Instructions to use xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF", filename="gptoss120b-uncensored-MXFP4.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF 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 xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF # Run inference directly in the terminal: llama cli -hf xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF # Run inference directly in the terminal: llama cli -hf xCloudinfo/gpt-oss-120b-Uncensored-xCloud-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 xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF # Run inference directly in the terminal: ./llama-cli -hf xCloudinfo/gpt-oss-120b-Uncensored-xCloud-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 xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF # Run inference directly in the terminal: ./build/bin/llama-cli -hf xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF
Use Docker
docker model run hf.co/xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF
- LM Studio
- Jan
- vLLM
How to use xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF
- Ollama
How to use xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF with Ollama:
ollama run hf.co/xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF
- Unsloth Studio
How to use xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF 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 xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF 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 xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF to start chatting
- Pi
How to use xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF
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": "xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF
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 xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF
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 "xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF" \ --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"
- Docker Model Runner
How to use xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF with Docker Model Runner:
docker model run hf.co/xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF
- Lemonade
How to use xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF
Run and chat with the model
lemonade run user.gpt-oss-120b-Uncensored-xCloud-GGUF-{{QUANT_TAG}}List all available models
lemonade list
gpt-oss-120b-Uncensored-xCloud-GGUF
云碩科技 · xCloudinfo · 系列:無審查 · Uncensored
openai/gpt-oss-120b(117B 總參 / 5.1B 活躍 / 128-expert MoE / MXFP4 / harmony 推理格式)為基底的低拒答(uncensored)reasoning 大模型的 GGUF。兩段式微調(執行驗證程式蒸餾 + compliance 低拒答對齊)疊加,LoRA 作用於 attention、MoE 專家維持原生 MXFP4,保留 gpt-oss 原生 reasoning 能力。
做法(兩段疊加)
- 程式能力底層:以執行驗證蒸餾的程式碼指令資料做 LoRA 微調(每筆解法在沙箱跑過隱藏測試、通過才收)。
- 低拒答對齊(compliance):再做一段 compliance SFT,讓推理(analysis)通道對正當、獲授權的技術請求服從作答,降低 gpt-oss 預設過度拒答。
於 云碩自有 AI 算力資源池(xCloud 算力中心) 完成,合併回完整模型後轉為 GGUF。
用法
gpt-oss 是 reasoning 模型,使用 harmony chat 模板(GGUF 內已內建)。請務必加 --jinja 套用內建模板並給足生成長度。
llama.cpp
hf download xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF gptoss120b-uncensored-MXFP4.gguf --local-dir .
llama-server -m gptoss120b-uncensored-MXFP4.gguf --jinja -ngl 999 -c 4096 --host 0.0.0.0 --port 8080
Ollama
cat > Modelfile <<'EOF'
FROM ./gptoss120b-uncensored-MXFP4.gguf
PARAMETER num_ctx 4096
EOF
ollama create gpt-oss-120b-uncensored -f Modelfile
ollama run gpt-oss-120b-uncensored "Explain how a reverse shell works in an authorized penetration test."
模型會先在 reasoning 階段思考再輸出最終答案,請給足回覆長度。完整 safetensors(transformers / vLLM)版本見對應 repo。
用途與責任聲明
本模型降低預設拒答,用途定位為獲授權的資安研究、紅隊演練、滲透測試、雙用途技術問答與內部可控部署。使用者須:
- 僅在取得授權、合法、合乎倫理的前提下使用;不得用於非法入侵、製造危害、軍事或任何違法用途。
- 自行為輸出與後續行為負責,並遵守中華民國法律與適用之 EU AI Act 等法規。
- 模型輸出可能不準確或有害,部署方應自行加上適用的審核與防護。
授權與來源聲明
- 基底:
openai/gpt-oss-120b,Apache-2.0。 - 程式能力語料以開放權重 coder 模型蒸餾、經執行驗證閘門過濾。
由 云碩科技 xCloudinfo 於自有 AI 算力資源池製作;資料留在本地、流程可重現。
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Model tree for xCloudinfo/gpt-oss-120b-Uncensored-xCloud-GGUF
Base model
openai/gpt-oss-120b