/twirlz/SICS-1-35B:Q4_K_M
Quick Links

SICS-1-35B (GGUF)

Локальная модель для генерации и валидации проверяемых исследовательских гипотез (проект «Фабрика гипотез», хакатон «Норникель»). База — Qwen3.6-35B-A3B (MoE, 3B активных на токен), дообучена через PPO под идеацию и автономный ресёрч. Формат GGUF Q4_K_M (21 ГБ) для локального инференса через llama.cpp.

Запуск

llama-server -m SICS-1-35B.Q4_K_M.gguf --host 0.0.0.0 --port 8080 \
  --jinja --reasoning-format auto -c 32768 -ngl 99
Downloads last month
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GGUF
Model size
35B params
Architecture
qwen35moe
Hardware compatibility
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4-bit

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