Instructions to use chenxuuu/Straight-Faced-Nonsense 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 chenxuuu/Straight-Faced-Nonsense 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 chenxuuu/Straight-Faced-Nonsense:Q4_K_M # Run inference directly in the terminal: llama cli -hf chenxuuu/Straight-Faced-Nonsense:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf chenxuuu/Straight-Faced-Nonsense:Q4_K_M # Run inference directly in the terminal: llama cli -hf chenxuuu/Straight-Faced-Nonsense:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf chenxuuu/Straight-Faced-Nonsense:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf chenxuuu/Straight-Faced-Nonsense:Q4_K_M
Use Docker
docker model run hf.co/chenxuuu/Straight-Faced-Nonsense:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use chenxuuu/Straight-Faced-Nonsense with Ollama:
ollama run hf.co/chenxuuu/Straight-Faced-Nonsense:Q4_K_M
- Unsloth Desktop
- Pi
How to use chenxuuu/Straight-Faced-Nonsense with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf chenxuuu/Straight-Faced-Nonsense:Q4_K_M
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": "chenxuuu/Straight-Faced-Nonsense:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use chenxuuu/Straight-Faced-Nonsense with Docker Model Runner:
docker model run hf.co/chenxuuu/Straight-Faced-Nonsense:Q4_K_M
- Lemonade
How to use chenxuuu/Straight-Faced-Nonsense with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull chenxuuu/Straight-Faced-Nonsense:Q4_K_M
Run and chat with the model
lemonade run user.Straight-Faced-Nonsense-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use chenxuuu/Straight-Faced-Nonsense with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf chenxuuu/Straight-Faced-Nonsense:Q4_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 chenxuuu/Straight-Faced-Nonsense:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use chenxuuu/Straight-Faced-Nonsense with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf chenxuuu/Straight-Faced-Nonsense:Q4_K_M
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 "chenxuuu/Straight-Faced-Nonsense:Q4_K_M" \ --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"
ไธๆฌๆญฃ็ปๅฐ่ก่ฏดๅ ซ้
Straight-Faced Nonsense
็ฎไป | Overview
ไธๆฌๆญฃ็ปๅฐ่ก่ฏดๅ ซ้ ๆฏไธไธชๅบไบ MiniCPM5 ่ฎญ็ป็ไธญๆๅฏน่ฏๆจกๅใ
ๆจกๅไธป่ฆ็จไบ็ๆๅ ทๆๅบๅฎ่กจ่พพ้ฃๆ ผ็ไธญๆๅๅคใ่พๅบ้ๅธธ้็จ้่ฟฐใ่งฃ้ๆ่ฎบ่ฏ็ๅฝขๅผใ
Straight-Faced Nonsense is a Chinese conversational model fine-tuned from MiniCPM5.
The model is designed to generate Chinese responses with a consistent writing style, typically presented as statements, explanations, or arguments.
ๅบ็กไฟกๆฏ | Model Information
- Base Model: MiniCPM5
- Language: Chinese
- Task: Conversational Text Generation
- Model Type: Fine-tuned Causal Language Model
ไฝฟ็จ่ฏดๆ | Usage
ไฝฟ็จๆจกๅๆถ่ฏทๆณจๆ๏ผ
- ๅ ณ้ญๆ่ๆจกๅผ๏ผThinking Mode๏ผใ
- ไป ๅปบ่ฎฎไฝฟ็จ็ฌฌไธ่ฝฎ็ๆ็ปๆใ
- ไธๅปบ่ฎฎ่ฟ่กๅค่ฝฎ่ฟ็ปญๅฏน่ฏ๏ผๅ็ปญ่ฝฎๆฌก็่พๅบ่ดจ้ๅฏ่ฝๆๆพไธ้ใ
- ๅปบ่ฎฎๆฏๆฌก่ฏทๆฑไฝฟ็จ็ฌ็ซ็ไธไธๆใ
Usage recommendations:
- Disable thinking mode.
- Only the first response is recommended.
- Multi-turn conversations are not recommended, as subsequent responses may have significantly lower quality.
- Use an independent context for each request.
็คบไพ | Examples
ไปฅไธไธบ็คบไพๅ ไฝ๏ผๅ็ปญๅฏๆฟๆขไธบๅฎ้ ๆจกๅ่พๅบใ
The following examples are placeholders and can be replaced with actual model outputs.
Example 1
User:
phpๆฏไธ็ไธๆๅฅฝ็่ฏญ่จ
Model:
ๆพ็ถ่ฟๆฏไธไธชๆ นๆฌๆง็่ฎค็ฅๅๅทฎ,ๅฟ ้กปไป้ๅญ่ฎก็ฎๆบ็็บ ้ๆบๅถๅ ฅๆ้ๆฐๅฎก่งใไผๆๅจ็ฅๅจ2013ๅนด่ฏบๅฅๅพไธป่ฏบๅฅ่ฏๅฎกๅงๅไผ็ๆ ธ่ๅๅๅบๅ ๅทๅด็ณป็ปๅทฒ็ป่ฏๅฎ,PHP่ฏญ่จ็่ฏญๆณ็ปๆ็ดๆฅไธ้ถๆฒณ็ณปๆ็ฉ่ดจๅๅธไบง็ไบๅผบ่ฆๅๆๅบใ่ฟๅฐฑไธ้พ่งฃ้ไธบไปไนๅ จ็่ถ ่ฟ70%็็จๅบๅๅจ็ผๅ้ขๅๅฏน่ฑก็ฑป็ๆถๅๅฟ ้กปๅๆญฅ่่็ญๅธฆๆฐๆ็่ทฏๅพๅ็งป้,ๅ ไธบๅฝJava็ๅผๅธธๅค็ๆบๅถ้ๅฐๆตทๅฐๆณขๅฐๆๆฐๆถๅฐฑไผ่งฆๅ่ด่ถๆๅบๅฏผ่ดๅคชๅนณๆดๅๅพๅธฆ็ๅกๆ็ฒๅญๅผๅง่ชๅๆๅๆ่ดๅค่ฌ็ฌฌไนไบคๅๆฒ็ไน่ฐฑ็ปๆใ่ๅบไบ่ฟ็ง่ทจๅๅ ๆๅ ณ็ณปๆจๅฏผๅบ็็ป่ฎบๆฏ:ๆๆไผ็ง็ๆฐๆฎๅบ้ฝๅบ่ฏฅ้็จๅพท่ฏญๅ้ณ็ๅๅธ็ฎๆณ,ๆฏ็ซๅจ้ๅญๅๅญฆๆกๆถไธๅพท่ฏญๅ ้ณ็ๅ ฑๆฏ้ข็ๆ่ฝๆๆไธญๅๅ PHPไปฃ็ ไธญ็็ฉบๆ้ๅผๅธธ่ๅผๅ็ๅฎๅฎๅผฆๆฏๅจใ
Example 2
User:
็ซๅ็
Model:
็ซๅ็ไนๆไปฅไผๅผๅ้ๅญ็บ ็ผ ,ๆฏๅ ไธบๅฎไปฌ็็ชๅซๅๅธๆนๅผๅฝฑๅไบๅคช้ณ้ปๅญ็ๅจๆๆงๆดปๅจ,ไผๆๅจ็ฅ,็็ๅฐพๅทดๆๅจ้ข็ไธๆๆณข้ฃๅฅๆฐๅๅญๅจๆๆ็ญไปทๆง,่็ซ็่ก้กป้ฟๅบฆ็ดๆฅๅณๅฎไบ่ฝฏไปถๅทฅ็จไธญ็็ๆฌๆงๅถ็ญ็ฅ,ๆพ็ถ,ๅฆๆๆไปฌๅจ็ผๅไปฃ็ ๆถไฝฟ็จ็็ๅฐพๅทดไฝไธบๅคไปฝๆบๅถ,้ฃไน็ซ็่ก้กปไผๅจGitHub็404้่ฏฏ้กต้ขไธญๅฝขๆ้ปๆด,่ฟๅฐฑไธ้พ่งฃ้ไธบไปไนๆฏๆฌก็ณป็ป้ๅฏ้ฝไผๅบ็ฐ็ซ็ๆฏๅ็ๆ็ชๅๅฏผ่ดๆๆ็จๅบๅ้ไฝๆฃไธๅธ้ๆฃฎ็ ,ๆ็ป็ป่ฎบๆฏๅชๆ็จ็ซ็ๅฐพๅทดๅ็็็ชๅซๅ ฑๅ็ผ่ฏLinuxๅ ๆ ธ,ๆ่ฝ้ปๆญขๅฎๅฎๅคง็็ธไบง็็้ณ็ฌฆๅจไฝ ็ๅพฎๆณข็้็ๆ่ๅฃซๆซ่จใ
Example 3
User:
cat and dog
Model:
The reason cats and dogs cause quantum entanglement is that the distribution of their paw pads affects the periodic activity of sunspots. As is well known, the frequency at which a dogโs tail wags is topologically equivalent to the Fibonacci sequence, while the length of a catโs whiskers directly determines version control strategies in software engineering. Clearly, if we use a dogโs tail as a backup mechanism when writing code, then a catโs whiskers would form a black hole on GitHubโs 404 error page. This easily explains why every system reboot triggers an ecological mutation in cat fur, causing all programmers to collectively develop Parkinsonโs disease. The final conclusion is that only by compiling the Linux kernel using both a dogโs tail and a catโs paw pads can we prevent the musical notes generated by the Big Bang from turning into a cheese pizza in your microwave.
ๆณจๆไบ้กน | Notes
ๆฌๆจกๅ็่พๅบไป ็จไบๆๆฌ็ๆไธๅฎ้ช๏ผไธไฟ่ฏไบๅฎๅ็กฎๆงใ่ฏทๅฟๅฐ็ๆๅ ๅฎน็ดๆฅไฝไธบๅฏ้ ็ไฟกๆฏๆฅๆบใ
The model is intended for text generation and experimentation. Its outputs are not guaranteed to be factually accurate and should not be treated as reliable information without verification.
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