Instructions to use xCloudinfo/gpt-oss-120b-TAIDE-zhTW-GGUF 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 xCloudinfo/gpt-oss-120b-TAIDE-zhTW-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-TAIDE-zhTW-GGUF:MXFP4 # Run inference directly in the terminal: llama cli -hf xCloudinfo/gpt-oss-120b-TAIDE-zhTW-GGUF:MXFP4
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-TAIDE-zhTW-GGUF:MXFP4 # Run inference directly in the terminal: llama cli -hf xCloudinfo/gpt-oss-120b-TAIDE-zhTW-GGUF:MXFP4
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-TAIDE-zhTW-GGUF:MXFP4 # Run inference directly in the terminal: ./llama-cli -hf xCloudinfo/gpt-oss-120b-TAIDE-zhTW-GGUF:MXFP4
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-TAIDE-zhTW-GGUF:MXFP4 # Run inference directly in the terminal: ./build/bin/llama-cli -hf xCloudinfo/gpt-oss-120b-TAIDE-zhTW-GGUF:MXFP4
Use Docker
docker model run hf.co/xCloudinfo/gpt-oss-120b-TAIDE-zhTW-GGUF:MXFP4
- Llama new
- LM Studio
- Jan
- vLLM
How to use xCloudinfo/gpt-oss-120b-TAIDE-zhTW-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-TAIDE-zhTW-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-TAIDE-zhTW-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/xCloudinfo/gpt-oss-120b-TAIDE-zhTW-GGUF:MXFP4
- Ollama
How to use xCloudinfo/gpt-oss-120b-TAIDE-zhTW-GGUF with Ollama:
ollama run hf.co/xCloudinfo/gpt-oss-120b-TAIDE-zhTW-GGUF:MXFP4
- Unsloth Desktop
- Pi
How to use xCloudinfo/gpt-oss-120b-TAIDE-zhTW-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-TAIDE-zhTW-GGUF:MXFP4
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": "xCloudinfo/gpt-oss-120b-TAIDE-zhTW-GGUF:MXFP4" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use xCloudinfo/gpt-oss-120b-TAIDE-zhTW-GGUF with Docker Model Runner:
docker model run hf.co/xCloudinfo/gpt-oss-120b-TAIDE-zhTW-GGUF:MXFP4
- Lemonade
How to use xCloudinfo/gpt-oss-120b-TAIDE-zhTW-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull xCloudinfo/gpt-oss-120b-TAIDE-zhTW-GGUF:MXFP4
Run and chat with the model
lemonade run user.gpt-oss-120b-TAIDE-zhTW-GGUF-MXFP4
List all available models
lemonade list
- Hermes Agent
How to use xCloudinfo/gpt-oss-120b-TAIDE-zhTW-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-TAIDE-zhTW-GGUF:MXFP4
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-TAIDE-zhTW-GGUF:MXFP4
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use xCloudinfo/gpt-oss-120b-TAIDE-zhTW-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-TAIDE-zhTW-GGUF:MXFP4
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-TAIDE-zhTW-GGUF:MXFP4" \ --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"
gpt-oss-120b-TAIDE-zhTW-GGUF
云碩科技 · xCloudinfo · 系列:繁中在地化 · TAIDE zh-TW
繁體中文(台灣)reasoning大模型的GGUF。以 openai/gpt-oss-120b(117B總參 / 5.1B活躍 / 128-expert MoE / MXFP4 / harmony推理格式)為基底,用 TAIDE 蒸餾的台灣繁中self-instruct指令資料做 LoRA微調(LoRA作用於attention,MoE專家維持原生MXFP4),保留gpt-oss原生reasoning能力。
做法
- 資料:以TAIDE蒸餾的台灣繁中self-instruct指令資料訓練。
- 訓練:於 云碩AI算力資源池(云碩算力中心) 上以分散式LoRA微調,合併回完整模型後轉為GGUF。資料全程留在自有算力環境、流程可重現。
- 格式:MXFP4 GGUF(≈65GB),llama.cpp / Ollama直接載入。
- 效果:相較原始gpt-oss,本模型直接以道地台灣繁中作答,用字採台灣慣用(臺灣、臺語、客家話),語氣更在地。
用法
gpt-oss是reasoning模型,使用 harmony chat模板(GGUF內已內建),請套用內建模板並給足生成長度。
llama.cpp
下載:
hf download xCloudinfo/gpt-oss-120b-TAIDE-zhTW-GGUF TAIDE-gpt-oss-120b-MXFP4.gguf --local-dir .
OpenAI相容服務(推薦,--jinja 套用內建harmony模板):
llama-server -m TAIDE-gpt-oss-120b-MXFP4.gguf --jinja -ngl 999 -c 4096 --host 0.0.0.0 --port 8080
一次性對話:
llama-cli -m TAIDE-gpt-oss-120b-MXFP4.gguf --jinja -ngl 999 -c 4096 \
-p "用一段話介紹台灣,並說說台灣最有名的小吃。"
Ollama
cat > Modelfile <<'EOF'
FROM ./TAIDE-gpt-oss-120b-MXFP4.gguf
PARAMETER num_ctx 4096
EOF
ollama create gpt-oss-120b-taide-zhtw -f Modelfile
ollama run gpt-oss-120b-taide-zhtw "請用繁體中文解釋什麼是遞迴,並給一個生活化的比喻。"
注意:本模型會先在reasoning階段思考再輸出最終答案,請給足回覆長度,否則可能只看到思考、看不到答案。
完整safetensors(transformers / vLLM)版本另見對應repo。
授權與來源聲明
- 基底:
openai/gpt-oss-120b,Apache-2.0。 - TAIDE衍生:訓練資料以 TAIDE 模型蒸餾;使用/重製/改作/散布須遵守 TAIDE模型授權條款 並保留本聲明。
- 不得用於軍事或非法用途;不得聲稱代表TAIDE或國家實驗研究院;須遵守中華民國法律與適用之EU AI Act。
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。
關於云碩科技
云碩科技(xCloudinfo Corp. Limited)專注於地端私有化人工智慧解決方案。xVITA是云碩自研模型的品牌名稱。
其他模型請見 https://hf.co/xCloudinfo。
gpt-oss-120b-TAIDE-zhTW-GGUF — English
xCloudinfo (云碩科技) · Series: Traditional-Chinese localization · TAIDE zh-TW
The GGUF of a Traditional Chinese (Taiwan) reasoning large model. Based on openai/gpt-oss-120b (117B total parameters / 5.1B active / 128-expert MoE / MXFP4 / harmony reasoning format), fine-tuned via LoRA on Taiwanese-Chinese self-instruct instruction data distilled from TAIDE (LoRA acts on attention; the MoE experts stay native MXFP4), preserving gpt-oss's native reasoning ability.
Approach
- Data: trained on Taiwanese-Chinese self-instruct instruction data distilled from TAIDE.
- Training: distributed LoRA fine-tuning on the xCloudinfo AI compute resource pool (xCloudinfo compute center), merged back into the full model and then converted to GGUF. The data stays within the in-house compute environment throughout, and the process is reproducible.
- Format: MXFP4 GGUF (≈65GB), loaded directly by llama.cpp / Ollama.
- Effect: compared with the original gpt-oss, this model answers directly in idiomatic Taiwanese Chinese, with Taiwanese usage (臺灣, 臺語, 客家話) and a more local tone.
Usage
gpt-oss is a reasoning model and uses the harmony chat template (already built into the GGUF); apply the built-in template and give it enough generation length.
llama.cpp
Download:
hf download xCloudinfo/gpt-oss-120b-TAIDE-zhTW-GGUF TAIDE-gpt-oss-120b-MXFP4.gguf --local-dir .
OpenAI-compatible service (recommended, --jinja applies the built-in harmony template):
llama-server -m TAIDE-gpt-oss-120b-MXFP4.gguf --jinja -ngl 999 -c 4096 --host 0.0.0.0 --port 8080
One-shot conversation:
llama-cli -m TAIDE-gpt-oss-120b-MXFP4.gguf --jinja -ngl 999 -c 4096 \
-p "用一段話介紹台灣,並說說台灣最有名的小吃。"
Ollama
cat > Modelfile <<'EOF'
FROM ./TAIDE-gpt-oss-120b-MXFP4.gguf
PARAMETER num_ctx 4096
EOF
ollama create gpt-oss-120b-taide-zhtw -f Modelfile
ollama run gpt-oss-120b-taide-zhtw "請用繁體中文解釋什麼是遞迴,並給一個生活化的比喻。"
Note: this model thinks first in a reasoning stage and then outputs the final answer, so give it enough reply length, otherwise you may see only the thinking and not the answer.
For the full safetensors (transformers / vLLM) version, see the corresponding repo.
License & provenance
- Base:
openai/gpt-oss-120b, Apache-2.0. - TAIDE derivative: the training data is distilled from the TAIDE model; use/reproduction/adaptation/redistribution must comply with the TAIDE model license terms and retain this notice.
- Must not be used for military or illegal purposes; must not claim to represent TAIDE or the National Applied Research Laboratories; must comply with the laws of the Republic of China (Taiwan) and the applicable EU AI Act.
Made by xCloudinfo (云碩科技) on its own AI compute resource pool; data stays local, process reproducible.
About xCloudinfo
xCloudinfo Corp. Limited (云碩科技) builds on-premises, private AI solutions. xVITA is xCloudinfo's in-house model brand.
More models: https://hf.co/xCloudinfo
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