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MiniMaxAI
/
MiniMax-M2.1

Text Generation
Transformers
Safetensors
Eval Results
Model card Files Files and versions
xet
Community
35

Instructions to use MiniMaxAI/MiniMax-M2.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use MiniMaxAI/MiniMax-M2.1 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="MiniMaxAI/MiniMax-M2.1")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("MiniMaxAI/MiniMax-M2.1", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use MiniMaxAI/MiniMax-M2.1 with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "MiniMaxAI/MiniMax-M2.1"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "MiniMaxAI/MiniMax-M2.1",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/MiniMaxAI/MiniMax-M2.1
  • SGLang

    How to use MiniMaxAI/MiniMax-M2.1 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 "MiniMaxAI/MiniMax-M2.1" \
        --host 0.0.0.0 \
        --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "MiniMaxAI/MiniMax-M2.1",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    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 "MiniMaxAI/MiniMax-M2.1" \
            --host 0.0.0.0 \
            --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "MiniMaxAI/MiniMax-M2.1",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use MiniMaxAI/MiniMax-M2.1 with Docker Model Runner:

    docker model run hf.co/MiniMaxAI/MiniMax-M2.1
MiniMax-M2.1 / docs
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  • 6 contributors
History: 6 commits
AntonV's picture
AntonV HF Staff
update docs
1f5d476 5 months ago
  • sglang_deploy_guide.md
    3.55 kB
    update: use nightly sglang 5 months ago
  • sglang_deploy_guide_cn.md
    3.51 kB
    update: use nightly sglang 5 months ago
  • tool_calling_guide.md
    16.6 kB
    update: add toolcall docs 5 months ago
  • tool_calling_guide_cn.md
    16.7 kB
    update: add toolcall docs 5 months ago
  • transformers_deploy_guide.md
    2.86 kB
    update docs 5 months ago
  • transformers_deploy_guide_cn.md
    2.74 kB
    update docs 5 months ago
  • vllm_deploy_guide.md
    4.19 kB
    udpate: guide use nightly vllm 5 months ago
  • vllm_deploy_guide_cn.md
    4.11 kB
    udpate: guide use nightly vllm 5 months ago