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Inferact
/
MiniMax-M3-EAGLE3-GQA-NVFP4

Text Generation
Transformers
Safetensors
llama
eagle3
speculative-decoding
draft-model
gqa
vllm
nvfp4
quantized
text-generation-inference
modelopt
Model card Files Files and versions
xet
Community

Instructions to use Inferact/MiniMax-M3-EAGLE3-GQA-NVFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Inferact/MiniMax-M3-EAGLE3-GQA-NVFP4 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="Inferact/MiniMax-M3-EAGLE3-GQA-NVFP4")
    # Load model directly
    from transformers import AutoTokenizer, LlamaForCausalLMEagle3
    
    tokenizer = AutoTokenizer.from_pretrained("Inferact/MiniMax-M3-EAGLE3-GQA-NVFP4")
    model = LlamaForCausalLMEagle3.from_pretrained("Inferact/MiniMax-M3-EAGLE3-GQA-NVFP4")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use Inferact/MiniMax-M3-EAGLE3-GQA-NVFP4 with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "Inferact/MiniMax-M3-EAGLE3-GQA-NVFP4"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Inferact/MiniMax-M3-EAGLE3-GQA-NVFP4",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/Inferact/MiniMax-M3-EAGLE3-GQA-NVFP4
  • SGLang

    How to use Inferact/MiniMax-M3-EAGLE3-GQA-NVFP4 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 "Inferact/MiniMax-M3-EAGLE3-GQA-NVFP4" \
        --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": "Inferact/MiniMax-M3-EAGLE3-GQA-NVFP4",
    		"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 "Inferact/MiniMax-M3-EAGLE3-GQA-NVFP4" \
            --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": "Inferact/MiniMax-M3-EAGLE3-GQA-NVFP4",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use Inferact/MiniMax-M3-EAGLE3-GQA-NVFP4 with Docker Model Runner:

    docker model run hf.co/Inferact/MiniMax-M3-EAGLE3-GQA-NVFP4
MiniMax-M3-EAGLE3-GQA-NVFP4
5.66 GB
Ctrl+K
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  • 1 contributor
History: 4 commits
ZixiQi's picture
ZixiQi
Add acceptance-rate Performance section (MT-Bench + SPEED-Bench, per-position)
f0a1fea verified 1 day ago
  • .gitattributes
    1.52 kB
    initial commit 2 days ago
  • MiniMax M3 LICENSE.txt
    3.34 kB
    Add NVFP4 W4A4 MLP-quantized EAGLE3 GQA draft (block 16, calibrated input_scale) + model card 1 day ago
  • README.md
    904 Bytes
    Add acceptance-rate Performance section (MT-Bench + SPEED-Bench, per-position) 1 day ago
  • config.json
    1.43 kB
    Add NVFP4 W4A4 MLP-quantized EAGLE3 GQA draft (block 16, calibrated input_scale) + model card 1 day ago
  • hf_quant_config.json
    356 Bytes
    Add NVFP4 W4A4 MLP-quantized EAGLE3 GQA draft (block 16, calibrated input_scale) + model card 1 day ago
  • model.safetensors
    5.66 GB
    xet
    Add NVFP4 W4A4 MLP-quantized EAGLE3 GQA draft (block 16, calibrated input_scale) + model card 1 day ago