Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Hardware
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

MatterWaveAI
/
grt-30m-mor

Text Generation
Transformers
Safetensors
grt
geometric-rotation-transformer
mixture-of-rotations
mor
Mixture of Experts
rotational-transformer
givens-rotations
clifford-algebra
matterwave
Model card Files Files and versions
xet
Community

Instructions to use MatterWaveAI/grt-30m-mor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use MatterWaveAI/grt-30m-mor with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="MatterWaveAI/grt-30m-mor")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoModelForCausalLM
    model = AutoModelForCausalLM.from_pretrained("MatterWaveAI/grt-30m-mor", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use MatterWaveAI/grt-30m-mor with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "MatterWaveAI/grt-30m-mor"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "MatterWaveAI/grt-30m-mor",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/MatterWaveAI/grt-30m-mor
  • SGLang

    How to use MatterWaveAI/grt-30m-mor 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 "MatterWaveAI/grt-30m-mor" \
        --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": "MatterWaveAI/grt-30m-mor",
    		"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 "MatterWaveAI/grt-30m-mor" \
            --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": "MatterWaveAI/grt-30m-mor",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use MatterWaveAI/grt-30m-mor with Docker Model Runner:

    docker model run hf.co/MatterWaveAI/grt-30m-mor
grt-30m-mor
143 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 21 commits
davidhouseholter's picture
davidhouseholter
Update SHA256SUMS
354b1d0 verified about 10 hours ago
  • .gitattributes
    1.63 kB
    Add GRT_Whitepaper.pdf about 11 hours ago
  • GRT_Whitepaper.pdf
    1.02 MB
    xet
    Update GRT_Whitepaper.pdf (clean page 1 author/header/footer + GRT-30M results) about 10 hours ago
  • README.md
    6.79 kB
    Update README: remove GNU Free Software Statement, keep Apache 2.0 and matterwave.ai citation about 10 hours ago
  • SHA256SUMS
    673 Bytes
    Update SHA256SUMS about 10 hours ago
  • config.json
    1.13 kB
    Release MatterWaveAI/grt-30m-mor (4-expert Mixture-of-Rotations, 0 nn.Linear layers) about 12 hours ago
  • eval_results.json
    4.3 kB
    Release MatterWaveAI/grt-30m-mor (4-expert Mixture-of-Rotations, 0 nn.Linear layers) about 12 hours ago
  • generation_config.json
    177 Bytes
    Release MatterWaveAI/grt-30m-mor (4-expert Mixture-of-Rotations, 0 nn.Linear layers) about 12 hours ago
  • model.safetensors
    131 MB
    xet
    Release MatterWaveAI/grt-30m-mor (4-expert Mixture-of-Rotations, 0 nn.Linear layers) about 12 hours ago
  • tokenizer.json
    11.4 MB
    xet
    Release MatterWaveAI/grt-30m-mor (4-expert Mixture-of-Rotations, 0 nn.Linear layers) about 12 hours ago
  • tokenizer_config.json
    726 Bytes
    Release MatterWaveAI/grt-30m-mor (4-expert Mixture-of-Rotations, 0 nn.Linear layers) about 12 hours ago