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
Link MatterWaveAI/grt-10m-base in GRT-10M model card
Browse files- SHA256SUMS +1 -1
SHA256SUMS
CHANGED
|
@@ -1,6 +1,6 @@
|
|
| 1 |
ed4458b69e63f88515162ab0599abc54b6ef6f61ca5133d0d6740555e61eb960 config.json
|
| 2 |
433d041c312ca8c87cc3bd15335ab1047e7c3ca5d73283f4f8c563bf7b76bca3 eval_results.json
|
| 3 |
40fd3dd28b960375780e4fbb68923ddb7204106ed993f9467ea3f2b02ab3ae57 model.safetensors
|
| 4 |
-
|
| 5 |
5f31bc9fb786cac939f638270633434095be6640ef7c530b316bd42636c5d975 slm_bench_results.json
|
| 6 |
fc0fab0e6fad9006677fe4a1161e7538acf1c644464d04e810f64ba5901c473e tokenizer.json
|
|
|
|
| 1 |
ed4458b69e63f88515162ab0599abc54b6ef6f61ca5133d0d6740555e61eb960 config.json
|
| 2 |
433d041c312ca8c87cc3bd15335ab1047e7c3ca5d73283f4f8c563bf7b76bca3 eval_results.json
|
| 3 |
40fd3dd28b960375780e4fbb68923ddb7204106ed993f9467ea3f2b02ab3ae57 model.safetensors
|
| 4 |
+
b1bf41474d4f237f50815dd56713c7795b9568206b1bc5b3eaeecb2388286acc README.md
|
| 5 |
5f31bc9fb786cac939f638270633434095be6640ef7c530b316bd42636c5d975 slm_bench_results.json
|
| 6 |
fc0fab0e6fad9006677fe4a1161e7538acf1c644464d04e810f64ba5901c473e tokenizer.json
|