Instructions to use openbmb/MiniCPM4-Survey with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openbmb/MiniCPM4-Survey with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="openbmb/MiniCPM4-Survey", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("openbmb/MiniCPM4-Survey", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use openbmb/MiniCPM4-Survey with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "openbmb/MiniCPM4-Survey" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "openbmb/MiniCPM4-Survey", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/openbmb/MiniCPM4-Survey
- SGLang
How to use openbmb/MiniCPM4-Survey with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "openbmb/MiniCPM4-Survey" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "openbmb/MiniCPM4-Survey", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "openbmb/MiniCPM4-Survey" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "openbmb/MiniCPM4-Survey", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use openbmb/MiniCPM4-Survey with Docker Model Runner:
docker model run hf.co/openbmb/MiniCPM4-Survey
| :root { | |
| font-family: system-ui, Avenir, Helvetica, Arial, sans-serif; | |
| line-height: 1.5; | |
| font-weight: 400; | |
| color-scheme: light dark; | |
| color: rgba(255, 255, 255, 0.87); | |
| background-color: #242424; | |
| font-synthesis: none; | |
| text-rendering: optimizeLegibility; | |
| -webkit-font-smoothing: antialiased; | |
| -moz-osx-font-smoothing: grayscale; | |
| } | |
| a { | |
| font-weight: 500; | |
| color: #646cff; | |
| text-decoration: inherit; | |
| } | |
| a:hover { | |
| color: #535bf2; | |
| } | |
| body { | |
| margin: 0; | |
| display: flex; | |
| place-items: center; | |
| min-width: 320px; | |
| min-height: 100vh; | |
| } | |
| h1 { | |
| font-size: 3.2em; | |
| line-height: 1.1; | |
| } | |
| button { | |
| border-radius: 8px; | |
| border: 1px solid transparent; | |
| padding: 0.6em 1.2em; | |
| font-size: 1em; | |
| font-weight: 500; | |
| font-family: inherit; | |
| background-color: #1a1a1a; | |
| cursor: pointer; | |
| transition: border-color 0.25s; | |
| } | |
| button:hover { | |
| border-color: #646cff; | |
| } | |
| button:focus, | |
| button:focus-visible { | |
| outline: 4px auto -webkit-focus-ring-color; | |
| } | |
| @media (prefers-color-scheme: light) { | |
| :root { | |
| color: #213547; | |
| background-color: #ffffff; | |
| } | |
| a:hover { | |
| color: #747bff; | |
| } | |
| button { | |
| background-color: #f9f9f9; | |
| } | |
| } | |