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
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We recommend using [Transformers](https://github.com/huggingface/transformers) to serve MiniMax-M2.1. Please refer to our [Transformers Deployment Guide](./docs/transformers_deploy_guide.md).
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### Other Inference Engines
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- [MLX-LM](./docs/mlx_deploy_guide.md)
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- [KTransformers](https://github.com/kvcache-ai/ktransformers/blob/main/doc/en/kt-kernel/MiniMax-M2.1-Tutorial.md)
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### Inference Parameters
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We recommend using [Transformers](https://github.com/huggingface/transformers) to serve MiniMax-M2.1. Please refer to our [Transformers Deployment Guide](./docs/transformers_deploy_guide.md).
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### KTransformers
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We recommend using [KTransformers](https://github.com/kvcache-ai/ktransformers) to serve MiniMax-M2.1. Please refer to [KTransformers Deployment Guide](https://github.com/kvcache-ai/ktransformers/blob/main/doc/en/kt-kernel/MiniMax-M2.1-Tutorial.md)
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### Other Inference Engines
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- [MLX-LM](./docs/mlx_deploy_guide.md)
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### Inference Parameters
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