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MiniMaxAI
/
MiniMax-M1-80k

Text Generation
Transformers
Safetensors
minimax_m1
vllm
conversational
custom_code
Model card Files Files and versions
xet
Community
21

Instructions to use MiniMaxAI/MiniMax-M1-80k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use MiniMaxAI/MiniMax-M1-80k with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="MiniMaxAI/MiniMax-M1-80k", trust_remote_code=True)
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # Load model directly
    from transformers import AutoModelForCausalLM
    model = AutoModelForCausalLM.from_pretrained("MiniMaxAI/MiniMax-M1-80k", trust_remote_code=True, dtype="auto")
  • Inference
  • HuggingChat
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use MiniMaxAI/MiniMax-M1-80k with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "MiniMaxAI/MiniMax-M1-80k"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "MiniMaxAI/MiniMax-M1-80k",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/MiniMaxAI/MiniMax-M1-80k
  • SGLang

    How to use MiniMaxAI/MiniMax-M1-80k 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-M1-80k" \
        --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": "MiniMaxAI/MiniMax-M1-80k",
    		"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 "MiniMaxAI/MiniMax-M1-80k" \
            --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": "MiniMaxAI/MiniMax-M1-80k",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use MiniMaxAI/MiniMax-M1-80k with Docker Model Runner:

    docker model run hf.co/MiniMaxAI/MiniMax-M1-80k
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Update README.md

#21 opened 4 months ago by
cherry0328

使用transformer部署模型有报错

1
#19 opened 9 months ago by
chuyuelin1

Minimum requirements

3
#18 opened 10 months ago by
Julen10

update functioncall

#16 opened 10 months ago by
kamuy-shennai

HF Compatible Weights

1
#15 opened 10 months ago by
geetu040

How to get structrured output?

#14 opened 10 months ago by
Sheffchenko

使用vllm推理部署,对比了DeepSeek- R1和MiniMax-M1-80k的性能,差距很大,是什么原因?

1
#13 opened 10 months ago by
dingyuansheng

Quantization Support

#12 opened 10 months ago by
Wongibaek

Was the 7.5T Token Continual Pre-Training Performed on the Instruction-Tuned Model or the Base PLM?

3
#10 opened 11 months ago by
Jinhwan

I hope you guys can provide a 32B dense model

👍 2
#9 opened 11 months ago by
zletpm

MLX Convert Error

4
#8 opened 11 months ago by
baggaindia

main

#7 opened 11 months ago by
zwb19820615

Where's the knowledge?

🧠❤️ 8
6
#5 opened 11 months ago by
phil111

Can we expect a 20b~32b parameter minimax model to fit into a single 4090?

🚀🔥 35
#3 opened 11 months ago by
win10

WHAT a benchmarks graph

👍 13
1
#2 opened 11 months ago by
CyborgPaloma

gguf weights for llama.cpp?

👍🧠 24
1
#1 opened 11 months ago by
segmond
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