Instructions to use openbmb/MiniCPM4-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openbmb/MiniCPM4-8B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="openbmb/MiniCPM4-8B", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("openbmb/MiniCPM4-8B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use openbmb/MiniCPM4-8B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "openbmb/MiniCPM4-8B" # 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/MiniCPM4-8B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/openbmb/MiniCPM4-8B
- SGLang
How to use openbmb/MiniCPM4-8B 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/MiniCPM4-8B" \ --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/MiniCPM4-8B", "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/MiniCPM4-8B" \ --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/MiniCPM4-8B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use openbmb/MiniCPM4-8B with Docker Model Runner:
docker model run hf.co/openbmb/MiniCPM4-8B
Commit History
9 days ago
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Set native MiniCPM4 model type
Verified signatureCompanion configuration update for native MiniCPM4 support in https://github.com/huggingface/transformers/pull/47736, following the maintainers' request to update the published checkpoint configs. This PR only sets `model_type` to `minicpm4`. All other configuration values, the existing `auto_map`, and every other repository file are unchanged. No weights are uploaded or modified. The Transformers PR includes a temporary model-specific compatibility dispatcher for legacy `minicpm` configs. Correcting the metadata enables standard native AutoConfig loading, including the 0.5B checkpoint where this field is currently missing. Please coordinate merging this metadata update with the availability of the corresponding native Transformers support.447fad1
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Increase Hugging Face requirements in config.json to version 4.56.1
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Verified signature- Add model description and link to paper (f9c341a8fbe4c21c893d7e20421ba25e884ba8c9) Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>fc9b50f
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Update README.md (#4)
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