Instructions to use goldevgeny/antirk-9b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use goldevgeny/antirk-9b with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="goldevgeny/antirk-9b", filename="antirk-9b-q5_k_m.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use goldevgeny/antirk-9b with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf goldevgeny/antirk-9b:Q5_K_M # Run inference directly in the terminal: llama-cli -hf goldevgeny/antirk-9b:Q5_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf goldevgeny/antirk-9b:Q5_K_M # Run inference directly in the terminal: llama-cli -hf goldevgeny/antirk-9b:Q5_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 goldevgeny/antirk-9b:Q5_K_M # Run inference directly in the terminal: ./llama-cli -hf goldevgeny/antirk-9b:Q5_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 goldevgeny/antirk-9b:Q5_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf goldevgeny/antirk-9b:Q5_K_M
Use Docker
docker model run hf.co/goldevgeny/antirk-9b:Q5_K_M
- LM Studio
- Jan
- Ollama
How to use goldevgeny/antirk-9b with Ollama:
ollama run hf.co/goldevgeny/antirk-9b:Q5_K_M
- Unsloth Studio
How to use goldevgeny/antirk-9b with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for goldevgeny/antirk-9b to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for goldevgeny/antirk-9b to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for goldevgeny/antirk-9b to start chatting
- Pi
How to use goldevgeny/antirk-9b with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf goldevgeny/antirk-9b:Q5_K_M
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "goldevgeny/antirk-9b:Q5_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use goldevgeny/antirk-9b with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf goldevgeny/antirk-9b:Q5_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default goldevgeny/antirk-9b:Q5_K_M
Run Hermes
hermes
- Docker Model Runner
How to use goldevgeny/antirk-9b with Docker Model Runner:
docker model run hf.co/goldevgeny/antirk-9b:Q5_K_M
- Lemonade
How to use goldevgeny/antirk-9b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull goldevgeny/antirk-9b:Q5_K_M
Run and chat with the model
lemonade run user.antirk-9b-Q5_K_M
List all available models
lemonade list
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf goldevgeny/antirk-9b:Q5_K_M# Run inference directly in the terminal:
llama-cli -hf goldevgeny/antirk-9b:Q5_K_MUse 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 goldevgeny/antirk-9b:Q5_K_M# Run inference directly in the terminal:
./llama-cli -hf goldevgeny/antirk-9b:Q5_K_MBuild 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 goldevgeny/antirk-9b:Q5_K_M# Run inference directly in the terminal:
./build/bin/llama-cli -hf goldevgeny/antirk-9b:Q5_K_MUse Docker
docker model run hf.co/goldevgeny/antirk-9b:Q5_K_MAntiRK-9B
Дообученная Qwen3.5-9B — эксперт по сетевым протоколам, Xray/XTLS, Reality, Hysteria2 и обходу интернет-цензуры (DPI/ТСПУ).
Что знает
- Сетевые протоколы: TCP, UDP, QUIC, TLS 1.2/1.3, HTTP/2, HTTP/3, DNS (на базе RFC)
- Xray/XTLS: VLESS, Reality, XHTTP, gRPC, WebSocket, fallback, routing, sniffing
- Hysteria2: QUIC, Salamander обфускация, Brutal congestion control
- DPI и обход: active probing, TLS fingerprinting (JA3/JA4), методы маскировки
Обучена на 5687 примерах (RFC, документация Xray/Hysteria, GitHub issues) + Q&A на русском, английском, китайском.
Файлы
antirk-9b-q5_k_m.gguf— квантизованная модель для llama.cpp / LM Studio (~6 GB)lora-adapter/— LoRA адаптер (для дообучения поверх базовой Qwen3.5-9B)
Запуск (llama.cpp / LM Studio)
Перетащи antirk-9b-q5_k_m.gguf в LM Studio, или:
llama-server -m antirk-9b-q5_k_m.gguf -ngl 99 --port 1234
Требуется свежая версия llama.cpp/LM Studio с поддержкой архитектуры qwen35.
Системный промпт
Ты — AntiRK, эксперт по сетевым протоколам, настройке Xray/XTLS, Hysteria2
и обходу интернет-цензуры.
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Install from brew
# Start a local OpenAI-compatible server with a web UI: llama-server -hf goldevgeny/antirk-9b:Q5_K_M# Run inference directly in the terminal: llama-cli -hf goldevgeny/antirk-9b:Q5_K_M