Instructions to use netease-youdao/Confucius4-T3PO-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 netease-youdao/Confucius4-T3PO-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 netease-youdao/Confucius4-T3PO-GGUF:F16 # Run inference directly in the terminal: llama cli -hf netease-youdao/Confucius4-T3PO-GGUF:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf netease-youdao/Confucius4-T3PO-GGUF:F16 # Run inference directly in the terminal: llama cli -hf netease-youdao/Confucius4-T3PO-GGUF:F16
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 netease-youdao/Confucius4-T3PO-GGUF:F16 # Run inference directly in the terminal: ./llama-cli -hf netease-youdao/Confucius4-T3PO-GGUF:F16
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 netease-youdao/Confucius4-T3PO-GGUF:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf netease-youdao/Confucius4-T3PO-GGUF:F16
Use Docker
docker model run hf.co/netease-youdao/Confucius4-T3PO-GGUF:F16
- LM Studio
- Jan
- Ollama
How to use netease-youdao/Confucius4-T3PO-GGUF with Ollama:
ollama run hf.co/netease-youdao/Confucius4-T3PO-GGUF:F16
- Unsloth Desktop
- Docker Model Runner
How to use netease-youdao/Confucius4-T3PO-GGUF with Docker Model Runner:
docker model run hf.co/netease-youdao/Confucius4-T3PO-GGUF:F16
- Lemonade
How to use netease-youdao/Confucius4-T3PO-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull netease-youdao/Confucius4-T3PO-GGUF:F16
Run and chat with the model
lemonade run user.Confucius4-T3PO-GGUF-F16
List all available models
lemonade list
- Atomic Chat
Confucius4-T3PO: simulTaneous Translation via pareTo Policy Optimization
Confucius4-T3PO-GGUF
GGUF conversions of netease-youdao/Confucius4-T3PO,
a ChineseβEnglish bidirectional streaming simultaneous translation model.
Refer to the original model card
for the streaming protocol, the latency operating points, and evaluation results.
Files
| File | Output type | Size |
|---|---|---|
Confucius4-T3PO-F16.gguf |
F16 |
29.5 GB |
Confucius4-T3PO-Q6_K.gguf |
Q6_K |
12.1 GB |
Confucius4-T3PO-Q5_K_M.gguf |
Q5_K_M |
10.5 GB |
The low-bit variants are quantized from the F16 GGUF. Start with Q6_K for a
close match to F16 quality at well under half the size; Q5_K_M trades a little
more quality for the smallest footprint. No GGUF splitting has been applied, so
the files run as-is. SHA256SUMS and CONVERSION_INFO.md record the checksums
and the exact conversion commands.
Use with llama.cpp
Compile and install llama.cpp first.
Single-shot generation:
llama-cli -m Confucius4-T3PO-Q6_K.gguf -no-cnv --temp 0 -n 128 -p "..."
OpenAI-compatible server:
llama-server -m Confucius4-T3PO-Q6_K.gguf --host 127.0.0.1 --port 8010
curl http://127.0.0.1:8010/v1/chat/completions \
-H 'content-type: application/json' \
-d '{
"temperature": 0,
"max_tokens": 128,
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "<the task prompt and the two protocol blocks>"}
]
}'
The user message must follow the streaming protocol from the original model
card: the task prompt followed by the <STREAMING_HISTORY> and
<CURRENT_INPUT> blocks. An empty response means WAIT; a non-empty one is the
next translation segment.
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