Text Generation
Transformers
Safetensors
English
grt
geometric-rotation-transformer
causal-lm
rotational
Instructions to use MatterWaveAI/grt-10m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MatterWaveAI/grt-10m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="MatterWaveAI/grt-10m")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("MatterWaveAI/grt-10m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use MatterWaveAI/grt-10m with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "MatterWaveAI/grt-10m" # 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-10m", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/MatterWaveAI/grt-10m
- SGLang
How to use MatterWaveAI/grt-10m 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-10m" \ --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-10m", "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-10m" \ --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-10m", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use MatterWaveAI/grt-10m with Docker Model Runner:
docker model run hf.co/MatterWaveAI/grt-10m
Publish MatterWaveAI/grt-10m with 10-task SLM-Bench evaluation (T-040)
Browse files- config.json +30 -0
config.json
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{
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"angle_init_scale": 0.1,
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"architectures": [
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"GRTForCausalLM"
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],
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"bos_token_id": 2,
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"coupling_init_scale": 0.01,
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"d_ff": null,
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"d_model": 256,
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"dropout": 0.0,
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"eos_token_id": 3,
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"ffn_mult": 4,
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"ffn_n_rotations": 9,
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"learnable_rope": true,
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"log_magnitude_init": 0.0,
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"max_seq_len": 1024,
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"model_type": "grt",
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"n_blocks": 6,
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"n_heads": 4,
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"n_mixer_rotations": 1,
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"n_qkv_rotations": 5,
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"num_hidden_layers": 6,
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"output_scale_init": 30.0,
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"pad_token_id": 0,
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"phase_init_scale": 0.1,
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"pos_freq_base": 10000.0,
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"residual_gate_mode": "bounded_depth",
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"transformers_version": "5.10.2",
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"vocab_size": 50000
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}
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