Text Generation
GGUF
Chinese
English
llama.cpp
reasoning
bounded-thinking
ternary
q2_0
llama-cpp
lm-studio
experimental
conversational
Instructions to use Vita0818/Vireqo-27T-Plus-260818 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Vita0818/Vireqo-27T-Plus-260818 with 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 Vita0818/Vireqo-27T-Plus-260818 # Run inference directly in the terminal: llama cli -hf Vita0818/Vireqo-27T-Plus-260818
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Vita0818/Vireqo-27T-Plus-260818 # Run inference directly in the terminal: llama cli -hf Vita0818/Vireqo-27T-Plus-260818
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 Vita0818/Vireqo-27T-Plus-260818 # Run inference directly in the terminal: ./llama-cli -hf Vita0818/Vireqo-27T-Plus-260818
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 Vita0818/Vireqo-27T-Plus-260818 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Vita0818/Vireqo-27T-Plus-260818
Use Docker
docker model run hf.co/Vita0818/Vireqo-27T-Plus-260818
- LM Studio
- Jan
- vLLM
How to use Vita0818/Vireqo-27T-Plus-260818 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Vita0818/Vireqo-27T-Plus-260818" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Vita0818/Vireqo-27T-Plus-260818", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Vita0818/Vireqo-27T-Plus-260818
- Ollama
How to use Vita0818/Vireqo-27T-Plus-260818 with Ollama:
ollama run hf.co/Vita0818/Vireqo-27T-Plus-260818
- Unsloth Desktop
- Pi
How to use Vita0818/Vireqo-27T-Plus-260818 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Vita0818/Vireqo-27T-Plus-260818
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "Vita0818/Vireqo-27T-Plus-260818" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use Vita0818/Vireqo-27T-Plus-260818 with Docker Model Runner:
docker model run hf.co/Vita0818/Vireqo-27T-Plus-260818
- Lemonade
How to use Vita0818/Vireqo-27T-Plus-260818 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Vita0818/Vireqo-27T-Plus-260818
Run and chat with the model
lemonade run user.Vireqo-27T-Plus-260818-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use Vita0818/Vireqo-27T-Plus-260818 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Vita0818/Vireqo-27T-Plus-260818
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 Vita0818/Vireqo-27T-Plus-260818
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use Vita0818/Vireqo-27T-Plus-260818 with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Vita0818/Vireqo-27T-Plus-260818
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "Vita0818/Vireqo-27T-Plus-260818" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
File size: 674 Bytes
6254961 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | Vireqo-27T-Plus-260818 is an independent, unofficial experimental bounded-
Thinking configuration bundle. It reuses Vireqo-27B-Plus-260816 byte-for-byte
and adds no trained or modified tensor. Product differentiation is supplied by
the tested LM Studio Think512-Concise configuration.
The underlying artifact derives from Qwen3.8-27B and Ternary-Bonsai-27B.
Qwen3.8-27B is Copyright 2026 Alibaba Cloud. Bonsai is Copyright 2026-present
Prism ML, Inc. Both pinned upstream sources were distributed under Apache
License 2.0. Retained attribution: Created using Bonsai by Prism ML.
No affiliation with or endorsement from Alibaba Cloud, Qwen, Prism ML, or
Bonsai is claimed.
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